WO2019010714A1 - 一种波束成形方法及设备 - Google Patents

一种波束成形方法及设备 Download PDF

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Publication number
WO2019010714A1
WO2019010714A1 PCT/CN2017/093052 CN2017093052W WO2019010714A1 WO 2019010714 A1 WO2019010714 A1 WO 2019010714A1 CN 2017093052 W CN2017093052 W CN 2017093052W WO 2019010714 A1 WO2019010714 A1 WO 2019010714A1
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Prior art keywords
path
frequency response
channel
polarization
frequency
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PCT/CN2017/093052
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English (en)
French (fr)
Inventor
种稚萌
冯荻
张晓媚
曲景峰
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华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN201780092878.4A priority Critical patent/CN110870216B/zh
Priority to KR1020207003842A priority patent/KR102266761B1/ko
Priority to PCT/CN2017/093052 priority patent/WO2019010714A1/zh
Priority to EP17917246.5A priority patent/EP3648364B1/en
Publication of WO2019010714A1 publication Critical patent/WO2019010714A1/zh
Priority to US16/742,366 priority patent/US11265054B2/en

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413MIMO systems
    • H04B7/0456Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/046Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account
    • H04B7/0469Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account taking special antenna structures, e.g. cross polarized antennas into account
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842Weighted combining
    • H04B7/086Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/022Channel estimation of frequency response
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00Modulated-carrier systems
    • H04L27/26Systems using multi-frequency codes
    • H04L27/2601Multicarrier modulation systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00Modulated-carrier systems
    • H04L27/26Systems using multi-frequency codes
    • H04L27/2601Multicarrier modulation systems
    • H04L27/2626Arrangements specific to the transmitter only
    • H04L27/2646Arrangements specific to the transmitter only using feedback from receiver for adjusting OFDM transmission parameters, e.g. transmission timing or guard interval length

Definitions

  • the embodiments of the present application relate to the field of communications technologies, and in particular, to a beamforming method and device.
  • Massive MIMO technology can provide greater spatial freedom.
  • Massive MIMO beamforming technology automatically adjusts the transmit or receive antenna pattern for better coverage and capacity performance.
  • An existing beamforming scheme is to construct a beamforming weight according to a precoding matrix indicator (PMI) reported by a terminal, thereby performing beamforming according to the weight of the beamforming.
  • PMI precoding matrix indicator
  • the terminal calculates a frequency response h DL of the downlink channel according to the received signal, and calculates, for each candidate weight w m , a beamforming signal to noise ratio (SNR) that may be obtained on the base station antenna array by weighting on the channel.
  • SNR beamforming signal to noise ratio
  • the terminal selects the M with the largest SNR/reception power gain as the PMI to report to the base station, and the base station selects the corresponding candidate weights under the same codebook set according to the PMI, and performs weightforming on the antenna array.
  • the solution in the prior art requires the terminal to feed back the PMI to the base station after determining the h DL to determine the weight of the beamforming, thereby performing beamforming.
  • This feedback mechanism reduces the real-time performance of the beamforming. In this way, when the base station waits for the feedback of the terminal and then performs beamforming, the channel has changed due to factors such as environmental changes and terminal movement, and the base station uses the PMI of the channel before the change to perform beamforming, which causes a large error.
  • the embodiment of the present invention provides a beamforming method and device.
  • the terminal does not need to perform feedback, thereby improving the real-time performance of the beamforming.
  • a beamforming method comprising: first, an access network device calculates a frequency response of an uplink channel. Then, the access network device calculates a model parameter in the mathematical model of the frequency response of the channel according to the frequency response of the uplink channel and the frequency of each uplink subcarrier. The model parameter has reciprocity at the upper and lower subcarrier frequency points. After that, the access network device constructs a frequency response of the downlink channel according to the model parameters, the frequency response mathematical model of the channel, and the frequency of each downlink subcarrier. Then, the access network device calculates the weight of the beamforming of each downlink subcarrier frequency according to the frequency response of the downlink channel. Further, the access network device performs downlink beamforming on the antenna array according to the weight, and the antenna array is a dual-polarized antenna array or a single-polarized antenna array.
  • the access network device can directly construct the frequency response of the downlink channel according to the frequency response of the uplink channel and the frequency response of the channel, and calculate the weight of the beamforming according to the frequency response of the downlink channel, thereby performing beamforming, and thus Calculating the weight of beamforming does not require the terminal to perform feedback as in the prior art, thereby improving the real-time performance of beamforming and reducing errors due to poor real-time performance.
  • the model parameters include the path of each path, the angle of arrival of each path, the amplitude of each path, and the initial phase of each path.
  • the independent variables in the frequency response mathematical model of the channel may include the path of each path, the angle of arrival of each path, the amplitude of each path, and the initial phase of each path.
  • the access network device calculates a model parameter in a frequency response mathematical model of the channel according to the frequency response of the uplink channel and each uplink subcarrier frequency point.
  • the method includes: First, the access network device constructs a target likelihood spectrum of the frequency response of the uplink channel according to the frequency response of the uplink channel and the frequency of each uplink subcarrier. Then, the access network device calculates the target value of each path and the target value of the arrival angle of each path according to the target likelihood spectrum. Thereafter, the access network device calculates a target value of the amplitude of each path and a target value of the initial phase of each path based on the target value of the path of each path and the target value of the angle of arrival of each path.
  • the method of obtaining the model parameters by constructing the target likelihood spectrum and searching for the peaks on the target likelihood spectrum is relatively simple.
  • the target likelihood spectrum is a spatial spectrum formed by coherent accumulation of the steering vector conjugate compensation for the frequency response of the uplink channel.
  • the true value can be highlighted in the peak of the target likelihood spectrum, so that the way to solve the model parameters by searching the spectral peak is faster and more accurate.
  • the access network device calculates, according to the target likelihood spectrum, a target value of each path and a target value of an arrival angle of each path, including: an access network.
  • the device calculates an initial value of the path of each path and an initial value of the angle of arrival of each path according to the target likelihood spectrum.
  • the access network device calculates the target value of the path of each path and the target value of the arrival angle of each path by an optimization algorithm according to the initial value of the path of each path and the initial value of the arrival angle of each path.
  • the access network device can obtain the initial value of the model parameter simply and quickly by searching for the peak on the target likelihood spectrum, and then accurately solve the target value of each model parameter by the optimization algorithm.
  • the access network device calculates, according to the target likelihood spectrum, a target value of each path and a target value of an arrival angle of each path, including: an access network.
  • the device calculates an initial value of the path of each path and an initial value of the angle of arrival of each path according to the target likelihood spectrum.
  • the access network device calculates a target value of the path of each path and a target value of the arrival angle of each path by a search algorithm according to the target likelihood spectrum, the initial value of the path of each path, and the initial value of the arrival angle of each path.
  • the access network device solves the initial value and the target value of each model parameter by searching for the peak value on the target likelihood spectrum, which is relatively simple.
  • the access network device solves the target value of each model parameter by using an optimization algorithm according to the frequency response of the uplink channel.
  • the access network device directly solves the model parameters in the entire parameter space, and thus is more accurate.
  • the frequency response mathematical model of the channel does not include the direction information.
  • the expression of the frequency response mathematical model of the channel is:
  • F(k,i) represents the mathematical model of the frequency response of the channel
  • N represents the number of paths
  • d n represents the path of the nth path
  • ⁇ n Indicates the angle of arrival of the nth path
  • a n represents the amplitude of the nth path
  • ⁇ n represents the initial phase of the nth path
  • I denotes the number of subcarrier frequency points
  • I denotes the number of subcarrier frequency points
  • k 1, 2, ...
  • K denotes the number of array elements
  • l denotes the array element spacing .
  • the expression provides a concrete form of a simple channel frequency response mathematical model.
  • the expression of the target likelihood spectrum of the frequency response of the uplink channel is:
  • ⁇ (d, ⁇ ) represents the target likelihood spectrum
  • h UL (k, i) represents the frequency response of the uplink channel
  • d represents the path of the path
  • represents the angle of arrival of the path
  • i represents the ith uplink
  • I represents the number of the subcarrier frequency point
  • I represents the number of subcarrier frequency points
  • k 1, 2, ...
  • K represents the array element
  • 2 represents the Euclidean norm.
  • the expression provides a concrete form of the target likelihood spectrum obtained by conjugate compensation and coherent accumulation.
  • the expression of the frequency response mathematical model of the channel is:
  • ⁇ n represents the angle of arrival of the nth path
  • a n represents the amplitude of the nth path
  • ⁇ n represents the initial phase of the nth path
  • ⁇ i represents the wavelength corresponding to the frequency of the i th subcarrier
  • i 1 , 2 ...
  • I represents the number of subcarrier frequency points
  • I represents the number of subcarrier frequency points
  • k 1, 2, ...
  • K represents the number of array elements, the number of K array elements
  • l Indicates the array element spacing
  • k H represents the number of rows of the antenna array
  • k V represents the number of columns of the antenna array.
  • ⁇ n represents the pitch angle
  • the expression provides a concrete form of the mathematical model of the frequency response of the channel in the case of an area array.
  • the frequency response of the uplink channel includes a frequency response of the first polarized uplink channel and a second The frequency response of the polarized uplink channel
  • the model parameters include a first polarization model parameter and a second polarization model parameter
  • the model parameters conform to the following expression:
  • argmin represents the variable value when the objective function obtains the minimum value
  • i represents the number of the subcarrier frequency point
  • k represents the number of the array element
  • represents the wavelength corresponding to the subcarrier frequency point
  • ⁇ UL represents the uplink subcarrier frequency point.
  • a mathematical model of the frequency response representing the first polarized uplink channel, a mathematical model representing the frequency response of the second polarized uplink channel, and F representing a mathematical model of the frequency response of the channel Representing the frequency response of the first polarized uplink channel, Indicates the frequency response of the second polarized upstream channel
  • 2 represents the Euclidean norm.
  • the access network device can jointly solve the model parameters according to the dual-polarization information by adding the dual-polarized optimization objective functions, thereby further highlighting the true multipath optimization target.
  • the peak formed on the function which suppresses noise and the like, forms a pseudo peak formed on the target optimization function, thereby reducing the number of iterations and facilitating more efficient and accurate determination of model parameters in the case of dual polarization.
  • the frequency response of the uplink channel includes a frequency response of the first polarized uplink channel and a second The frequency response of the polarized upstream channel.
  • the target network spectrum of the access network device according to the frequency response of the uplink channel and the frequency of each uplink subcarrier, and the target likelihood spectrum of the frequency response of the uplink channel includes: the frequency response of the access network device according to the first polarization uplink channel and each uplink subcarrier The frequency point is used to construct a first polarization likelihood spectrum of the frequency response of the uplink channel.
  • the access network device constructs a second polarization likelihood spectrum of the frequency response of the uplink channel according to the frequency response of the second polarized uplink channel and each uplink subcarrier frequency.
  • the sum of the first polarization likelihood spectrum and the second polarization likelihood spectrum is the target likelihood spectrum.
  • the access network device can solve the model parameters by combining the first polarization likelihood spectrum and the second polarization likelihood spectrum, thereby further highlighting the true multipath in the target likelihood spectrum.
  • the peak formed on the spectrum suppresses the pseudo peak formed on the target likelihood spectrum by relatively suppressing noise, so that the number of iterations can be reduced, and the model parameters can be determined more simply, efficiently, and accurately.
  • the amplitude of each path when the antenna array is a dual-polarized antenna array, the amplitude of each path includes the amplitude and the second of each path corresponding to the first polarization.
  • the access network device constructs the frequency response of the downlink channel according to the model parameter, the frequency response mathematical model of the channel, and the downlink subcarrier frequency points, including: the distance of each path in the model parameter according to the model parameter, the arrival angle of each path, The amplitude of each path corresponding to the first polarization, the initial phase of each path corresponding to the first polarization, the frequency response mathematical model of the channel, and the frequency of each downlink subcarrier establish a frequency response of the first polarization downlink channel.
  • the access network device according to the path of each path in the model parameter, the arrival angle of each path, the amplitude of each path corresponding to the second polarization, the initial phase of each path corresponding to the second polarization, and the frequency response of the channel
  • the model and each downlink subcarrier frequency point construct a frequency response of the second polarized downlink channel.
  • the access network device can separately construct the frequency response of the dual-polarized downlink channel according to the dual-polarization information.
  • the weight includes a first polarization weight and a second polarization weight.
  • the access network device calculates the weight of the beamforming of each downlink subcarrier frequency according to the frequency response of the downlink channel, and the access network device calculates the downlink corresponding to the first polarization according to the frequency response of the first polarization downlink channel.
  • the weight of the beamforming of the subcarrier frequency is calculated, according to the frequency response of the second polarized downlink channel, a weight of beamforming of each downlink subcarrier frequency point corresponding to the second polarization.
  • the access network device can calculate the weight of the beamforming of each downlink sub-carrier frequency corresponding to the dual-polarization according to the dual-polarization information.
  • model parameters conform to the following expression:
  • argmin represents the variable value when the objective function obtains the minimum value
  • i represents the number of the subcarrier frequency point
  • k represents the number of the array element
  • represents the wavelength corresponding to the subcarrier frequency point
  • ⁇ UL represents the uplink subcarrier frequency point.
  • F UL represents the mathematical model of the frequency response of the upstream channel
  • F represents the mathematical model of the frequency response of the channel
  • h UL represents the frequency response of the upstream channel
  • 2 represents the Euclidean norm.
  • an embodiment of the present application provides an access network device, including: a first calculating unit, configured to calculate a frequency response of an uplink channel.
  • the second calculating unit is configured to calculate a model parameter in a frequency response mathematical model of the channel according to the frequency response of the uplink channel and each uplink subcarrier frequency point, and the model parameter has reciprocity in the upper and lower subcarrier frequency points.
  • a building unit is configured to construct a frequency response of the downlink channel according to the model parameter, the frequency response mathematical model of the channel, and the frequency of each downlink subcarrier.
  • a third calculating unit configured to calculate, according to a frequency response of the downlink channel, a weight of beamforming of each downlink subcarrier frequency point.
  • a beamforming unit is configured to perform downlink beamforming on the antenna array according to the weight, and the antenna array is a dual-polarized antenna array or a single-polarized antenna array.
  • the model parameters include the path of each path, the angle of arrival of each path, the amplitude of each path, and the initial phase of each path.
  • the second calculating unit is specifically configured to: construct a frequency response of the uplink channel according to the frequency response of the uplink channel and each uplink subcarrier frequency point.
  • Target likelihood spectrum A target value of each path and a target value of an angle of arrival of each path are calculated based on the target likelihood spectrum.
  • the target value of the amplitude of each path and the target value of the initial phase of each path are calculated based on the target value of the path of each path and the target value of the angle of arrival of each path.
  • the second calculating unit is specifically configured to: calculate an initial value of a path of each path and an initial of an arrival angle of each path according to the target likelihood spectrum value.
  • the target value of the path of each path and the target value of the arrival angle of each path are calculated by an optimization algorithm according to the initial value of the path of each path and the initial value of the angle of arrival of each path.
  • the second calculating unit is specifically configured to: calculate an initial value of a path of each path and an initial of an arrival angle of each path according to the target likelihood spectrum value.
  • the target value of the path of each path and the target value of the arrival angle of each path are calculated by the search algorithm according to the target likelihood spectrum, the initial value of the path of each path, and the initial value of the arrival angle of each path.
  • the expression of the frequency response mathematical model of the channel is:
  • F(k,i) represents the mathematical model of the frequency response of the channel
  • N represents the number of paths
  • d n represents the path of the nth path
  • ⁇ n Indicates the angle of arrival of the nth path
  • a n represents the amplitude of the nth path
  • ⁇ n represents the initial phase of the nth path
  • I denotes the number of subcarrier frequency points
  • I denotes the number of subcarrier frequency points
  • k 1, 2, ...
  • K denotes the number of array elements
  • l denotes the array element spacing .
  • the expression of the target likelihood spectrum of the frequency response of the uplink channel is:
  • ⁇ (d, ⁇ ) represents the target likelihood spectrum
  • h UL (k, i) represents the frequency response of the uplink channel
  • d represents the path of the path
  • represents the angle of arrival of the path
  • i represents the ith uplink
  • I represents the number of the subcarrier frequency point
  • I represents the number of subcarrier frequency points
  • k 1, 2, ...
  • K represents the array element
  • the number, the number of K array elements, l represents the spacing of the elements,
  • 2 represents the Euclidean norm.
  • the expression of the frequency response mathematical model of the channel is:
  • ⁇ n represents the angle of arrival of the nth path
  • a n represents the amplitude of the nth path
  • ⁇ n represents the initial phase of the nth path
  • ⁇ i represents the wavelength corresponding to the frequency of the i th subcarrier
  • i 1 , 2 ...
  • I represents the number of subcarrier frequency points
  • I represents the number of subcarrier frequency points
  • k 1, 2, ...
  • K represents the number of array elements, the number of K array elements
  • l Indicates the array element spacing
  • k H represents the number of rows of the antenna array
  • k V represents the number of columns of the antenna array.
  • ⁇ n represents the pitch angle
  • the frequency response of the uplink channel includes a frequency response of the first polarization uplink channel and a second The frequency response of the polarized uplink channel
  • the model parameters include a first polarization model parameter and a second polarization model parameter
  • the model parameters conform to the following expression:
  • argmin represents the variable value when the objective function obtains the minimum value
  • i represents the number of the subcarrier frequency point
  • k represents the number of the array element
  • represents the wavelength corresponding to the subcarrier frequency point
  • ⁇ UL represents the uplink subcarrier frequency point.
  • a mathematical model of the frequency response representing the first polarized uplink channel, a mathematical model representing the frequency response of the second polarized uplink channel, and F representing a mathematical model of the frequency response of the channel Representing the frequency response of the first polarized uplink channel, Indicates the frequency response of the second polarized upstream channel
  • 2 represents the Euclidean norm.
  • the frequency response of the uplink channel includes a frequency response of the first polarization uplink channel and a second The frequency response of the uplink channel is polarized
  • the second calculating unit is specifically configured to: construct a first polarization likelihood spectrum of the frequency response of the uplink channel according to the frequency response of the first polarized uplink channel and each uplink subcarrier frequency.
  • a second polarization likelihood spectrum of the frequency response of the uplink channel is constructed according to the frequency response of the second polarized uplink channel and each uplink subcarrier frequency.
  • the sum of the first polarization likelihood spectrum and the second polarization likelihood spectrum is the target likelihood spectrum.
  • the amplitude of each path when the antenna array is a dual-polarized antenna array, the amplitude of each path includes an amplitude and a second of each path corresponding to the first polarization.
  • the amplitude of each path corresponding to the polarization, the initial phase of each path includes the initial phase of each path corresponding to the first polarization and the initial phase of each path corresponding to the second polarization, and the frequency response of the downlink channel includes the first polarization downlink The frequency response of the channel and the frequency response of the second polarized downlink channel.
  • the construction unit is specifically configured to: according to the path of each path in the model parameter, the arrival angle of each path, the amplitude of each path corresponding to the first polarization, the initial phase of each path corresponding to the first polarization, and the frequency response of the channel
  • the model and each downlink subcarrier frequency point construct a frequency response of the first polarization downlink channel.
  • the arrival angle of each path, the amplitude of each path corresponding to the second polarization, the initial phase of each path corresponding to the second polarization, the frequency response mathematical model of the channel, and each downlink subcarrier Frequency point construct the frequency response of the second polarization downlink channel.
  • the weight includes the first polarization
  • the third computing unit is configured to: calculate a weight of the beamforming of each downlink subcarrier frequency corresponding to the first polarization according to the frequency response of the first polarization downlink channel. And calculating a weight of beamforming of each downlink subcarrier frequency point corresponding to the second polarization according to a frequency response of the second polarization downlink channel.
  • model parameters conform to the following expression:
  • argmin represents the variable value when the objective function obtains the minimum value
  • i represents the number of the subcarrier frequency point
  • k represents the number of the array element
  • represents the wavelength corresponding to the subcarrier frequency point
  • ⁇ UL represents the uplink subcarrier frequency point.
  • F UL represents the mathematical model of the frequency response of the upstream channel
  • F represents the mathematical model of the frequency response of the channel
  • h UL represents the frequency response of the upstream channel
  • 2 represents the Euclidean norm.
  • an embodiment of the present application provides an access network device, including: a processor, a memory, a bus, and a communication interface; a processor and a memory are connected through a bus, and the memory is used to store a computer to execute an instruction, when the access network device In operation, the processor executes a memory stored computer to execute instructions to cause the access network device to perform the beamforming method in any of the possible implementations of the first aspect.
  • an embodiment of the present application provides a computer readable storage medium, configured to store computer software instructions used by the access network device, when executed on a computer, to enable the computer to perform any of the first aspect.
  • a beamforming method in a possible implementation.
  • an embodiment of the present application provides a computer program product comprising instructions, which when executed on a computer, enable the computer to perform a beamforming method in any of the possible implementations of the first aspect.
  • FIG. 1 is a schematic structural diagram of a communication system according to an embodiment of the present application.
  • FIG. 2 is a schematic structural diagram of an access network device according to an embodiment of the present disclosure
  • FIG. 3 is a flowchart of a beamforming method according to an embodiment of the present application.
  • FIG. 5 is a flowchart of another beamforming method according to an embodiment of the present disclosure.
  • FIG. 6 is a schematic structural diagram of another access network device according to an embodiment of the present disclosure.
  • FIG. 7 is a schematic structural diagram of another access network device according to an embodiment of the present disclosure.
  • FIG. 8 is a schematic structural diagram of another access network device according to an embodiment of the present disclosure.
  • Beamforming A technique for forming a desired ideal signal by weighting and combining the signals received by the multiple antenna elements.
  • Frequency point The frequency of each subcarrier.
  • Path The electromagnetic wave in the communication channel is connected to the route between the base station and the user after being deflected and diffracted.
  • Path of the route the length of the above route.
  • Angle of arrival of the path the angle between the above-mentioned route and the direction of the antenna array of the base station when it arrives at the base station.
  • Likelihood spectrum It is a kind of spatial spectrum of conventional spectral estimation. This spatial spectrum can also be called Bartlett spectrum, etc. It is a two-dimensional function about the distance and the angle of arrival, or it can be about the distance or arrival. A one-dimensional function of the angle.
  • Polarization direction refers to the direction of the electric field strength formed when the antenna is radiated.
  • Single-polarized antenna An antenna that includes only one polarization direction.
  • Dual-polarized antenna Combines two antennas with orthogonal directions of +45° and -45°, and works in transceiver duplex mode.
  • Array element the antenna element, the components on the antenna array, have the function of guiding and amplifying electromagnetic waves, and are used to make the electromagnetic signal received by the antenna array stronger.
  • Search algorithm refers to a method that uses the high performance of a computer to objectively exhaust a part or all of the possible situations of the solution space to solve the solution of the problem.
  • Steering vector A vector with a guiding direction and a pointing direction.
  • the mobile communication system herein may be a 3rd generation mobile communication (3G) communication system, a 4th generation mobile communication (4G) communication system, and a future evolution network, such as The fifth generation mobile communication technology (5th-generation, 5G) communication system.
  • the mobile communication system herein may be a long term evolution (LTE) system, a 3G related cellular system, etc., and other such communication systems.
  • LTE long term evolution
  • UDN ultra dense network
  • the 5G standard may include machine to machine (M2M), D2M, macro communication, enhanced mobile broadband (eMBB), ultra high reliability and ultra low latency communication ( Ultra reliable & low latency communication (uRLLC) and massive machine type communication (mMTC) scenarios, which may include, but are not limited to, communication scenarios between access network devices and access network devices, access network devices Communication scenarios with the terminal, etc.
  • M2M machine to machine
  • eMBB enhanced mobile broadband
  • uRLLC ultra high reliability and ultra low latency communication
  • mMTC massive machine type communication
  • the technical solution provided by the embodiment of the present application may be applied to the system architecture shown in FIG. 1 , where the system architecture may include an access network device 100 and one or more terminals 200 connected to the access network device 100.
  • An antenna array is disposed in the access network device 100, and the access network device 100 transmits and receives signals through the antenna array to communicate with the terminal 200.
  • the access network device 100 may configure the weight of the beamforming before transmitting the signal through the antenna array, thereby performing downlink beamforming according to the weight, and performing signal transmission through the antenna array.
  • the access network device here may be a relay station or an access point.
  • the access network device may be a base transceiver station (BTS) in a global system for mobile communication (GSM) or a code division multiple access (CDMA) network, or may be
  • the NB (NodeB) in the wideband code division multiple access (WCDMA) may also be an eNB or an eNodeB (evolutional NodeB) in LTE.
  • the access network device 100 can also be a wireless controller in a cloud radio access network (CRAN) scenario.
  • the access network device 100 may also be a network device in a future 5G network or a network device in a public land mobile network (PLMN) that is evolved in the future.
  • Network devices in future 5G networks may include new radio base stations (new radio) NodeB), next generation NodeB (gNB), or transmission point.
  • the access network device can be implemented by the structure shown in FIG. 2.
  • the access network device may include an uplink detection subsystem, a medium RF subsystem, a baseband subsystem, and an antenna feed subsystem.
  • the uplink detection subsystem may be configured to receive a signal sent by the terminal, such as a sounding reference signal (SRS), calculate a frequency response of the uplink channel, and the like.
  • the baseband subsystem can be used for the implementation of basic physical layer algorithms.
  • the medium RF subsystem can be used for up-conversion on the basis of the baseband signal (that is, the signal is shifted from the fundamental frequency to the carrier frequency), and solves the problems of distortion and error generated in the up-conversion process.
  • the antenna feeder subsystem includes an antenna array, which can be used to acquire an array structure of the antenna array, and then calculate a beam pattern of the weighted antenna array, that is, for performing downlink beamforming.
  • the access network device may also adopt other general hardware architectures, and is not limited to only one hardware architecture shown in FIG. 2.
  • the configuration of the beamforming weight of the antenna array may be specifically performed in the middle RF subsystem or in the baseband subsystem.
  • the beamforming scheme in the prior art needs to construct the weight of beamforming according to the PMI fed back by the terminal, so that the real-time performance of beamforming is poor and the error is large.
  • the terminal can obtain the maximum SNR. / Receive power gain. This requires the base station to know the frequency response of the downlink channel in advance before transmitting.
  • the frequency response of the channel on the upper and lower channels of time division duplexing has reciprocity in the antenna number domain
  • frequency division duplexing Under the FDD frequency division duplexing
  • the frequency response of the uplink and downlink channels in the antenna number domain is not as good as TDD due to the difference in frequency bands.
  • the embodiment of the present application provides a beamforming method.
  • the access network device can construct a frequency response of the downlink channel according to the frequency response of the uplink channel and the frequency response mathematical model of the channel, and according to the frequency response of the downlink channel.
  • the weight of the beamforming is calculated to perform downlink beamforming, so that the calculation of the weight of the beamforming does not require the terminal to perform feedback as in the prior art, thereby improving the real-time performance of the beamforming and reducing the real-time performance.
  • the error caused by the difference is a condition in which the weight of the beamforming is calculated.
  • an embodiment of the present application provides a beamforming method, including:
  • the access network device calculates a frequency response of the uplink channel.
  • the frequency response of the uplink channel is used to describe the response of the uplink channel to each array element of the antenna array and the frequency of each uplink subcarrier.
  • the access network device may calculate the frequency response of the uplink channel according to an uplink signal such as an SRS received from the terminal.
  • the access network device calculates a model parameter in a mathematical model of the frequency response of the channel according to the frequency response of the uplink channel and the frequency of each uplink subcarrier, and the model parameter has reciprocity in the uplink and downlink subcarrier frequencies.
  • the frequency response mathematical model of the channel may be preset in the access network device, and the frequency response mathematical model of the channel is used to describe the frequency response of the channel, that is, the response of the channel at each subcarrier frequency.
  • the frequency response mathematical model of the channel includes at least one model parameter, which is a channel multipath parameter, and the model parameter has reciprocity at the upper and lower subcarrier frequencies.
  • the frequency interval between the uplink subcarrier frequency points and the downlink subcarrier frequency points is relatively large, and the frequency spacing between the uplink subcarrier frequency points is small, and the frequency interval between the downlink subcarrier frequency points is small.
  • the model parameters have reciprocity at the uplink and downlink subcarrier frequencies, it can be understood that the model parameters also have reciprocity at each uplink subcarrier frequency, and the model parameters are in each downlink subcarrier frequency. Points are also reciprocal. That is to say, the model parameter has reciprocity at each uplink subcarrier frequency point and each downlink subcarrier frequency point. It can be understood that the model parameter can be applied to each of the uplink and downlink subcarrier frequency points, and frequency shifting can be performed between each of the upper and lower subcarrier frequency points.
  • the frequency response mathematical model of the channel can be used for Indicates the frequency response of the uplink channel; when the downlink subcarrier frequency is substituted into the frequency response mathematical model of the channel, the frequency response mathematical model of the channel can be used to indicate the downlink The frequency response of the channel.
  • the frequency response of the downlink channel can be obtained. That is to say, when the model parameters of the frequency response mathematical model of the channel have reciprocity at the upper and lower subcarrier frequencies, the process of reconstructing the downlink channel can be made simpler.
  • the access network device constructs a frequency response of the downlink channel according to the model parameter, the frequency response mathematical model of the channel, and the downlink subcarrier frequency points.
  • the access network device may substitute the downlink subcarrier frequency point and the obtained model parameters into the frequency response mathematical model of the channel, thereby obtaining the frequency response of the downlink channel.
  • the access network device calculates a weight of beamforming of each downlink subcarrier frequency according to a frequency response of the downlink channel.
  • the frequency response of the downlink channel is obtained in step 303.
  • the access network device may calculate the weight of the beamforming of each downlink subcarrier frequency according to the frequency response of the downlink channel.
  • the expression of the weight forming w i of the beamforming corresponding to the ith downlink subcarrier frequency point may be expressed as follows:
  • Equation 1 h DL (k, i) represents the frequency response of the i-th downlink subcarrier frequency point corresponding to the kth array element on the downlink channel, [] H represents a conjugate matrix, and
  • the access network device may obtain the weight of the beamforming corresponding to each downlink element frequency on each array element according to Equation 1 above.
  • the access network device performs downlink beamforming on the antenna array according to the weight, and the antenna array is a dual-polarized antenna array or a single-polarized antenna array.
  • Each of the array elements in the dual-polarized antenna array corresponds to two polarization directions, that is, a first polarization direction and a second polarization direction; each of the array elements in the single-polarized antenna array corresponds to one polarization direction.
  • the access network device may weight the weight of the beamforming corresponding to each downlink subcarrier frequency point to perform downlink beamforming on each array element of the antenna array. That is, the weights on the array elements of the antenna array are multiplied by the signals on the respective array elements, equivalent to the weight vector on the antenna array and the signal vector to make a dot product, and then the signal is transmitted.
  • the access network device can directly construct the frequency response of the downlink channel according to the frequency response of the uplink channel and the frequency response mathematical model of the channel, and calculate beamforming according to the frequency response of the downlink channel.
  • the weight value is thus used for beamforming, so that the calculation of the weight of the beamforming does not require the terminal to perform feedback as in the prior art, thereby improving the real-time performance of the beamforming and reducing the real-time performance. error.
  • the model parameters in the frequency response model of the channel have reciprocity at the uplink and downlink subcarrier frequencies
  • the model parameters and the frequency response mathematical model of each downlink subcarrier frequency point are substituted into the channel, and the frequency response of the downlink channel can be obtained. Therefore, the method for constructing the frequency response of the downlink channel is simple, real-time and easy to implement, thereby reducing beamforming.
  • the computational complexity of the weights increases the processing efficiency of the access network devices.
  • the access network device approaches the optimal weight by constructing a codebook set and selecting a codebook that maximizes the received power gain, which is equivalent to The space in which the h DL is located is quantized, and the candidate closest to the true value is selected from the finite discrete values, which inevitably causes quantization error. If the codebook set is sparse, the quantization error will increase, which will affect the beamforming performance. If the codebook set is dense, especially in the case of Massive MIMO, the computational complexity will be very large, which will affect the efficiency. Therefore, the impact of PMI quantization error on performance is not negligible.
  • the access network device needs to configure a corresponding codebook set for different array elements and terminals, and only a large number of codebook sets are configured. Only the quantization error can be guaranteed to be as small as possible.
  • the access network device side needs 16 codebooks under 4 ports, and 256 codebooks under 8 ports. It is conceivable that 16 ports, 32 ports, and even 64 and 128 ports required for Massive MIMO systems. The number of codebooks required is even larger, which inevitably increases the computational burden and data processing efficiency of the communication system.
  • the access network device directly constructs the frequency response of the downlink channel, and constructs the weight of the beamforming according to the frequency response of the downlink channel, and can also avoid the quantization error caused by the codebook set and Huge data processing, calculation, and cache burden.
  • the access network device performs DOA estimation based on the uplink SRS signal, calculates the DOA of the main path of the channel, and substitutes the DOA into the steering vector as the weight of the beamforming; and weights the weight as the weight of the beamforming On the antenna array.
  • This scheme relies too much on the accuracy of DOA estimation.
  • the weight of beamforming will also be biased.
  • this scheme only estimates the DOA of the main path of the channel into the steering vector as the weight of the beamforming, that is, the relatively weaker paths of other energy are ignored.
  • This method is suitable for channels with only one path of line of sight (LOS) or main path and other channels with very weak path, but for non-line of sight (NLOS) channels, especially exist When multiple energy paths are close to each other, this method can only obtain one DOA, so the weight error calculated based on the DOA is also large.
  • LOS line of sight
  • NLOS non-line of sight
  • the technical solution provided by the embodiment of the present application does not rely on the DOA estimation of a single main path, but directly constructs the frequency response of the downlink channel according to the frequency response of the downlink channel.
  • the DOA estimation accuracy of a single principal path does not have a decisive influence on the performance, and it also has good applicability to the NLOS channel.
  • the specific form of the frequency response mathematical model of the channel having the characteristics that the model parameters have reciprocity in the upper and lower subcarrier frequencies may be various, and the model parameters in the frequency response mathematical model of the channel Specifically, there may be many different combinations.
  • the model parameters may include a path of each path, an angle of arrival of each path, an amplitude of each path, and an initial phase of each path. The distance between each path, the angle of arrival of each path, the amplitude of each path, and the initial phase of each path have reciprocity at the upper and lower subcarrier frequencies. It is worth noting that the path of each path here is not a parameter. When there are N paths, the path of each path here represents the path of N paths, which are N parameters; other model parameters (the angle of arrival of each path) The amplitude of each path is similar to the initial phase of each path.
  • the frequency response mathematical model of the channel provided by the embodiment of the present application is a simplified model, does not include an antenna pattern, and does not require a complicated domain transformation and the like, so that the antenna array is constructed by the frequency response mathematical model of the channel.
  • the process of the frequency response of the downlink channel (especially the dual-polarized antenna array) is relatively simple.
  • the expression of the frequency response mathematical model of a channel may be as follows:
  • F(k,i) represents the mathematical model of the frequency response of the channel
  • N represents the number of paths
  • d n represents the path of the nth path
  • ⁇ n Indicates the angle of arrival of the nth path
  • a n represents the amplitude of the nth path
  • ⁇ n represents the initial phase of the nth path
  • I denotes the number of subcarrier frequency points
  • I denotes the number of subcarrier frequency points
  • k 1, 2, ...
  • K denotes the number of array elements
  • l denotes the array element spacing .
  • Equation 3 the expression of the frequency response mathematical model of another channel can be seen in Equation 3 below:
  • the above formula 3 represents a mathematical model of the frequency response of the channel corresponding to the antenna array when the antenna array is an area array, wherein F(k H , k V , i) represents a mathematical model of the frequency response of the channel, k H represents The number of rows of the antenna array, k V represents the number of columns of the antenna array, Indicates the horizontal angle of the nth path, and ⁇ n represents the pitch angle of the nth path.
  • the access network device may perform the method for solving the model parameters in the frequency response mathematical model of the channel according to the frequency response of the uplink channel and the frequency of each uplink subcarrier in step 302.
  • the access network device may construct a target likelihood spectrum for the frequency response of the uplink channel, and solve each model parameter according to the target likelihood spectrum.
  • the access network device can directly solve each model parameter through an optimization algorithm.
  • a specific implementation of step 302 may include :
  • the access network device constructs a target likelihood spectrum of the frequency response of the uplink channel according to the frequency response of the uplink channel and each uplink subcarrier frequency.
  • the target likelihood spectrum is a function of at least one of the path of the path and the angle of arrival of the path.
  • the access network device calculates a target value of each path and a target value of an arrival angle of each path according to the target likelihood spectrum.
  • the access network device calculates a target value of the amplitude of each path and a target value of the initial phase of each path according to the target value of the path of each path and the target value of the angle of arrival of each path.
  • the target value of each model parameter refers to an optimal value of each model parameter. Since the target likelihood spectrum is a function of at least one of the path of the path and the angle of arrival of the path, the target value of each path and the target value of the angle of arrival of each path can be first obtained according to the target likelihood spectrum, and then according to The target value of the path of each path and the target value of the angle of arrival of each path are used to calculate the target value of the amplitude of each path and the target value of the initial phase of each path.
  • the first possible implementation manner described above may specifically include the following manners A and B.
  • the foregoing step 3022 may specifically include:
  • the access network device calculates an initial value of a path of each path and an initial value of an arrival angle of each path according to the target likelihood spectrum.
  • the access network device calculates, according to an initial value of a path of each path and an initial value of an arrival angle of each path, an optimization algorithm to calculate a target value of a path of each path and a target value of an arrival angle of each path.
  • the foregoing step 3022 may specifically include:
  • the access network device calculates an initial value of the path of each path and an initial value of the arrival angle of each path according to the target likelihood spectrum.
  • the access network device calculates, according to the target likelihood spectrum, the initial value of the path of each path, and the initial value of the arrival angle of each path, the target value of the path of each path and the target value of the arrival angle of each path are calculated by a search algorithm.
  • the initial values of the paths of the paths obtained in the above steps 401 and 501 and the initial values of the arrival angles of the paths are only initial estimates, and are not necessarily the paths of the paths and the arrival angles of the paths.
  • the figure of merit therefore, it is necessary to further calculate the path of each path and the optimal value of the angle of arrival of each path according to the path of each path and the initial value of the angle of arrival of each path, that is, the distance of each path and the target of the arrival angle of each path are estimated. value.
  • the access network device can construct a target likelihood spectrum, and then determine the peak value on the target likelihood spectrum by the search algorithm, thereby solving the model parameters, and the method is relatively simple.
  • the access network device can construct an objective function, and determine the peak value on the objective function by an optimization algorithm (for example, maximum likelihood method) to solve the model parameters, and the method is more accurate.
  • the antenna array may be a dual-polarized antenna array or a single-polarized antenna array.
  • the frequency response mathematical model of the channel shown in Equation 2 is taken as an example. According to the above methods for solving model parameters, the beamforming methods in the single-polarized antenna array scene and the dual-polarized antenna array scene are specifically described. .
  • Scenario 1 Single-polarized antenna array scenario
  • the access network device may calculate, in step 301, a frequency response h UL (k, i) of the uplink channel, where the h UL (k, i) may be according to each uplink subcarrier frequency point and Equation 2
  • the frequency response mathematical model of the channel expressed as the frequency response mathematical model F UL (k, i) of the upstream channel as shown in Equation 4:
  • Equation 4 Equation 4
  • the access network device may construct a target likelihood spectrum of the frequency response of the uplink channel in step 3021, and the target likelihood spectrum may specifically be The form shown in 5:
  • ⁇ (d, ⁇ ) represents the target likelihood spectrum
  • h UL (k, i) represents the frequency response of the uplink channel
  • d represents the path of the path
  • represents the angle of arrival of the path
  • i represents the ith uplink
  • the wavelength corresponding to the subcarrier frequency point, i 1, 2, ...
  • I represents the number of the subcarrier frequency point
  • I represents the number of subcarrier frequency points
  • k 1, 2, ...
  • K represents the array element
  • the number, the number of K array elements, l indicates the spacing of the elements, and the superscript "2" indicates the square.
  • Equation 5 the path d n different from each path is used to represent the path of the path; the angle of arrival ⁇ n is different from the path, and ⁇ is used to indicate the angle of arrival of the path.
  • the access network device can calculate the initial value of the path of each path and the initial value of the arrival angle of each path based on the target likelihood spectrum in step 401 or step 501.
  • the parameter space corresponding to the target likelihood spectrum shown in Equation 5 may be divided into multiple grid points, and the access network device may traverse the search peaks on the grid points by using a search algorithm to estimate the path d n of each path.
  • a threshold range for example, 10 dB smaller than the highest peak
  • the number of peaks in the threshold range is the number N of the paths.
  • the target likelihood spectrum in the embodiment of the present application is a steering vector that responds to the frequency of the uplink channel (in Equation 4). After doing the conjugate compensation, the spatial spectrum formed by coherent addition is added.
  • the peak corresponding to the grid point is not necessarily the peak of the entire target likelihood spectrum, and thus the obtained model
  • the value of the parameter is only the initial value and is not necessarily the optimal value of the model parameter.
  • the access network device may substitute the obtained initial value of d n and the initial value of ⁇ n into subsequent optimization.
  • the amplitude a n of each path and the initial phase ⁇ n of each path are represented by d n and ⁇ n by the method of elimination, so that the optimal value of d n is first calculated.
  • the optimal value of ⁇ n that is, the target value of d n and the target value of ⁇ n
  • the optimal value of a n and the optimal value of ⁇ n according to the target value of d n and the target value of ⁇ n .
  • the target value of a n and the target value of ⁇ n that is, the target value of a n and the target value of ⁇ n .
  • the frequency response mathematical model F' UL (k, i) of the uplink channel can be constructed by the frequency response model of the channel:
  • F' UL (k, i) represents an estimate of a set of model parameters
  • F UL (k, i) represents an estimate of a set of model parameters
  • argmin represents the variable value when the objective function obtains the minimum value
  • i represents the number of the subcarrier frequency point
  • k represents the number of the array element
  • represents the wavelength corresponding to the subcarrier frequency point
  • ⁇ UL represents the uplink subcarrier frequency point.
  • F UL represents the mathematical model of the frequency response of the upstream channel
  • F represents the mathematical model of the frequency response of the channel
  • h UL represents the frequency response of the upstream channel.
  • ⁇ ) F(k,i
  • ⁇ UL ) can indicate that the mathematical model of the frequency response of the uplink channel is a mathematical model of the frequency response of substituting the wavelength ⁇ UL corresponding to each uplink subcarrier frequency into the channel.
  • Equation 7 The optimization problem shown in Equation 7 above can be solved by the following steps:
  • Equation 4 can be expressed as a matrix
  • Equation 13 the mathematical model of the frequency response of the total uplink channel of the full bandwidth can be expressed as
  • Equation 7 Based on the matrix form represented by Equation 16, the optimization problem shown in Equation 7 can be expressed as
  • optimization problem 17 can be transformed into a only and Related, that is, only Related optimization issues, ie
  • the 4N-dimensional optimization problem in Equation 17 can be transformed into the 2N-dimensional optimization problem in Equation 19 by means of elimination, which can reduce the computational complexity and make the calculation process simpler.
  • the simplex method (for example, the Nelder-Mead method) can be used to determine the peak value to obtain the optimal value. Worried here That is, the target value of the model parameter d n and the target value of ⁇ n are respectively.
  • the access network device can be based on an optimal Calculate the optimal by Equation 18 above which is
  • the target value of the model parameter a n and the target value of ⁇ n are respectively.
  • the initial value of d n and ⁇ n are The initial value is a solution obtained by traversing the peak of the search target likelihood spectrum on the grid point of the parameter space division, and is not necessarily the optimal solution, that is, the peak corresponding to the grid point, and is not necessarily the entire target likelihood spectrum.
  • the peak value, and thus the access network device can also obtain the target value of d n and the target value of ⁇ n by traversing the peak near the initial value on the search target likelihood spectrum, that is, the peak value near the grid point in step 502. Further, the target value of a n and the target value of ⁇ n can be obtained by Equation 18.
  • the access network device may not solve the initial value of d n and the initial value of ⁇ n through the target likelihood spectrum, but directly according to the optimization target shown in Equation 17.
  • the function solves the target value of d n , the target value of ⁇ n , the target value of a n , and the target value of ⁇ n by an optimization algorithm (for example, a maximum likelihood method). Since this method searches for peaks in the entire parameter space, the resulting model parameters are more accurate.
  • the access network device may construct a downlink channel according to the model parameters, the frequency response mathematical model of the channel, and the downlink subcarrier frequency points in step 303.
  • the mathematical model of the frequency response F DL (k, i) is the frequency of access network device constructed downlink channel response h DL (k, i):
  • h DL (k, i) is the frequency response of the downlink channel reconstructed according to the model parameters and the frequency response mathematical model of the channel, and is not the frequency response of the real downlink channel.
  • the access network device may obtain the weight of the optimal beamforming corresponding to each downlink subcarrier frequency point shown in the foregoing formula 1 based on the frequency response of the constructed downlink channel.
  • the access network device may perform downlink beamforming on the antenna array according to the weight in step 305, and then perform signal transmission.
  • the beamforming method provided by the embodiment of the present application can calculate the weight of the beamforming to perform beamforming by constructing a frequency response of the downlink channel in a single polarization scenario.
  • FIG. 5 A flowchart of the beamforming method corresponding to the scenario can be seen in FIG. 5.
  • the access network device can reconstruct the frequency response of the downlink channel according to the channel characteristics corresponding to the two polarization directions. Thereby beamforming is performed.
  • the specific process is as follows:
  • the access network device may calculate, in step 301, the frequency response of the uplink channel, where the frequency response of the uplink channel may include the frequency response of the first polarized uplink channel.
  • Frequency response of the second polarized uplink channel the The mathematical model of the frequency response of each uplink subcarrier frequency point and channel can be expressed as a mathematical model of the frequency response of the first polarized uplink channel as shown in Equation 22.
  • the mathematical model of the frequency response of each of the uplink subcarrier frequency points and the channel can be expressed as a mathematical model of the frequency response of the second polarized uplink channel as shown in Equation 23.
  • l represents the spacing of the elements
  • N represents the number of paths
  • d n represents the path of the nth path
  • ⁇ n represents the path of the nth Arrival angle
  • Representing the amplitude of the nth path corresponding to the second polarization Indicates the initial phase of the nth path corresponding to the first polarization
  • the initial phase of the nth path corresponding to the second polarization, ⁇ UL, i represents the wavelength corresponding to the frequency of the i th uplink subcarrier.
  • the access network device in step 3021 according to the frequency response of the uplink channel and each uplink subcarrier frequency, the target likelihood spectrum of the frequency response of the uplink channel may be:
  • the access network device constructs a first polarization likelihood spectrum of the frequency response of the uplink channel according to the frequency response of the first polarization uplink channel and each uplink subcarrier frequency point; and the frequency of the second polarization uplink channel of the access network device according to the access network device
  • the second polarization likelihood spectrum of the frequency response of the uplink channel is constructed in response to each uplink subcarrier frequency, and the sum of the first polarization likelihood spectrum and the second polarization likelihood spectrum is the target likelihood spectrum.
  • Equation 4 the expression of the first polarization likelihood spectrum ⁇ + (d, ⁇ ) can be seen in the following Equation 24, and the expression of the second polarization likelihood spectrum ⁇ - (d, ⁇ ) can be seen in the following Equation 25,
  • Equation 26 The expression of the target likelihood spectrum ⁇ DP (d, ⁇ ) after the addition of the polarization likelihood spectrum and the second polarization likelihood spectrum can be seen in Equation 26 below:
  • the access network device may calculate the initial value and path of each path according to the target likelihood spectrum in step 401 or step 501.
  • the initial value of the angle of arrival may be calculated.
  • the parameter space corresponding to the target likelihood spectrum shown in Equation 26 may be divided into multiple grid points, and the access network device may traverse the search peaks on the grid points by using a search algorithm to estimate the path d n of each path.
  • the likelihood spectrum shown in Equations 24 and 25 is a spatial spectrum formed by the steering vector conjugate compensation and the coherent accumulation, the true value can be highlighted as a peak on the target likelihood spectrum.
  • the model parameters d n and ⁇ n are the same in the case of dual polarization, the bipolar polarization spectrum (the first polarization likelihood spectrum and the second polarization likelihood spectrum) can be added. Thereby merging into a total target likelihood spectrum, and jointly estimating the initial value of d n and the initial value of ⁇ n according to the total target likelihood spectrum.
  • the peak formed above interferes with noise and the like to form a pseudo peak formed on the target likelihood spectrum, thereby reducing the number of iterations and facilitating the simpler, more efficient and accurate determination of the initial values of d n and ⁇ n in the case of dual polarization. .
  • the access network device may substitute the obtained initial value of d n and the initial value of ⁇ n into subsequent optimization.
  • the amplitude a n of each path and the initial phase ⁇ n of each path are represented by d n and ⁇ n by the method of elimination, so that the optimal value of d n is first calculated.
  • the amplitude a n of each path includes the amplitude of each path corresponding to the first polarization.
  • Amplitude of each path corresponding to the second polarization The initial phase ⁇ n of each path includes the initial phase of each path corresponding to the first polarization.
  • the initial phase of each path corresponding to the second polarization the target value of the amplitude of each path also includes a target value of the amplitude of each path corresponding to the first polarization and a target value of the amplitude of each path corresponding to the second polarization, and the target value of the initial phase of each path is also The target value of the initial phase of each path corresponding to the first polarization and the target value of the initial phase of each path corresponding to the second polarization are included.
  • the frequency response mathematical model of a pair of dual-polarized uplink channels can be constructed by the frequency response model of the channel, that is, the mathematical model of the frequency response of the first polarization uplink channel Mathematical model of frequency response of the second polarized uplink channel
  • Equation 29 Optimal estimate of model parameters Is making The closest to the real value calculated in step 301 And make The closest to the real value calculated in step 301 Therefore, the problem of estimating the model parameters can be transformed into an optimization problem as shown in Equation 29:
  • Equation 30 argmin represents the value of the variable when the objective function takes the minimum value, i represents the number of the subcarrier frequency, k represents the number of the element, ⁇ represents the wavelength corresponding to the subcarrier frequency, and ⁇ UL represents the uplink.
  • the first polarization model parameter may include an amplitude of each path corresponding to the first polarization and an initial phase of each path corresponding to the first polarization
  • the second polarization model parameter may include each path corresponding to the second polarization.
  • the mathematical model of the frequency response of the first-polarized uplink channel is an expression obtained by substituting the wavelength ⁇ UL and the first polarization model parameter corresponding to each uplink sub-carrier frequency into the frequency response mathematical model of the channel.
  • the mathematical model of the frequency response of the second polarized uplink channel is an expression obtained by substituting the wavelength ⁇ UL and the second polarization model parameter corresponding to each uplink subcarrier frequency into the frequency response mathematical model of the channel.
  • the access network device combines the dual-polarized optimization objective function shown in Equation 27 and Equation 28 into the optimized objective function shown in Equation 29 to jointly optimize the solution, due to the dual polarization case.
  • the peak is the first polarization optimization objective function
  • the second polarization optimization objective function is not a peak, for example, may be a valley
  • the first polarization optimization target when the function is a peak, it is also a peak in the second polarization optimization objective function. Therefore, by adding the dual polarization optimization objective functions, the peak formed by the real multipath on the optimization objective function can be further highlighted, and the noise is relatively suppressed.
  • the interference is formed on the target optimization function to form a pseudo-peak, so that the number of iterations can be reduced, and the model parameters in the case of dual polarization can be determined more efficiently and accurately.
  • Equation 22 and Equation 23 can be represented by a matrix as
  • Equation 29 Based on the matrix form represented by Equation 42 and Equation 43, the optimization problem shown in Equation 29 can be expressed as
  • optimization problem 44 can be converted into a only and Related, that is, only Related optimization issues, ie
  • Equation 44 can be transformed into the 2N-dimensional optimization problem in Equation 47 by means of elimination, which can reduce the computational complexity and make the calculation process simpler.
  • the simplex method (for example, the Nelder-Mead method of the downhill simplex method) can be used to search for the optimal one. Worried here That is, the target value of the model parameter d n and the target value of ⁇ n are respectively.
  • the access network device can be based on an optimal Calculate the optimal by Equation 45 and Equation 46 above. which is
  • the foregoing is mainly described by using the mode A in the first possible implementation manner of the model parameter, and the mode B in the first possible implementation manner is similar to the single-polarization scenario, because d
  • the initial value of n and the initial value of ⁇ n are solutions obtained by traversing the peak of the search target likelihood spectrum on the grid points of the parameter space division, and are not necessarily the optimal solution, that is, the peak corresponding to the grid point, and not It must be the peak of the entire target likelihood spectrum. Therefore, the access network device can also obtain the target of d n by traversing the peak near the initial value on the search target likelihood spectrum, that is, the corresponding peak near the grid point, in step 502.
  • the value and the target value of ⁇ n can be obtained by Equations 45 and 46. Target value, Target value, Target value, The target value.
  • the access network device may directly solve the initial value of d n and the initial value of ⁇ n through the target likelihood spectrum, and directly According to the equation 44, the target value of d n , the target value of ⁇ n , and the target value of ⁇ n are solved by an optimization algorithm. Target value, Target value, Target value and The target value. Moreover, since this method traverses the search in the entire parameter space, the obtained model parameters are more accurate.
  • the access network device constructs the frequency response of the downlink channel according to the model parameter, the frequency response mathematical model of the channel, and the downlink subcarrier frequency points in step 303, which may include:
  • the access network device according to the path of each path in the model parameter, the arrival angle of each path, the amplitude of each path corresponding to the first polarization, the initial phase of each path corresponding to the first polarization, and the frequency response of the channel
  • the model and each downlink subcarrier frequency point construct a frequency response of the first polarization downlink channel.
  • the access network device calculates, according to the path of each path in the model parameter, the arrival angle of each path, the amplitude of each path corresponding to the second polarization, the initial phase of each path corresponding to the second polarization, and the frequency response of the channel.
  • the model and each downlink subcarrier frequency point construct a frequency response of the second polarized downlink channel.
  • the access network device can construct a mathematical model of the frequency response of the first polarization downlink channel as shown below.
  • Mathematical model of frequency response of the second polarized downlink channel The That is, the frequency response of the first polarized downlink channel constructed by the access network device The That is, the frequency response of the downlink channel constructed by the access network device
  • the weight of the beamforming includes the first polarization weight and the second polarization weight, and the access network device calculates the frequency of each downlink subcarrier according to the frequency response of the downlink channel in step 304 above.
  • the weight of beamforming includes:
  • the access network device calculates the weight of the beamforming of each downlink subcarrier frequency corresponding to the first polarization according to the frequency response of the first polarization downlink channel.
  • the access network device calculates, according to the frequency response of the second polarized downlink channel, the weight of the beamforming of each downlink subcarrier frequency corresponding to the second polarization.
  • the access network device may obtain the corresponding frequency of each downlink subcarrier frequency point represented by the formula 52 based on the frequency response of the first polarization downlink channel and the frequency response of the second polarization downlink channel respectively.
  • the weight of one polarization optimal beamforming, and the weight of the second polarization optimal beamforming corresponding to each downlink subcarrier frequency point represented by Equation 53.
  • the access network device may perform downlink beamforming on the antenna array according to the weight in step 305, and then perform signal transmission.
  • the beamforming method provided by the embodiment of the present application can construct the frequency response of the dual-polarized downlink channel by using the dual-polarization characteristic in the dual-polarization scenario, thereby calculating the beamforming right according to the frequency response of the dual-polarized downlink channel. Value for beamforming.
  • the model parameters of the frequency response mathematical model of the channel provided by the embodiment of the present application have reciprocity at the upper and lower subcarrier frequencies, thereby making it heavier than using other mathematical models.
  • the process of constructing the downlink channel is simpler.
  • the frequency response of the obtained channel in the above two scenarios is the value of the model parameter in the mathematical model, and Not the actual value of the channel multipath parameter, but an estimate of the channel multipath parameter.
  • the model parameters and the frequency response of the reconstructed downlink channel in addition to being used for beamforming, can also be applied in many applications, such as:
  • Geometric inversion calculations are performed on the target based on estimated channel multipath parameters such as time delay (ie, path travel) and angle of arrival to obtain a specific location of the target in space.
  • the channel frequency response of the adjacent bandwidth can be reconstructed by using the channel frequency response of a certain bandwidth, so that the uplink bandwidth that can be used for transmitting the SRS is multiplied and reaches the uplink coverage.
  • each network element such as an access network device and a terminal, in order to implement the above functions, includes hardware structures and/or software modules corresponding to each function.
  • the present application can be implemented in a combination of hardware or hardware and computer software in combination with the algorithmic steps of the various examples described in the embodiments disclosed herein. Whether a function is implemented in hardware or computer software to drive hardware depends on the specific application and design constraints of the solution. A person skilled in the art can use different methods to implement the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present application.
  • the embodiment of the present application may divide the function module into the access network device according to the foregoing method example.
  • each function module may be divided according to each function, or two or more functions may be integrated into one processing module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of the module in the embodiment of the present application is schematic, and is only a logical function division, and the actual implementation may have another division manner.
  • FIG. 6 is a schematic diagram showing a possible composition of the access network device involved in the foregoing and the embodiment.
  • the access network device may include the following.
  • the first computing unit is configured to support the access network device to perform step 301 in the beamforming method shown in FIG. 3.
  • the second calculating unit 602 is configured to support the access network device to perform step 302 in FIG. 3, and step 3021, step 3022, step 3023, step 401, step 402, step 501, and step 502 in the foregoing.
  • the construction unit 603 is configured to support the access network device to perform step 303 in the beamforming method shown in FIG. 3, and steps 3031 and 3032 in the foregoing.
  • the third calculating unit 604 is configured to support the access network device to perform step 304 in the beamforming method shown in FIG. 3, and steps 3041 and 3042 in the foregoing.
  • the beamforming unit 605 is configured to support the access network device to perform step 305 in the beamforming method illustrated in FIG.
  • the access network device may include: an uplink detection subsystem 701, a baseband subsystem 702, a medium radio frequency subsystem 703, and an antenna feed.
  • the function of the first calculating unit 601 can be implemented by the uplink detecting subsystem 701
  • the function of the second calculating unit 602 can be implemented by the baseband subsystem 702
  • the function of the building unit 603 can be implemented by the baseband subsystem 703, and the third computing
  • the functionality of unit 604 may be implemented by baseband subsystem 702 or medium radio frequency subsystem 703, and the functionality of beamforming unit 605 may be implemented by antenna feed subsystem 704.
  • the access network device provided by the embodiment of the present application is configured to execute the foregoing data processing method, so that the same effect as the data processing method described above can be achieved.
  • FIG. 7 shows another possible composition diagram of the access network device involved in the above embodiment.
  • the access network device includes a processing module 801 and a communication module 802.
  • the processing module 801 is configured to control and manage the actions of the access network device.
  • the processing module 801 is configured to support the access network device to perform the steps in FIG. 3, FIG. 4, and FIG. 5, and/or used in the description herein. Other processes of technology.
  • Communication module 802 is used to support communication between the access network device and other network entities, such as with the terminal shown in FIG.
  • the access network device may further include a storage module 803 for storing program codes and data of the access network device.
  • the processing module 801 can be a processor or a controller. It is possible to implement or carry out the various illustrative logical blocks, modules and circuits described in connection with the present disclosure.
  • the processor can also be a combination of computing functions, for example, including one or more microprocessor combinations, a combination of a DSP and a microprocessor, and the like.
  • the communication module 802 can be a transceiver, a transceiver circuit, a communication interface, or the like.
  • the storage module 803 can be a memory.
  • the access network device involved in the embodiment of the present application may be the access network device shown in FIG. 8.
  • a "unit” herein may refer to an application specific integrated circuit (ASIC), circuitry, a processor and memory that executes one or more software or firmware programs, integrated logic circuitry, and/or other functions that provide the functionality described above.
  • ASIC application specific integrated circuit
  • FIG. 8 Each unit can be implemented by the processor and memory of FIG.
  • the access network device can include one or more ports 904 coupled to the transceiver 903.
  • Transceiver 903 can be a transmitter, a receiver, or a combination thereof, that transmits or receives data packets from other network elements through port 904.
  • Processor 901 is coupled to transceiver 903 for processing data packets.
  • Processor 901 can include one or more multi-core processors and/or memory 902.
  • the processor 901 can be a general purpose processor, an application specific integrated circuit, or a digital signal processing (DSP).
  • Memory 902 can be a non-transitory storage medium coupled to processor 901 for storing different types of data.
  • the memory 902 may include a read only memory (ROM), a random access memory (RAM), or other types of dynamic storage devices that can store information and instructions, and may also be a disk storage.
  • the embodiment of the present invention further provides a computer storage medium for storing computer software instructions used by the access network device shown in FIG. 2, FIG. 6, FIG. 7, or FIG. 8, which includes an embodiment for performing the above method.
  • the program designed. Beamforming can be achieved by executing a stored program.
  • the embodiment of the present application further provides a computer program product comprising instructions, which when executed on a computer, enable the computer to perform the beamforming method implemented by the above method embodiment.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of modules or units is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or It can be integrated into another device, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through Some interfaces, indirect couplings or communication connections of devices or units may be in electrical, mechanical or other form.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may be one physical unit or multiple physical units, that is, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • An integrated unit can be stored in a readable storage medium if it is implemented as a software functional unit and sold or used as a standalone product.
  • the technical solution of the embodiments of the present application may be embodied in the form of a software product in the form of a software product in essence or in the form of a contribution to the prior art, and the software product is stored in a storage medium.
  • a number of instructions are included to cause a device (which may be a microcontroller, chip, etc.) or a processor to perform all or part of the steps of the various embodiments of the present application.
  • the foregoing storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a random access memory RAM, a magnetic disk, or an optical disk.

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Abstract

本申请实施例提供一种波束成形方法及设备,涉及通信技术领域,在配置天线阵列的波束成形的权值时不需要终端进行反馈,因而可以提高波束成形的实时性。具体方案为:接入网设备计算上行信道的频率响应,根据上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数,该模型参数在上、下行子载波频点具有互易性,根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应,根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值,根据权值对天线阵列进行下行波束成形,该天线阵列为双极化天线阵列或单极化天线阵列。本申请实施例用于波束成形。

Description

一种波束成形方法及设备 技术领域
本申请实施例涉及通信技术领域,尤其涉及一种波束成形方法及设备。
背景技术
作为新一代移动通信的关键技术,大规模多入多出(Massive MIMO)技术可以提供更大的空间自由度。利用Massive MIMO波束成形技术可以自动调整发射或接收天线方向图,从而获得更好的覆盖和容量性能。
一种现有波束成形方案为,根据终端上报的预编码矩阵指示(precoding matrix indicator,PMI)来构造波束成形的权值,从而根据波束成形的权值进行波束成形。具体的,针对不同的天线阵列,终端配置对应的码本集,这些码本集为候选权值{wm},基站和终端共享这些码本集,其中m=1,2,...,M,M表示码本集中所***本的总数。终端依据接收信号计算下行信道的频率响应hDL,对每一个候选权值wm,计算其在此信道下加权在基站天线阵列上可能获得的波束成形信噪比(signal noise ratio,SNR)/接收功率增益。而后,终端选择使得SNR/接收功率增益最大的m作为PMI上报给基站,基站依据此PMI在相同码本集下选择对应的候选权值,加权在天线阵列上进行波束成形。
现有技术中的方案需要终端在得到hDL后,将PMI反馈给基站,以确定波束成形的权值,从而进行波束成形,这种反馈机制使得波束成形的实时性下降。这样,在基站等待终端反馈后再进行波束成形时,由于环境变化、终端移动等因素,信道已经发生变化,基站再采用变化之前的信道的PMI进行波束成形,将使得误差较大。
发明内容
本申请实施例提供一种波束成形方法及设备,在配置天线阵列的波束成形的权值时不需要终端进行反馈,因而可以提高波束成形的实时性。
为达到上述目的,本申请实施例采用如下技术方案:
第一方面,提供了一种波束成形方法,包括:首先,接入网设备计算上行信道的频率响应。而后,接入网设备根据上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数。其中,该模型参数在上、下行子载波频点具有互易性。之后,接入网设备根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应。而后,接入网设备根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值。进而,接入网设备根据权值对天线阵列进行下行波束成形,天线阵列为双极化天线阵列或单极化天线阵列。
这样,接入网设备可以根据上行信道的频率响应和信道的频率响应数学模型,直接构建下行信道的频率响应,并根据下行信道的频率响应计算波束成形的权值,从而进行波束成形,因而在计算波束成形的权值时并不需要像现有技术那样需要终端进行反馈,从而可以提高波束成形的实时性,减小由于实时性较差而导致的误差。
结合第一方面,在一种可能的实现方式中,模型参数包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相。
也就是说,信道的频率响应数学模型中的自变量可以包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,接入网设备根据上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数包括:首先,接入网设备根据上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的目标似然谱。而后,接入网设备根据目标似然谱计算各路径的目标值和各路径的到达角的目标值。之后,接入网设备根据各路径的路程的目标值和各路径的到达角的目标值,计算各路径的振幅的目标值和各路径的初相的目标值。
其中,通过构建目标似然谱,并在目标似然谱上搜索峰值,来获得模型参数的方法较为简单。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,该目标似然谱是对上行信道的频率响应的导向矢量共轭补偿后相干累加形成的空间谱。
这样,可以将真实值在目标似然谱上以峰值的方式突显出来,从而使得通过搜索谱峰求解模型参数的方式更为快速、准确。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,接入网设备根据目标似然谱计算各路径的目标值和各路径的到达角的目标值包括:接入网设备根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。接入网设备根据各路径的路程的初始值和各路径的到达角的初始值,通过优化算法计算各路径的路程的目标值和各路径的到达角的目标值。
也就是说,接入网设备可以通过在目标似然谱上搜索峰值,简单、快速地获得模型参数的初始值,而后通过优化算法准确地求解各模型参数的目标值。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,接入网设备根据目标似然谱计算各路径的目标值和各路径的到达角的目标值包括:接入网设备根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。接入网设备根据目标似然谱、各路径的路程的初始值和各路径的到达角的初始值,通过搜索算法计算各路径的路程的目标值和各路径的到达角的目标值。
也就是说,接入网设备通过在目标似然谱上搜索峰值来求解各模型参数的初始值和目标值,该种方式较为简单。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,接入网设备根据上行信道的频率响应,通过优化算法求解各模型参数的目标值。
这样,接入网设备直接在整个参数空间求解模型参数,因而更为准确。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,该信道的频率响应数学模型不包括方向图信息。
这样,在根据信道的频率响应数学模型构建下行信道频率响应数学模型时,不需要首先对信道的频率响应数学模型进行域变换,从而使得计算复杂度低、构建过程更为简单。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,信道的频率响应数学模型的表达式为:
Figure PCTCN2017093052-appb-000001
其中,F(k,i)表示信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距。
这样,该表达式提供了一种简单的信道的频率响应数学模型的具体形式。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,上行信道的频率响应的目标似然谱的表达式为:
Figure PCTCN2017093052-appb-000002
其中,Θ(d,θ)表示目标似然谱,hUL(k,i)表示上行信道的频率响应,d表示路径的路程,θ表示路径的到达角,λUL,i表示第i个上行子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,||||2表示欧几里得范数。
这样,该表达式提供了一种通过共轭补偿和相干累加获得的目标似然谱的具体形式。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为面阵时,信道的频率响应数学模型的表达式为:
Figure PCTCN2017093052-appb-000003
其中,F(kH,kV,i)表示信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,kH表示天线阵列的行数,kV表示天线阵列的列数,
Figure PCTCN2017093052-appb-000004
表示第n条路径的水平角,γn表示第n条路径的俯仰角。
这样,该表达式提供了一种面阵情况下的信道的频率响应数学模型的具体形式。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为双极化天线阵列时,上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,模型参数包括第一极化模型参数和第二极化模型参数,模型参数符合如下表达式:
Figure PCTCN2017093052-appb-000005
其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,
Figure PCTCN2017093052-appb-000006
表示第一极化上行信道的频率响应数学模型,
Figure PCTCN2017093052-appb-000007
表示第二极化上行信道的频率响应数学模型,F表示信道的频率响应数学模型,
Figure PCTCN2017093052-appb-000008
表示第一极化上行信道的频率响应,
Figure PCTCN2017093052-appb-000009
表示第二极化上行信道的频率响应,||||2表示欧几里得范数。
这样,在双极化天线阵列场景下,接入网设备可以通过将双极化的优化目标函数相加,来根据双极化信息联合求解模型参数,从而可以更加突显出真实多径在优化目标函数上形成的峰值,相对抑制噪声等干扰在目标优化函数上形成的伪峰,从而可以降低迭代次数,便于更加高效、准确地确定双极化情况下的模型参数。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为双极化天线阵列时,上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应。接入网设备根据上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的目标似然谱包括:接入网设备根据第一极化上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的第一极化似然谱。接入网设备根据第二极化上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的第二极化似然谱。其中,第一极化似然谱与第二极化似然谱的和即为目标似然谱。
这样,在双极化天线阵列场景下,接入网设备可以通过联合第一极化似然谱和第二极化似然谱来求解模型参数,从而更加突显出真实多径在目标似然谱上形成的谱峰,相对抑制噪声等干扰在目标似然谱上形成的伪峰,从而可以降低迭代次数,便于更加简单、高效、准确地确定模型参数。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为双极化天线阵列时,各路径的振幅包括第一极化对应的各路径的振幅和第二极化对应的各路径的振幅,各路径的初相包括第一极化对应的各路径的初相和第二极化对应的各路径的初相,下行信道的频率响应包括第一极化下行信道的频率响应和第二极化下行信道的频率响应。接入网设备根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应包括:接入网设备根据模型参数中的各路径的路程、各路径的到达角、第一极化对应的各路径的振幅、第一极化对应的各路径的初相、信道的频率响应数学模型和各下行子载波频点,构建第一极化下行信道的频率响应。并且,接入网设备根据模型参数中的各路径的路程、各路径的到达角、第二极化对应的各路径的振幅、第二极化对应的各路径的初相、信道的频率响应数学模型和各下行子载波频点,构建第二极化下行信道的频率响应。
也就是说,在双极化天线阵列场景下,接入网设备可以根据双极化信息,分别构建双极化下行信道的频率响应。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,权值包括第一极化权值和第二极化权值。接入网设备根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值包括:接入网设备根据第一极化下行信道的频率响应,计算第一极化对应的各下行子载波频点的波束成形的权值。并且,接入网设备根据第二极化下行信道的频率响应,计算第二极化对应的各下行子载波频点的波束成形的权值。
也就是说,在双极化天线阵列场景下,接入网设备可以根据双极化信息,分别计算双极化对应的各下行子载波频点的波束成形的权值。
结合第一方面和上述可能的实现方式,在另一种可能的实现方式中,模型参数符合如下表达式:
Figure PCTCN2017093052-appb-000010
其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元 的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,FUL表示上行信道的频率响应数学模型,F表示信道的频率响应数学模型,hUL表示上行信道的频率响应,||||2表示欧几里得范数。
也就是说,在单极化天线阵列场景中,通过优化算法求解模型参数时,模型参数满足上述表示式。
第二方面,本申请实施例提供了一种接入网设备,包括:第一计算单元,用于计算上行信道的频率响应。第二计算单元,用于根据上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数,模型参数在上、下行子载波频点具有互易性。构建单元,用于根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应。第三计算单元,用于根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值。波束成形单元,用于根据权值对天线阵列进行下行波束成形,天线阵列为双极化天线阵列或单极化天线阵列。
结合第二方面,在一种可能的实现方式中,模型参数包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,第二计算单元具体用于:根据上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的目标似然谱。根据目标似然谱计算各路径的目标值和各路径的到达角的目标值。根据各路径的路程的目标值和各路径的到达角的目标值,计算各路径的振幅的目标值和各路径的初相的目标值。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,第二计算单元具体用于:根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。根据各路径的路程的初始值和各路径的到达角的初始值,通过优化算法计算各路径的路程的目标值和各路径的到达角的目标值。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,第二计算单元具体用于:根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。根据目标似然谱、各路径的路程的初始值和各路径的到达角的初始值,通过搜索算法计算各路径的路程的目标值和各路径的到达角的目标值。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,信道的频率响应数学模型的表达式为:
Figure PCTCN2017093052-appb-000011
其中,F(k,i)表示信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,上行信道的频率响应的目标似然谱的表达式为:
Figure PCTCN2017093052-appb-000012
其中,Θ(d,θ)表示目标似然谱,hUL(k,i)表示上行信道的频率响应,d表示路径的路程,θ表示路径的到达角,λUL,i表示第i个上行子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,||||2表示 欧几里得范数。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为面阵时,信道的频率响应数学模型的表达式为:
Figure PCTCN2017093052-appb-000013
其中,F(kH,kV,i)表示信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,kH表示天线阵列的行数,kV表示天线阵列的列数,
Figure PCTCN2017093052-appb-000014
表示第n条路径的水平角,γn表示第n条路径的俯仰角。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为双极化天线阵列时,上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,模型参数包括第一极化模型参数和第二极化模型参数,模型参数符合如下表达式:
Figure PCTCN2017093052-appb-000015
其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,
Figure PCTCN2017093052-appb-000016
表示第一极化上行信道的频率响应数学模型,
Figure PCTCN2017093052-appb-000017
表示第二极化上行信道的频率响应数学模型,F表示信道的频率响应数学模型,
Figure PCTCN2017093052-appb-000018
表示第一极化上行信道的频率响应,
Figure PCTCN2017093052-appb-000019
表示第二极化上行信道的频率响应,||||2表示欧几里得范数。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为双极化天线阵列时,上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,第二计算单元具体用于:根据第一极化上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的第一极化似然谱。根据第二极化上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的第二极化似然谱。其中,第一极化似然谱与第二极化似然谱的和即为目标似然谱。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,当天线阵列为双极化天线阵列时,各路径的振幅包括第一极化对应的各路径的振幅和第二极化对应的各路径的振幅,各路径的初相包括第一极化对应的各路径的初相和第二极化对应的各路径的初相,下行信道的频率响应包括第一极化下行信道的频率响应和第二极化下行信道的频率响应。构建单元具体用于:根据模型参数中的各路径的路程、各路径的到达角、第一极化对应的各路径的振幅、第一极化对应的各路径的初相、信道的频率响应数学模型和各下行子载波频点,构建第一极化下行信道的频率响应。根据模型参数中的各路径的路程、各路径的到达角、第二极化对应的各路径的振幅、第二极化对应的各路径的初相、信道的频率响应数学模型和各下行子载波频点,构建第二极化下行信道的频率响应。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,权值包括第一极化 权值和第二极化权值,第三计算单元具体用于:根据第一极化下行信道的频率响应,计算第一极化对应的各下行子载波频点的波束成形的权值。根据第二极化下行信道的频率响应,计算第二极化对应的各下行子载波频点的波束成形的权值。
结合第二方面和上述可能的实现方式,在另一种可能的实现方式中,模型参数符合如下表达式:
Figure PCTCN2017093052-appb-000020
其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,FUL表示上行信道的频率响应数学模型,F表示信道的频率响应数学模型,hUL表示上行信道的频率响应,||||2表示欧几里得范数。
第三方面,本申请实施例提供了一种接入网设备,包括:处理器、存储器、总线和通信接口;处理器与存储器通过总线连接,存储器用于存储计算机执行指令,当接入网设备运行时,处理器执行存储器存储的计算机执行指令,以使接入网设备执行如第一方面任意一种可能的实现方式中的波束成形方法。
第四方面,本申请实施例提供了一种计算机可读存储介质,用于储存为上述接入网设备所用的计算机软件指令,当其在计算机上运行时,使得计算机可以执行如第一方面任意一种可能的实现方式中的波束成形方法。
第五方面,本申请实施例提供了一种包含指令的计算机程序产品,当其在计算机上运行时,使得计算机可以执行如第一方面任意一种可能的实现方式中的波束成形方法。
其中,上述第二方面至第五方面对应的有益效果,可以参见上述第一方面中的相关描述,这里不再赘述。
附图说明
图1为本申请实施例提供的一种通信***的结构示意图;
图2为本申请实施例提供的一种接入网设备的结构示意图;
图3为本申请实施例提供的一种波束成形方法流程图;
图4为本申请实施例提供的另一种波束成形方法流程图;
图5为本申请实施例提供的另一种波束成形方法流程图;
图6为本申请实施例提供的另一种接入网设备的结构示意图;
图7为本申请实施例提供的另一种接入网设备的结构示意图;
图8为本申请实施例提供的另一种接入网设备的结构示意图。
具体实施方式
为了便于理解,示例的给出了部分与本申请实施例相关概念的说明以供参考。如下所示:
波束成形:通过对多天线阵元接收到的各路信号进行加权合成,形成所需的理想信号的技术。
频点:各个子载波的频率大小。
路径:通信信道中的电磁波经过折反射、绕射后连接基站和用户之间的路线。
路径的路程:上述路线的长度。
路径的到达角:上述路线到达基站时与基站天线阵列方向的夹角。
似然谱:是常规谱估计的一种空间谱,这种空间谱还可以称为巴特莱特(Bartlett)谱等,是关于路程和到达角的二维函数,或者,也可以是关于路程或到达角的一维函数。
极化方向:指天线辐射时形成的电场强度的方向。
单极化天线:只包括一个极化方向的天线。
双极化天线:组合了+45°和-45°两副极化方向相互正交的天线,且工作在收发双工模式下。
阵元:即天线振子,天线阵列上的元器件,具有导向和放大电磁波的作用,用于使天线阵列接收到的电磁信号更强。
优化:指通过算法得到要求问题的更优解。
搜索算法:指利用计算机的高性能来有目的的穷举一个问题解空间的部分或所有的可能情况,从而求出问题的解的一种方法。
导向矢量:具有引导方向、指示方向的矢量。
下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行描述。其中,在本申请实施例的描述中,除非另有说明,“/”表示或的意思,例如,A/B可以表示A或B;本文中的“和/或”仅仅是一种描述关联对象的关联关系,表示可以存在三种关系,例如,A和/或B,可以表示:单独存在A,同时存在A和B,单独存在B这三种情况。另外,在本申请实施例的描述中,“多个”是指两个或多于两个。
本申请实施例提供的技术方案可以应用于各种FDD移动通信***中设置有天线阵列的接入网设备。例如,这里的移动通信***可以是第三代移动通信技术(3rd generation mobile communication,3G)通信***,***移动通信技术(the 4th generation mobile communication,4G)通信***,以及未来演进网络,如第五代移动通信技术(5th-generation,5G)通信***。例如,这里的移动通信***可以是长期演进(long term evolution,LTE)***,3G相关的蜂窝***等,以及其他此类通信***。尤其地,可以应用于5G超密集组网(ultra dense network,UDN)***中。需要说明的是,5G标准中可以包括机器对机器(machine to machine,M2M)、D2M、宏微通信、增强型移动互联网(enhance mobile broadband,eMBB)、超高可靠性与超低时延通信(ultra reliable&low latency communication,uRLLC)以及海量物联网通信(massive machine type communication,mMTC)等场景,这些场景可以包括但不限于:接入网设备与接入网设备之间的通信场景,接入网设备与终端之间的通信场景等。
本申请实施例提供的技术方案可以应用于如图1所示的***架构中,该***架构中可以包括接入网设备100、以及与接入网设备100连接的一个或多个终端200。接入网设备100中设置有天线阵列,接入网设备100通过天线阵列发射和接收信号,从而与终端200进行通信。其中,接入网设备100在通过天线阵列发射信号前,可以配置波束成形的权值,从而根据该权值进行下行波束成形,并通过天线阵列进行信号发射。
其中,这里的接入网设备可以是中继站或接入点等。接入网设备可以是全球移动通信***(global system for mobile communication,GSM)或码分多址(code division multiple access,CDMA)网络中的基站收发信台(base transceiver station,BTS),也可以是宽带码分多址(wideband code division multiple access,WCDMA)中的NB(NodeB),还可以是LTE中的eNB或eNodeB(evolutional NodeB)。接入网设备100还可以是云无线接入网络(cloud radio access network,CRAN)场景下的无线控制器。接入网设备100还可以是未来5G网络中的网络设备或未来演进的公共陆地移动网络(public land mobile network,PLMN)中的网络设备等。未来5G网络中的网络设备可以包括新型无线电基站(new radio  NodeB),下一代基站(next generation NodeB,gNB),或者传输点(transmission point)等。
在一个示例中,接入网设备可以通过如图2所示的结构实现。如图2所示,接入网设备可以包括上行探测子***、中射频子***、基带子***和天馈子***。其中,上行探测子***可以用于接收终端发送的信号例如信道探测参考信号(sounding reference signal,SRS),计算上行信道的频率响应等。基带子***可以用于基本的物理层算法的实现。中射频子***可以用于在基带信号的基础上进行上变频(即将信号从基频上移到载频),并解决上变频过程中产生的失真、误差等问题。天馈子***包括天线阵列,可以用于获取天线阵列的阵列结构,进而计算加权后的天线阵列的波束方向图,即用于进行下行波束成形。应该注意的是,在具体实现过程中,接入网设备还可以采用其他通用硬件架构,而并非仅仅局限于图2所示的一种硬件架构。其中,关于天线阵列波束成形权值的配置,具体可以在中射频子***中进行,也可以在基带子***中进行。
现有技术中的波束成形方案需要根据终端反馈的PMI构造波束成形的权值,从而使得波束成形的实时性较差,误差也较大。而实际上,在理想情况下,当天线阵列中各阵元的波束成形的权值向量与对应的下行信道的频率响应在天线数域上的分布互为共轭时,终端可以得到最大的SNR/接收功率增益。这就需要基站在发射前预先知道下行信道的频率响应。在目前采用的两种主要制式下,时分双工(time division duplexing,TDD)上、下行的信道的频率响应在天线数域上的分布具有互易性,而在频分双工(frequency division duplexing,FDD)制式下,由于频段的差别,上、下行的信道的频率响应在天线数域上的分布,不像TDD那样具有良好互易性。在此基础上,本申请实施例提供了一种波束成形方法,接入网设备可以根据上行信道的频率响应和信道的频率响应数学模型,构建下行信道的频率响应,并根据下行信道的频率响应计算波束成形的权值,从而进行下行波束成形,因而在计算波束成形的权值时并不需要像现有技术那样需要终端进行反馈,因而可以提高波束成形的实时性,减小由于实时性较差而导致的误差。
以下将以图1所示场景为例,结合附图对本申请实施例提供的方案进行详细说明。
参见图3,本申请实施例提供一种波束成形方法,包括:
301、接入网设备计算上行信道的频率响应。
其中,上行信道的频率响应用于描述上行信道在天线阵列各阵元、各上行子载波频点上的响应情况。在本步骤中,接入网设备可以根据从终端接收到的SRS等上行信号,计算上行信道的频率响应。
302、接入网设备根据上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数,模型参数在上、下行子载波频点具有互易性。
接入网设备中可以预先设置有信道的频率响应数学模型,该信道的频率响应数学模型用于描述信道的频率响应,即信道在各子载波频点的响应情况。该信道的频率响应数学模型包括至少一个模型参数,该模型参数为信道多径参数,该模型参数在上、下行子载波频点具有互易性。
其中,由于上行子载波频点和下行子载波频点之间的频率间隔较大,各上行子载波频点之间的频率间隔较小,且各下行子载波频点之间的频率间隔较小,当该模型参数在上、下行子载波频点具有互易性时,可以理解的是,该模型参数在各上行子载波频点也具有互易性,且该模型参数在各下行子载波频点也具有互易性。也就是说,该模型参数在各上行子载波频点和各下行子载波频点具有互易性。可以理解为,该模型参数可以适用于各上、下行子载波频点,可以在各上、下行子载波频点间进行频点搬移。
这样,由于该信道的频率响应数学模型中的模型参数可以适用于各子载波频点,当将上行子载波频点代入该信道的频率响应数学模型时,该信道的频率响应数学模型可以用于表示上行信道的频率响应;当将下行子载波频点代入该信道的频率响应数学模型时,该信道的频率响应数学模型可以用于表示下行 信道的频率响应。
因而,在根据上行信道的频率响应计算获得上述模型参数后,当将下行子载波频点和上述模型参数代入该信道的频率响应数学模型时,可以得到下行信道的频率响应。也就是说,当信道的频率响应数学模型的模型参数在上、下行子载波频点具有互易性时,可以使得重构下行信道的过程更为简单。
303、接入网设备根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应。
在步骤302中获得信道的频率响应数学模型中的模型参数后,接入网设备可以将下行子载波频点和获得的模型参数代入该信道的频率响应数学模型,从而得到下行信道的频率响应。
304、接入网设备根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值。
由于当波束成形的权值与对应的下行信道的频率响应在天线数域上的分布互为共轭时,终端可以得到最大的波束成形SNR增益,因而在步骤303中得到下行信道的频率响应后,接入网设备可以根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值。
其中,第i个下行子载波频点对应的波束成形的权值wi的表达式可以为如下式1:
Figure PCTCN2017093052-appb-000021
在式1中,hDL(k,i)表示第k个阵元对应的第i个下行子载波频点在下行信道的频率响应,[]H表示共轭矩阵,||||2表示欧几里得范数。
接入网设备可以根据上述式1,分别获得各下行子载波频点在各阵元上对应的波束成形的权值。
305、接入网设备根据权值对天线阵列进行下行波束成形,该天线阵列为双极化天线阵列或单极化天线阵列。
其中,双极化天线阵列中的每个阵元对应两个极化方向,即第一极化方向和第二极化方向;单极化天线阵列中的每个阵元对应一个极化方向。在获得各下行子载波频点对应的波束成形的权值后,接入网设备可以将各下行子载波频点对应的波束成形的权值,加权在天线阵列的各阵元上进行下行波束成形,即将天线阵列各阵元上的权值乘以各自阵元上的信号,等效为天线阵列上的权值向量和信号向量做点积,而后进行信号发射。
在上述步骤301-305描述的波束成形方法中,接入网设备可以根据上行信道的频率响应和信道的频率响应数学模型,直接构建下行信道的频率响应,并根据下行信道的频率响应计算波束成形的权值,从而进行波束成形,因而在计算波束成形的权值时并不需要像现有技术那样需要终端进行反馈,从而可以提高波束成形的实时性,减小由于实时性较差而导致的误差。
需要说明的是,在本申请实施例中,由于信道的频率响应模型中的模型参数在上、下行子载波频点具有互易性,因而在根据上行信道的频率响应获得该模型参数后,将该模型参数和各下行子载波频点代入信道的频率响应数学模型,即可获得下行信道的频率响应,因而该种构建下行信道的频率响应的方法简单、实时,易于实现,从而降低了波束成形的权值的计算复杂度,提升了接入网设备的处理效率。
此外,在现有根据终端上报的PMI来构造波束成形的权值技术方案中,接入网设备通过构造码本集,并选择使得接收功率增益最大的码本来逼近最佳的权值,相当于是对hDL所在的空间进行量化,从有限的离散值中选择最接近真实值的候选,这样就势必会引起量化误差。如果码本集稀疏,量化误差会增大,进而影响波束成形性能;如果码本集密集,尤其在Massive MIMO情况下,计算复杂度会非常大,进而影响效率。所以,PMI的量化误差对性能的影响是不可忽视的。
而且,在现有根据终端上报的PMI来构造波束成形的权值技术方案中,接入网设备需要针对不同的阵元、终端配置对应的码本集的,而只有配置数量庞大的码本集才可以保证量化误差尽可能小。根据3GPP标准文件,接入网设备侧在4端口下需要16码本,而在8端口下需要256码本,可以想见,16端口、32端口、甚至Massive MIMO***需要的64、128端口下所需要的码本集数目则更为庞大,这势必会增加通信***的计算负担和数据处理效率。
本申请实施例提供的技术方案,接入网设备通过直接构建下行信道的频率响应,并根据下行信道的频率响应来构造波束成形的权值,还可以避免由码本集带来的量化误差和庞大的数据处理、计算、缓存负担。
另外,现有技术中还有一种基于到达角(direction of arrival,DOA)估计的波束成形技术。其具体实现方式为:接入网设备基于上行SRS信号进行DOA估计,计算信道的主径的DOA;将DOA代入导向矢量,作为波束成形的权值;将该权值作为波束成形的权值加权在天线阵列上。该种方案过于依赖于DOA估计的精度,当DOA估计出现偏差时,波束成形的权值也将出现偏差。并且,该种方案仅估计信道的主径的DOA代入导向矢量作为波束成形的权值,也就是说,其他能量相对较弱的径会被忽略。这种方式对于只有一条径的视线(line of sight,LOS)信道或者主径非常明显而其他径非常弱小的信道较为适用,但是,对于非视线(not line of sight,NLOS)信道,尤其是存在多条能量相差较近的径时,这种方式只能得到一个DOA,因此基于该DOA计算的权值误差也较大。
与现有基于到达角DOA估计的波束成形技术相比,本申请实施例提供的技术方案不依靠对单个主径的DOA估计,而是通过直接构建下行信道的频率响应,根据下行信道的频率响应来构造波束成形的权值,这样单个主径的DOA估计精度不会对性能好坏产生决定性影响,并且对NLOS信道也具有很好的适用性。
在本申请实施例中,具有模型参数在上、下行子载波频点具有互易性这一特性的信道的频率响应数学模型的具体形式可以有多种,信道的频率响应数学模型中的模型参数具体也可以有多种不同的组合形式。例如,在一种可能的实现方式中,上述模型参数可以包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相。其在,各路径的路程、各路径的到达角、各路径的振幅和各路径的初相,在上、下行子载波频点具有互易性。值得注意的是,这里的各路径的路程并不是一个参数,当路径有N个时,这里的各路径的路程表示N个路径的路程,是N个参数;其它模型参数(各路径的到达角、各路径的振幅和各路径的初相)类似。
并且,本申请实施例提供的信道的频率响应数学模型是一种简化的模型,不包括天线方向图,不需要进行复杂的域变换等计算过程,因而通过该信道的频率响应数学模型构建天线阵列(尤其是双极化天线阵列)的下行信道的频率响应的过程较为简单。
示例性的,当模型参数包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相时,一种信道的频率响应数学模型的表达式可以为如下式2:
Figure PCTCN2017093052-appb-000022
其中,F(k,i)表示信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距。
示例性的,当模型参数包括各路径的路程、到达角、振幅和初相时,另一种信道的频率响应数学模型的表达式可以参见如下式3:
Figure PCTCN2017093052-appb-000023
上述式3表示的是当天线阵列是面阵的情况下,天线阵列对应的信道的频率响应数学模型,其中,F(kH,kV,i)表示信道的频率响应数学模型,kH表示天线阵列的行数,kV表示天线阵列的列数,
Figure PCTCN2017093052-appb-000024
表示第n条路径的水平角,γn表示第n条路径的俯仰角。
另外,在本申请实施例中,接入网设备在步骤302中根据上行信道的频率响应和各上行子载波频点,求解信道的频率响应数学模型中的模型参数的方式可以有多种。示例性的,在第一种求解模型参数的方法中,接入网设备可以构建一个关于上行信道的频率响应的目标似然谱,根据该目标似然谱求解各模型参数。在第二种求解模型参数的方法中,接入网设备可以直接通过优化算法求解各模型参数。
例如,当模型参数包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相时,在上述第一种可能的实现方式中,步骤302的一种具体实施方式可以包括:
3021、接入网设备根据上行信道的频率响应和各上行子载波频点构建上行信道的频率响应的目标似然谱。
其中,这里的目标似然谱是关于路径的路程和路径的到达角中至少一种参数的函数。
3022、接入网设备根据目标似然谱计算各路径的目标值和各路径的到达角的目标值。
3023、接入网设备根据各路径的路程的目标值和各路径的到达角的目标值,计算各路径的振幅的目标值和各路径的初相的目标值。
其中,各模型参数的目标值是指各模型参数的最优值。由于目标似然谱是关于路径的路程和路径的到达角中至少一种参数的函数,因而可以根据目标似然谱首先获得各路径的目标值和各路径的到达角的目标值,而后再根据各路径的路程的目标值和各路径的到达角的目标值,计算各路径的振幅的目标值和各路径的初相的目标值。
上述第一种可能的实现方式具体还可以包括以下方式A和方式B。
在方式A中,上述步骤3022具体可以包括:
401、接入网设备根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。
402、接入网设备根据各路径的路程的初始值和各路径的到达角的初始值,通过优化算法计算各路径的路程的目标值和各路径的到达角的目标值。
在方式A中,上述步骤3022具体可以包括:
501、接入网设备根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。
502、接入网设备根据目标似然谱、各路径的路程的初始值和各路径的到达角的初始值,通过搜索算法计算各路径的路程的目标值和各路径的到达角的目标值。
其中,上述步骤401和步骤501中计算获得的各路径的路程的初始值和各路径的到达角的初始值仅为初始估计值,并不一定是各路径的路程和各路径的到达角的最优值,因而需要根据各路径的路程和各路径的到达角的初始值进一步计算各路径的路程和各路径的到达角的最优值,即估计各路径的路程和各路径的到达角的目标值。
在上述步骤401、步骤402和步骤501中,接入网设备可以构建一个目标似然谱,进而通过搜索算法在目标似然谱上确定峰值,从而求解模型参数,且该种方法较为简单。在步骤502中,接入网设备可以构建一个目标函数,通过优化算法(例如最大似然法)在目标函数上确定峰值,从而求解模型参数,且该种方法更为准确。
在实际的接入网设备中,天线阵列可以为双极化天线阵列,也可以为单极化天线阵列。以下将以式2所示的信道的频率响应数学模型为例,根据上述几种求解模型参数的方法,分别对单极化天线阵列场景和双极化天线阵列场景中的波束成形方法进行具体说明。
场景1:单极化天线阵列场景
该场景对应的波束成形方法流程图可以参见图4。在该场景中,接入网设备可以在步骤301中计算获得上行信道的频率响应hUL(k,i),该hUL(k,i)可以根据各上行子载波频点和式2所示的信道的频率响应数学模型,被表示为如式4所示的上行信道的频率响应数学模型FUL(k,i):
Figure PCTCN2017093052-appb-000025
其中,λUL,i表示第i个子载波频点对应的波长,FUL(k,i)表示上行信道的频率响应数学模型,关于式4中其它参数的描述可以参见上述式2中的相关说明。
基于式4所示的上行信道的频率响应hUL(k,i),接入网设备可以在步骤3021中构建上行信道的频率响应的目标似然谱,该目标似然谱具体可以为如式5所示形式:
Figure PCTCN2017093052-appb-000026
其中,Θ(d,θ)表示目标似然谱,hUL(k,i)表示上行信道的频率响应,d表示路径的路程,θ表示路径的到达角,λUL,i表示第i个上行子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,上标“2”表示求平方。
在式5中,区别于各路径的路程dn,d用于表示路径的路程这一参数;区别于各路径的到达角θn,θ用于表示路径的到达角这一参数。
根据如式5所示的目标似然谱,接入网设备可以在步骤401或步骤501中根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。
具体的,式5所示的目标似然谱对应的参数空间可以划分为多个网格点,接入网设备可以通过搜索算法在网格点上遍历搜索峰值,来估计各路径的路程dn的初始值和各路径的到达角θn的初始值。其中,在网格点上遍历搜索峰值时,可以预先设定一个阈值范围(例如比最高峰值小10dB),该阈值范围内的峰值数量即为路径的数量N。
需要说明的是,本申请实施例中的目标似然谱是一种通过对上行信道的频率响应的导向矢量(式4中的
Figure PCTCN2017093052-appb-000027
)做共轭补偿后,再相干累加而形成的空间谱。
在通过共轭补偿得到的目标似然谱上进行峰值搜索时,只有搜索到真实值处的路径路程和到夹角时,每个k、i上的导向矢量才会消掉,即每个k、i上的相位可以对齐,相干累加之后可以达到最大值。而其他位置处的相位均不能对齐,即相干累加达不到最大值。因此这种共轭补偿方式,可以将真实值在目标似然谱上以峰值的方式突显出来,从而使得通过搜索 谱峰求解模型参数的方式更为快速、准确。
另外,由于这种遍历搜索网格点对应的峰值的方式只是对dn和θn进行了粗略的估计,网格点对应的峰值并不一定是整个目标似然谱的峰值,因而得到的模型参数的值只是初始值,并不一定是模型参数的最优值。
在得到各路径的路程的初始值和各路径的到达角的初始值之后,在步骤402中,接入网设备可以将得到的dn的初始值和θn的初始值,代入到后续的优化求解过程中,进行进一步的精确估计,并通过消元的方法,将各路径的振幅an和各路径的初相φn用dn和θn表示,从而首先计算出dn的最优值和θn的最优值,也即dn的目标值和θn的目标值,进而根据dn的目标值和θn的目标值,计算an的最优值和φn的最优值,也即an的目标值和φn的目标值。
其中,通过优化算法求解模型参数过程的具体实现可以如下:
由式4可知,对于每一组模型参数估计值
Figure PCTCN2017093052-appb-000028
都可以通过信道的频率响应模型构建出上行信道的频率响应数学模型F′UL(k,i)即:
Figure PCTCN2017093052-appb-000029
其中,F′UL(k,i)表示与一组模型参数估计值
Figure PCTCN2017093052-appb-000030
对应的上行信道的频率响应数学模型FUL(k,i)。
模型参数的最优估计值
Figure PCTCN2017093052-appb-000031
是使得FUL(k,i)最逼近于步骤301中计算获得的真实的hUL(k,i),所以,对模型参数估计的问题可以转化为如下所示的优化问题:
Figure PCTCN2017093052-appb-000032
也就是说,在该场景中,模型参数符合如下表达式:
Figure PCTCN2017093052-appb-000033
其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,FUL表示上行信道的频率响应数学模型,F表示信道的频率响应数学模型,hUL表示上行信道的频率响应。
FUL(k,i|λ)=F(k,i|λUL)可以表明,上行信道的频率响应数学模型为,将各上行子载波频点对应的波长λUL代入信道的频率响应数学模型后得到的表达式。
上述式7所示的优化问题可以按照下列步骤求解:
(1)、将式4式写成矩阵形式,记
Figure PCTCN2017093052-appb-000034
Figure PCTCN2017093052-appb-000035
Figure PCTCN2017093052-appb-000036
Figure PCTCN2017093052-appb-000037
则式4式可以用矩阵表示为
HUL,i=ZiDiB      式13
进一步,记
Figure PCTCN2017093052-appb-000038
Figure PCTCN2017093052-appb-000039
联合I个上行子载波频点对应的式13,则全带宽的总的上行信道的频率响应数学模型可以表示为
GUL=YULB    式16
(2)、基于式16表示的矩阵形式,式7所示的优化问题可以表示为
Figure PCTCN2017093052-appb-000040
Figure PCTCN2017093052-appb-000041
固定时,
Figure PCTCN2017093052-appb-000042
的最优化问题即转化为线性规划问题,此时最优解可以表示为
Figure PCTCN2017093052-appb-000043
其中,
Figure PCTCN2017093052-appb-000044
表示
Figure PCTCN2017093052-appb-000045
的伪逆。
(3)、优化问题式17可以转化为一个只和
Figure PCTCN2017093052-appb-000046
有关,也就是只和
Figure PCTCN2017093052-appb-000047
有关的优化问题,即
Figure PCTCN2017093052-appb-000048
也就是说,通过消元的方式可以将式17中4N维优化问题,转化为式19中的2N维优化问题,这样可以降低计算复杂度,使得计算过程更为简单。
(4)、针对优化问题式19,可以采用单纯形法(例如下山单纯形法Nelder-Mead法)确定峰值,从而求得最优的
Figure PCTCN2017093052-appb-000049
这里求得的
Figure PCTCN2017093052-appb-000050
即分别为模型参数dn的目标值和θn的目标值。
在上述步骤402中得到最优的
Figure PCTCN2017093052-appb-000051
之后,在步骤3023中,接入网设备可以基于最优的
Figure PCTCN2017093052-appb-000052
通过上述式18计算最优的
Figure PCTCN2017093052-appb-000053
Figure PCTCN2017093052-appb-000054
这里求得的
Figure PCTCN2017093052-appb-000055
即分别为模型参数an的目标值、φn的目标值。
至此,模型参数dn、θn、an、φn的求解完成。
以上主要是以上述求解模型参数的第一种可能的实现方式中的方式A为例进行说明的,对于上述第一种可能的实现方式中的方式B,由于dn的初始值和θn的初始值是在参数空间划分的网格点上遍历搜索目标似然谱的峰值得到的解,并不一定是最优解,即网格点对应的峰值,并不一定是整个目标似然谱的峰值,因而接入网设备还可以在步骤502中通过遍历搜索目标似然谱上初始值附近的峰值,即在网格点附近对应的峰值,从而得到dn的目标值和θn的目标值,进而可以通过式18得到an的目标值和φn的目标值。
另外,对于上述求解模型参数的第二种可能的实现方式,接入网设备可以不通过目标似然谱求解dn的初始值和θn的初始值,而直接根据式17所示的优化目标函数,通过优化算法(例如极大似然法)求解dn的目标值、θn的目标值、an的目标值和φn的目标值。由于该种方式是在整个参数空间中搜索峰值,因而得到的模型参数更为精确。
在得到模型参数dn、θn、an、φn的目标值后,接入网设备可以在步骤303中根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应数学模型FDL(k,i),该FDL(k,i)即为接入网设备构建的下行信道的频率响应hDL(k,i):
Figure PCTCN2017093052-appb-000056
需要说明的是,这里的hDL(k,i)是根据模型参数以及信道的频率响应数学模型重构出的下行信道的频率响应,并不是真实的下行信道的频率响应。
在步骤304中,接入网设备可以基于构建出的下行信道的频率响应,得到上述式1所示的各下行子载波频点对应的最佳波束成形的权值。
在得到波束成形的权值后,接入网设备可以在步骤305中,根据该权值对天线阵列进行下行波束成形,而后进行信号发射。
可见,本申请实施例提供的波束成形方法,可以在单极化场景下,通过构建下行信道的频率响应,从而计算波束成形的权值以进行波束成形。
场景2:双极化天线阵列场景
该场景对应的波束成形方法流程图可以参见图5。在该场景中,由于双极化天线阵列中的每个阵元可以对应两个极化方向,因而接入网设备可以联合两个极化方向分别对应的信道特性重构下行信道的频率响应,从而进行波束成形。具体过程如下:
接入网设备可以在步骤301中计算获得上行信道的频率响应,该上行信道的频率响应可以包括第一极化上行信道的频率响应
Figure PCTCN2017093052-appb-000057
和第二极化上行信道的频率响应
Figure PCTCN2017093052-appb-000058
其中,该
Figure PCTCN2017093052-appb-000059
可以根据各上行子载波频点和信道的频率响应数学模型,被表示为如式22所示的第一极化上行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000060
Figure PCTCN2017093052-appb-000061
可以根据各上行子载波频点和信道的频率响应数学模型,被表示为如式23所示的第二极化上行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000062
Figure PCTCN2017093052-appb-000063
Figure PCTCN2017093052-appb-000064
其中,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角,
Figure PCTCN2017093052-appb-000065
表示第一极化对应的第n个路径的振幅,
Figure PCTCN2017093052-appb-000066
表示第二极化对应的第n个路径的振幅,
Figure PCTCN2017093052-appb-000067
表示第一极化对应的第n个路径的初相,
Figure PCTCN2017093052-appb-000068
表示第二极化对应的第n个路径的初相,λUL,i表示第i个上行子载波频点对应的波长。
接入网设备在步骤3021中,根据上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的目标似然谱可以包括:
接入网设备根据第一极化上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的第一极化似然谱;接入网设备根据第二极化上行信道的频率响应和各上行子载波频点,构建上行信道的频率响应的第二极化似然谱,第一极化似然谱和第二极化似然谱的和即为目标似然谱。
其中,第一极化似然谱和第二极化似然谱的形式可以参考上述式4。具体的,第一极化似然谱Θ+(d,θ)的表达式可以参见如下式24,第二极化似然谱Θ-(d,θ)的表达式可以参见如下式25,第一极化似然谱和第二极化似然谱相加后的目标似然谱ΘDP(d,θ)的表达式可以参见如下式26:
Figure PCTCN2017093052-appb-000069
Figure PCTCN2017093052-appb-000070
Figure PCTCN2017093052-appb-000071
在得到式26所示的目标似然谱后,与上述单极化场景类似,接入网设备可以在步骤401或步骤501中,根据目标似然谱计算各路径的路程的初始值和各路径的到达角的初始值。
具体的,式26所示的目标似然谱对应的参数空间可以划分为多个网格点,接入网设备可以通过搜索算法在网格点上遍历搜索峰值,来估计各路径的路程dn的初始值和各路径的到达角θn的初始值。
需要说明的是,由于式24和式25所示的似然谱是对导向矢量共轭补偿和相干累加形成的空间谱,因而可以将真实值在目标似然谱上以谱峰的方式突显。并且,由于双极化情况下,模型参数dn、θn是一样的,因此可以将双极化的似然谱(第一极化似然谱和第二极化似然谱)相加,从而融合成一个总的目标似然谱,进而根据总的目标似然谱来联合估计dn初始值和θn的初始值。由于在双极化情况下,对于噪声等无用信号,在第一极化似然谱上是峰时,在第二极化似然谱上很可能不是峰,例如可能是谷;对于有用信号,在第一极化似然谱上是峰时,在第二极化似然谱上也是峰,因而通过将双极化的似然谱相加,可以更加突显出真实多径在目标似然谱上形成的谱峰,相对抑制噪声等干扰在目标似然谱上形成的伪峰,从而可以降低迭代次数,便于更加简单、高效、准确地确定双极化情况下dn和θn的初始值。
在得到各路径的路程的初始值和各路径的到达角的初始值之后,在步骤402中,接入网设备可以将得到的dn的初始值和θn的初始值,代入到后续的优化求解过程中,进行进一步的精确估计,并通过消元的方法,将各路径的振幅an和各路径的初相φn用dn和θn表示,从而首先计算出dn的最优值和θn的最优值,也即dn的目标值和θn的目标值,进而计算an的最优值和φn的最优值,也即an的目标值和φn的目标值。
需要说明的是,在双极化场景下,各路径的振幅an包括第一极化对应的各路径的振幅
Figure PCTCN2017093052-appb-000072
和第二极化对应的各路径的振幅
Figure PCTCN2017093052-appb-000073
各路径的初相φn包括第一极化对应的各路径的初相
Figure PCTCN2017093052-appb-000074
和第二极化对应的各路径的初相
Figure PCTCN2017093052-appb-000075
相对应的,各路径的振幅的目标值也包括第一极化对应的各路径的振幅的目标值和第二极化对应的各路径的振幅的目标值,各路径的初相的目标值也包括第一极化对应的各路径的初相的目标值和第二极化对应的各路径的初相的目标值。
其中,通过优化算法求解模型参数的过程具体如下:
由式22和式23可知,对于每一组参数估计值
Figure PCTCN2017093052-appb-000076
都可以通过信道的频率响应模型构建出一对双极化的上行信道的频率响应数学模型,即第一极化上行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000077
和第二极化上行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000078
Figure PCTCN2017093052-appb-000079
Figure PCTCN2017093052-appb-000080
其中,
Figure PCTCN2017093052-appb-000081
表示与一组模型参数估计值
Figure PCTCN2017093052-appb-000082
对应的第一极化上行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000083
表示与一组模型参数估计值
Figure PCTCN2017093052-appb-000084
对应的第二极化上行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000085
模型参数的最优估计值
Figure PCTCN2017093052-appb-000086
是使得
Figure PCTCN2017093052-appb-000087
最逼近于步骤301中计算获得的真实的
Figure PCTCN2017093052-appb-000088
且使得
Figure PCTCN2017093052-appb-000089
最逼近于步骤301中计算获得的真实的
Figure PCTCN2017093052-appb-000090
所以,对模型参数估计的问题可以转化为如式29所示的优化问题:
Figure PCTCN2017093052-appb-000091
也就是说,在该场景中,模型参数符合如下表达式:
Figure PCTCN2017093052-appb-000092
在式30中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,
Figure PCTCN2017093052-appb-000093
表示第一极化上行信道的频率响应数学模型,
Figure PCTCN2017093052-appb-000094
表示第二极化上行信道的频率响应数学模型,F表示信道的频率响应数学模型,
Figure PCTCN2017093052-appb-000095
表示第一极化上行信道的频率响应,
Figure PCTCN2017093052-appb-000096
表示第二极化上行信道的频率响应。
其中,第一极化模型参数可以包括第一极化对应的各路径的振幅和第一极化对应的各路径的初相,第二极化模型参数可以包括第二极化对应的各路径的振幅和第二极化对应的各路径的初相。
Figure PCTCN2017093052-appb-000097
可以表明,第一极化上行信道的频率响应数学模型为,将各上行子载波频点对应的波长λUL和第一极化模型参数,代入信道的频率响应数学模型后得到的表达式。
Figure PCTCN2017093052-appb-000098
可以表明,第二极化上行信道的频率响应数学模型为,将各上行子载波频点对应的波长λUL和第二极化模型参数代入信道的频率响应数学模型后得到的表达式。
值得强调的是,当接入网设备将式27和式28所示的双极化的优化目标函数,融合为式29所示的优化目标函数来联合优化求解时,由于在双极化情况下,对于噪声等无用信号,在第一极化优化目标函数上是峰时,在第二极化优化目标函数上很可能不是峰,例如可能是谷;对于有用信号,在第一极化优化目标函数上是峰时,在第二极化优化目标函数上也是峰,因而通过将双极化的优化目标函数相加,可以更加突显出真实多径在优化目标函数上形成的峰值,相对抑制噪声等干扰在目标优化函数上形成的伪峰,从而可以降低迭代次数,便于更加高效、准确地确定双极化情况下的模型参数。
上述式29所示的优化问题可以按照下列步骤求解:
(1)、将式22、式23分别写成矩阵形式,记
Figure PCTCN2017093052-appb-000099
Figure PCTCN2017093052-appb-000100
Figure PCTCN2017093052-appb-000101
Figure PCTCN2017093052-appb-000102
Figure PCTCN2017093052-appb-000103
Figure PCTCN2017093052-appb-000104
则式22、式23可以用矩阵表示为
Figure PCTCN2017093052-appb-000105
Figure PCTCN2017093052-appb-000106
进一步,记
Figure PCTCN2017093052-appb-000107
Figure PCTCN2017093052-appb-000108
Figure PCTCN2017093052-appb-000109
联合I个上行子载波频点对应的式37、式38,则全带宽的总的上行信道的频率响应数学模型可以表示为
Figure PCTCN2017093052-appb-000110
Figure PCTCN2017093052-appb-000111
(2)、基于式42和式43表示的矩阵形式,式29所示的优化问题可以表示为
Figure PCTCN2017093052-appb-000112
Figure PCTCN2017093052-appb-000113
固定时,
Figure PCTCN2017093052-appb-000114
的最优化问题即转化为线性规划问题,此时最优解可以表示为
Figure PCTCN2017093052-appb-000115
Figure PCTCN2017093052-appb-000116
其中,
Figure PCTCN2017093052-appb-000117
表示
Figure PCTCN2017093052-appb-000118
的伪逆。
(3)、优化问题式44可以转化为一个只和
Figure PCTCN2017093052-appb-000119
有关,也就是只和
Figure PCTCN2017093052-appb-000120
有关的优化问题,即
Figure PCTCN2017093052-appb-000121
也就是说,通过消元的方式可以将式44中6N维优化问题,转化为式47中的2N维优化问题,这样可以降低计算复杂度,使得计算过程更为简单。
(4)、针对优化问题式47,可以采用单纯形法(例如下山单纯形法Nelder-Mead法)进行搜索,求得最优的
Figure PCTCN2017093052-appb-000122
这里求得的
Figure PCTCN2017093052-appb-000123
即分别为模型参数dn的目标值和θn的目标值。
在上述步骤402中得到最优的
Figure PCTCN2017093052-appb-000124
之后,在步骤3023中,接入网设备可以基于最优的
Figure PCTCN2017093052-appb-000125
通过上述式45、式46计算最优的
Figure PCTCN2017093052-appb-000126
Figure PCTCN2017093052-appb-000127
Figure PCTCN2017093052-appb-000128
这里求得的
Figure PCTCN2017093052-appb-000129
即分别为模型参数
Figure PCTCN2017093052-appb-000130
的目标值、
Figure PCTCN2017093052-appb-000131
的目标值、
Figure PCTCN2017093052-appb-000132
的目标值和
Figure PCTCN2017093052-appb-000133
的目标值。
至此,模型参数dn、θn
Figure PCTCN2017093052-appb-000134
的求解完成。
以上主要是以上述求解模型参数的第一种可能的实现方式中的方式A为例进行说明的,对于上述第一种可能的实现方式中的方式B,与上述单极化场景类似,由于dn的初始值和θn的初始值是在参数空间划分的网格点上遍历搜索目标似然谱的峰值得到的解,并不一定是最优解,即网格点对应的峰值,并不一定是整个目标似然谱的峰值,因而接入网设备还可以在步骤502中通过遍历搜索目标似然谱上初始值附近的峰值,即网格点附近对应的峰值,从而得到dn的目标值和θn的目标值,进而可以通过式45和式46得到
Figure PCTCN2017093052-appb-000135
的目标值、
Figure PCTCN2017093052-appb-000136
的目标值、
Figure PCTCN2017093052-appb-000137
的目标值、
Figure PCTCN2017093052-appb-000138
的目标值。
另外,与上述单极化场景类似,对于上述求解模型参数的第二种可能的实现方式,接入网设备可以不通过目标似然谱求解dn的初始值和θn的初始值,而直接根据式44通过优化算法求解dn的目标值、θn的目标值、
Figure PCTCN2017093052-appb-000139
的目标值、
Figure PCTCN2017093052-appb-000140
的目标值、
Figure PCTCN2017093052-appb-000141
的目标值和
Figure PCTCN2017093052-appb-000142
的目标值。并且,由于该种方式是在整个参数空间中遍历搜索,因而得到的模型参数更为精确。
在得到模型参数dn、θn
Figure PCTCN2017093052-appb-000143
的目标值后,在双极化情况下,接入网设备在步骤303中根据模型参数、信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应可以包括:
3031、接入网设备根据模型参数中的各路径的路程、各路径的到达角、第一极化对应的各路径的振幅、第一极化对应的各路径的初相、信道的频率响应数学模型和各下行子载波频点,构建第一极化下行信道的频率响应。
3032、接入网设备根据模型参数中的各路径的路程、各路径的到达角、第二极化对应的各路径的振幅、第二极化对应的各路径的初相、信道的频率响应数学模型和各下行子载波频点,构建第二极化下行信道的频率响应。
具体的,接入网设备可以构建如下所示的第一极化下行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000144
和第二极化下行信道的频率响应数学模型
Figure PCTCN2017093052-appb-000145
Figure PCTCN2017093052-appb-000146
即为接入网设备构建的第一极化下行信道的频率响应
Figure PCTCN2017093052-appb-000147
Figure PCTCN2017093052-appb-000148
即为接入网设备构建的下行信道的频率响应
Figure PCTCN2017093052-appb-000149
Figure PCTCN2017093052-appb-000150
Figure PCTCN2017093052-appb-000151
在双极化情况下,波束成形的权值包括第一极化权值和第二极化权值,接入网设备在上述步骤304根据下行信道的频率响应,计算各下行子载波频点的波束成形的权值包括:
3041、接入网设备根据第一极化下行信道的频率响应,计算第一极化对应的各下行子载波频点的波束成形的权值。
3042、接入网设备根据第二极化下行信道的频率响应,计算第二极化对应的各下行子载波频点的波束成形的权值。
在步骤304中,接入网设备可以分别基于构建出的第一极化下行信道的频率响应和第二极化下行信道的频率响应,得到式52所示的各下行子载波频点对应的第一极化最佳波束成形的权值,和式53所示的各下行子载波频点对应的第二极化最佳波束成形的权值。
Figure PCTCN2017093052-appb-000152
Figure PCTCN2017093052-appb-000153
在得到波束成形的权值后,接入网设备可以在步骤305中,根据该权值对天线阵列进行下行波束成形,而后进行信号发射。
可见,本申请实施例提供的波束成形方法,可以在双极化场景下,利用双极化特性构建双极化下行信道的频率响应,从而根据双极化下行信道的频率响应计算波束成形的权值,以进行波束成形。
并且,尤其在双极化场景下,与采用其它数学模型相比,由于本申请实施例提供的信道的频率响应数学模型的模型参数在上、下行子载波频点具有互易性,因而使得重构下行信道的过程更为简单。
此外,需要说明的是,上述两个场景中求解获得的信道的频率响应数学模型中的模型参数的值,并 不是信道多径参数的实际值,而是对信道多径参数的估计值。该模型参数以及重构的下行信道的频率响应,除了可以用于进行波束成形外,还可以有多方面的应用,例如:
(1)、目标定位
根据估计的信道多径参数例如时延(即路径的路程)、到达角对目标进行几何反演计算,以获得目标在空间中的具***置。
(2)、上行覆盖增强
根据信道参数估计和信道重构,在上行链路中,可以通过一定带宽的信道频率响应,重构出相邻带宽的信道频率响应,使得可用于发射SRS的上行带宽成倍增加,达到上行覆盖增强的目的。
(3)、信道估计降噪
传统的降噪方案通过截断时延域上的信道响应拖尾的分量来实现。但由于不知道信道具体的多径时延位置,因此在时延域上的截断非常不精确,有可能仍然会留下大部分噪声分量,也有可能会把部分信号也截断掉。而通过信道参数估计则可以在截断前准确知道多径的时延位置,进而准确的去掉噪声分量,保留信号分量,使得降噪效果更明显。
上述主要从各个网元之间交互的角度对本申请实施例提供的方案进行了介绍。可以理解的是,各个网元,例如接入网设备、终端为了实现上述功能,其包含了执行各个功能相应的硬件结构和/或软件模块。本领域技术人员应该很容易意识到,结合本文中所公开的实施例描述的各示例的算法步骤,本申请能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行,取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本申请的范围。
本申请实施例可以根据上述方法示例对接入网设备进行功能模块的划分,例如,可以对应各个功能划分各个功能模块,也可以将两个或两个以上的功能集成在一个处理模块中。上述集成的模块既可以采用硬件的形式实现,也可以采用软件功能模块的形式实现。需要说明的是,本申请实施例中对模块的划分是示意性的,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式。
在采用对应各个功能划分各个功能模块的情况下,图6示出了上述和实施例中涉及的接入网设备的一种可能的组成示意图,如图6所示,该接入网设备可以包括:第一计算单元601、第二计算单元602、构建单元603、第三计算单元604和波束成形单元605。
其中,第一计算单元用于支持接入网设备执行图3所示的波束成形方法中的步骤301。第二计算单元602用于支持接入网设备执行图3中的步骤302,以及前文中的步骤3021、步骤3022、步骤3023、步骤401、步骤402、步骤501和步骤502。构建单元603用于支持接入网设备执行图3所示的波束成形方法中的步骤303,以及前文中的步骤3031和步骤3032。第三计算单元604用于支持接入网设备执行图3所示的波束成形方法中的步骤304,以及前文中的步骤3041和步骤3042。波束成形单元605用于支持接入网设备执行图3所示的波束成形方法中的步骤305。
在本申请实施例中,在另一种模块划分方式中,如图2所示,该接入网设备可以包括:上行探测子***701、基带子***702、中射频子***703、以及天馈子***704。其中,上述第一计算单元601的功能可以通过上行探测子***701实现,第二计算单元602的功能可以通过基带子***702实现,构建单元603的功能可以通过基带子***703实现,第三计算单元604的功能可以通过基带子***702或中射频子***703实现,波束成形单元605的功能可以通过天馈子***704实现。
需要说明的是,上述方法实施例涉及的各步骤的所有相关内容均可以援引到对应功能模块的功能描 述,在此不再赘述。
本申请实施例提供的接入网设备,用于执行上述数据处理方法,因此可以达到与上述数据处理方法相同的效果。
在采用集成的单元的情况下,图7示出了上述实施例中所涉及的接入网设备的另一种可能的组成示意图。如图7所示,该接入网设备包括:处理模块801和通信模块802。
处理模块801用于对接入网设备的动作进行控制管理,例如,处理模块801用于支持接入网设备执行图3、图4和图5中的步骤,和/或用于本文所描述的技术的其它过程。通信模块802用于支持接入网设备与其他网络实体的通信,例如与图1中示出的终端之间的通信。接入网设备还可以包括存储模块803,用于存储接入网设备的程序代码和数据。
其中,处理模块801可以是处理器或控制器。其可以实现或执行结合本申请公开内容所描述的各种示例性的逻辑方框,模块和电路。处理器也可以是实现计算功能的组合,例如包含一个或多个微处理器组合,DSP和微处理器的组合等等。通信模块802可以是收发器、收发电路或通信接口等。存储模块803可以是存储器。
当处理模块801为处理器,通信模块802为通信接口,存储模块803为存储器时,本申请实施例所涉及的接入网设备可以为图8所示的接入网设备。
进一步地,上述图2和图6中的接入网设备是以功能单元的形式来呈现的。这里的“单元”可以指特定应用集成电路(application specific integrated circuit,ASIC),电路,执行一个或多个软件或固件程序的处理器和存储器,集成逻辑电路,和/或其他可以提供上述功能的器件。在一个简单的实施例中,本领域的技术人员可以想到图2和图6中的接入网设备也可以采用图8所示的形式。各单元可以通过图8的处理器和存储器来实现。
如图8所示,接入网设备可以包括一个或多个端口904,与收发器903相耦合。收发器903可以是发射器,接收器或其组合,从其它网元通过端口904发送或接收数据包。处理器901耦合到收发器903,用于处理数据包。处理器901可包含一个或多个多核处理器和/或存储器902。处理器901可以是一个通用处理器,专用集成电路,或数字信号处理器(digital signal processing,DSP)。
存储器902可为非瞬时性的存储介质,与处理器901相耦合,用于保存不同类型的数据。存储器902可包含只读存储器(read only memory,ROM),随机存取存储器(random access memory,RAM)或者可存储信息和指令的其他类型的动态存储设备,也可以是磁盘存储器。
本发明实施例还提供了一种计算机存储介质,用于储存为上述图2、图6、图7或图8所示接入网设备所用的计算机软件指令,其包含用于执行上述方法实施例所设计的程序。通过执行存储的程序,可以实现波束成形。
本申请实施例还提供了一种包含指令的计算机程序产品,当其在计算机上运行时,使得计算机可以执行上述方法实施例所实现的波束成形方法。
通过以上的实施方式的描述,所属领域的技术人员可以清楚地了解到,为描述的方便和简洁,仅以上述各功能模块的划分进行举例说明,实际应用中,可以根据需要而将上述功能分配由不同的功能模块完成,即将装置的内部结构划分成不同的功能模块,以完成以上描述的全部或者部分功能。
在本申请所提供的几个实施例中,应该理解到,所揭露的装置和方法,可以通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如,模块或单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个装置,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过 一些接口,装置或单元的间接耦合或通信连接,可以是电性,机械或其它的形式。
作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是一个物理单元或多个物理单元,即可以位于一个地方,或者也可以分布到多个不同地方。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件功能单元的形式实现。
集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个可读取存储介质中。基于这样的理解,本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来,该软件产品存储在一个存储介质中,包括若干指令用以使得一个设备(可以是单片机,芯片等)或处理器(processor)执行本申请各个实施例方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、ROM、随机存取存储器RAM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述,仅为本发明的具体实施方式,但本发明的保护范围并不局限于此,任何熟悉本技术领域的技术人员在本发明揭露的技术范围内,可轻易想到变化或替换,都应涵盖在本发明的保护范围之内。因此,本发明的保护范围应以所述权利要求的保护范围为准。

Claims (27)

  1. 一种波束成形方法,其特征在于,包括:
    计算上行信道的频率响应;
    根据所述上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数,所述模型参数在上、下行子载波频点具有互易性;
    根据所述模型参数、所述信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应;
    根据所述下行信道的频率响应,计算各下行子载波频点的波束成形的权值;
    根据所述权值对天线阵列进行下行波束成形,所述天线阵列为双极化天线阵列或单极化天线阵列。
  2. 根据权利要求1所述的方法,其特征在于,所述模型参数包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相。
  3. 根据权利要求2所述的方法,其特征在于,所述根据所述上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数包括:
    根据所述上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的目标似然谱;
    根据所述目标似然谱计算所述各路径的目标值和所述各路径的到达角的目标值;
    根据所述各路径的路程的目标值和所述各路径的到达角的目标值,计算所述各路径的振幅的目标值和所述各路径的初相的目标值。
  4. 根据权利要求3所述的方法,其特征在于,所述根据所述目标似然谱计算所述各路径的目标值和所述各路径的到达角的目标值包括:
    根据所述目标似然谱计算所述各路径的路程的初始值和所述各路径的到达角的初始值;
    根据所述各路径的路程的初始值和所述各路径的到达角的初始值,通过优化算法计算各路径的路程的目标值和各路径的到达角的目标值。
  5. 根据权利要求3所述的方法,其特征在于,所述根据所述目标似然谱计算所述各路径的目标值和所述各路径的到达角的目标值包括:
    根据所述目标似然谱计算所述各路径的路程的初始值和所述各路径的到达角的初始值;
    根据所述目标似然谱、所述各路径的路程的初始值和所述各路径的到达角的初始值,通过搜索算法计算各路径的路程的目标值和各路径的到达角的目标值。
  6. 根据权利要求2-5任一项所述的方法,其特征在于,所述信道的频率响应数学模型的表达式为:
    Figure PCTCN2017093052-appb-100001
    其中,F(k,i)表示所述信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距。
  7. 根据权利要求6所述的方法,其特征在于,所述上行信道的频率响应的目标似然谱的表达式为:
    Figure PCTCN2017093052-appb-100002
    其中,Θ(d,θ)表示所述目标似然谱,hUL(k,i)表示上行信道的频率响应,d表示路径的路程,θ表示路径的到达角,λUL,i表示第i个上行子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,|| ||2表示欧几里得范数。
  8. 根据权利要求2-5任一项所述的方法,其特征在于,当所述天线阵列为面阵时,所述信道的频率响应数学模型的表达式为:
    Figure PCTCN2017093052-appb-100003
    其中,F(kH,kV,i)表示所述信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,kH表示天线阵列的行数,kV表示天线阵列的列数,
    Figure PCTCN2017093052-appb-100004
    表示第n条路径的水平角,γn表示第n条路径的俯仰角。
  9. 根据权利要求1-8任一项所述的方法,其特征在于,当所述天线阵列为双极化天线阵列时,所述上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,所述模型参数包括第一极化模型参数和第二极化模型参数,所述模型参数符合如下表达式:
    Figure PCTCN2017093052-appb-100005
    其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,
    Figure PCTCN2017093052-appb-100006
    表示第一极化上行信道的频率响应数学模型,
    Figure PCTCN2017093052-appb-100007
    表示第二极化上行信道的频率响应数学模型,F表示所述信道的频率响应数学模型,
    Figure PCTCN2017093052-appb-100008
    表示第一极化上行信道的频率响应,
    Figure PCTCN2017093052-appb-100009
    表示第二极化上行信道的频率响应,|| ||2表示欧几里得范数。
  10. 根据权利要求3-9任一项所述的方法,其特征在于,当所述天线阵列为双极化天线阵列时,所述上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,所述根据所述上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的目标似然谱包括:
    根据所述第一极化上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的第一极化似然谱;
    根据所述第二极化上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的第二极化似然谱;
    所述第一极化似然谱与所述第二极化似然谱的和即为所述目标似然谱。
  11. 根据权利要求2-10任一项所述的方法,其特征在于,当所述天线阵列为双极化天线阵列时,所述各路径的振幅包括所述第一极化对应的各路径的振幅和所述第二极化对应的各路径的振幅,所述各路径的初相包括所述第一极化对应的各路径的初相和所述第二极化对应的各路径的初相,所述下行信道的频率响应包括第一极化下行信道的频率响应和第二极化下行信道的频率响应,所述根据所述模型参数、所述信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应包括:
    根据所述模型参数中的各路径的路程、各路径的到达角、第一极化对应的各路径的振幅、第一极化对应的各路径的初相、所述信道的频率响应数学模型和所述各下行子载波频点,构建第一极化下行信道的频率响应;
    根据所述模型参数中的各路径的路程、各路径的到达角、第二极化对应的各路径的振幅、第二极化对应的各路径的初相、所述信道的频率响应数学模型和所述各下行子载波频点,构建第二极化下行信道的频率响应。
  12. 根据权利要求11所述的方法,其特征在于,所述权值包括第一极化权值和第二极化权值,所述根据所述下行信道的频率响应,计算各下行子载波频点的波束成形的权值包括:
    根据所述第一极化下行信道的频率响应,计算第一极化对应的各下行子载波频点的波束成形的权值;
    根据所述第二极化下行信道的频率响应,计算第二极化对应的各下行子载波频点的波束成形的权值。
  13. 根据权利要求1-8任一项所述的方法,其特征在于,所述模型参数符合如下表达式:
    Figure PCTCN2017093052-appb-100010
    其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,FUL表示上行信道的频率响应数学模型,F表示所述信道的频率响应数学模型,hUL表示上行信道的频率响应,|| ||2表示欧几里得范数。
  14. 一种接入网设备,其特征在于,包括:
    第一计算单元,用于计算上行信道的频率响应;
    第二计算单元,用于根据所述上行信道的频率响应和各上行子载波频点,计算信道的频率响应数学模型中的模型参数,所述模型参数在上、下行子载波频点具有互易性;
    构建单元,用于根据所述模型参数、所述信道的频率响应数学模型和各下行子载波频点,构建下行信道的频率响应;
    第三计算单元,用于根据所述下行信道的频率响应,计算各下行子载波频点的波束成形的权值;
    波束成形单元,用于根据所述权值对天线阵列进行下行波束成形,所述天线阵列为双极化天线阵列或单极化天线阵列。
  15. 根据权利要求14所述的接入网设备,其特征在于,所述模型参数包括各路径的路程、各路径的到达角、各路径的振幅和各路径的初相。
  16. 根据权利要求15所述的接入网设备,其特征在于,所述第二计算单元具体用于:
    根据所述上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的目标似然谱;
    根据所述目标似然谱计算所述各路径的目标值和所述各路径的到达角的目标值;
    根据所述各路径的路程的目标值和所述各路径的到达角的目标值,计算所述各路径的振幅的目标值和所述各路径的初相的目标值。
  17. 根据权利要求16所述的接入网设备,其特征在于,所述第二计算单元具体用于:
    根据所述目标似然谱计算所述各路径的路程的初始值和所述各路径的到达角的初始值;
    根据所述各路径的路程的初始值和所述各路径的到达角的初始值,通过优化算法计算各路径的路程的目标值和各路径的到达角的目标值。
  18. 根据权利要求16所述的接入网设备,其特征在于,所述第二计算单元具体用于:
    根据所述目标似然谱计算所述各路径的路程的初始值和所述各路径的到达角的初始值;
    根据所述目标似然谱、所述各路径的路程的初始值和所述各路径的到达角的初始值,通过搜索算法计算各路径的路程的目标值和各路径的到达角的目标值。
  19. 根据权利要求15-18任一项所述的接入网设备,其特征在于,所述信道的频率响应数学模型的表达式为:
    Figure PCTCN2017093052-appb-100011
    其中,F(k,i)表示所述信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距。
  20. 根据权利要求19所述的接入网设备,其特征在于,所述上行信道的频率响应的目标似然谱的表达式为:
    Figure PCTCN2017093052-appb-100012
    其中,Θ(d,θ)表示所述目标似然谱,hUL(k,i)表示上行信道的频率响应,d表示路径的路程,θ表示路径的到达角,λUL,i表示第i个上行子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,|| ||2表示欧几里得范数。
  21. 根据权利要求15-18任一项所述的接入网设备,其特征在于,当所述天线阵列为面阵时,所述信道的频率响应数学模型的表达式为:
    Figure PCTCN2017093052-appb-100013
    其中,F(kH,kV,i)表示所述信道的频率响应数学模型,n=1,2,...,N表示路径的编号,N表示路径的数量,dn表示第n个路径的路程,θn表示第n个路径的到达角、an表示第n个路径的振幅、φn表示第n个路径的初相,λi表示第i个子载波频点对应的波长,i=1,2,...,I表示子载波频点的编号,I表示子载波频点的数量,k=1,2,...,K表示阵元的编号,K表阵元的数量,l表示阵元间距,kH表示天线阵列的行数,kV表示天线阵列的列数,
    Figure PCTCN2017093052-appb-100014
    表示第n条路径的水平角,γn表示第n条路径 的俯仰角。
  22. 根据权利要求14-21任一项所述的接入网设备,其特征在于,当所述天线阵列为双极化天线阵列时,所述上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,所述模型参数包括第一极化模型参数和第二极化模型参数,所述模型参数符合如下表达式:
    Figure PCTCN2017093052-appb-100015
    其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,
    Figure PCTCN2017093052-appb-100016
    表示第一极化上行信道的频率响应数学模型,
    Figure PCTCN2017093052-appb-100017
    表示第二极化上行信道的频率响应数学模型,F表示所述信道的频率响应数学模型,
    Figure PCTCN2017093052-appb-100018
    表示第一极化上行信道的频率响应,
    Figure PCTCN2017093052-appb-100019
    表示第二极化上行信道的频率响应,|| ||2表示欧几里得范数。
  23. 根据权利要求16-22任一项所述的接入网设备,其特征在于,当所述天线阵列为双极化天线阵列时,所述上行信道的频率响应包括第一极化上行信道的频率响应和第二极化上行信道的频率响应,所述第二计算单元具体用于:
    根据所述第一极化上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的第一极化似然谱;
    根据所述第二极化上行信道的频率响应和所述各上行子载波频点,构建所述上行信道的频率响应的第二极化似然谱;
    所述第一极化似然谱与所述第二极化似然谱的和即为所述目标似然谱。
  24. 根据权利要求15-23任一项所述的接入网设备,其特征在于,当所述天线阵列为双极化天线阵列时,所述各路径的振幅包括所述第一极化对应的各路径的振幅和所述第二极化对应的各路径的振幅,所述各路径的初相包括所述第一极化对应的各路径的初相和所述第二极化对应的各路径的初相,所述下行信道的频率响应包括第一极化下行信道的频率响应和第二极化下行信道的频率响应,所述构建单元具体用于:
    根据所述模型参数中的各路径的路程、各路径的到达角、第一极化对应的各路径的振幅、第一极化对应的各路径的初相、所述信道的频率响应数学模型和所述各下行子载波频点,构建第一极化下行信道的频率响应;
    根据所述模型参数中的各路径的路程、各路径的到达角、第二极化对应的各路径的振幅、第二极化对应的各路径的初相、所述信道的频率响应数学模型和所述各下行子载波频点,构建第二极化下行信道的频率响应。
  25. 根据权利要求24所述的接入网设备,其特征在于,所述权值包括第一极化权值和第二极化权值,所述第三计算单元具体用于:
    根据所述第一极化下行信道的频率响应,计算第一极化对应的各下行子载波频点的波束成形的权值;
    根据所述第二极化下行信道的频率响应,计算第二极化对应的各下行子载波频点的波束 成形的权值。
  26. 根据权利要求14-21任一项所述的接入网设备,其特征在于,所述模型参数符合如下表达式:
    Figure PCTCN2017093052-appb-100020
    其中,argmin表示求解使目标函数取得最小值时的变量值,i表示子载波频点的编号,k表示阵元的编号,λ表示子载波频点对应的波长,λUL表示上行子载波频点对应的波长,FUL表示上行信道的频率响应数学模型,F表示所述信道的频率响应数学模型,hUL表示上行信道的频率响应,|| ||2表示欧几里得范数。
  27. 一种接入网设备,其特征在于,包括:处理器、存储器、总线和通信接口;
    所述存储器用于存储计算机执行指令,所述处理器与所述存储器通过所述总线连接,当所述接入网设备运行时,所述处理器执行所述存储器存储的所述计算机执行指令,以使所述接入网设备执行如权利要求1-13任意一项所述的波束成形方法。
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US10686619B2 (en) 2018-10-15 2020-06-16 Avista Corporation Wireless broadband meter collar
US11863246B2 (en) 2020-03-18 2024-01-02 Avista Edge, Inc. Achieving polarization diversity and directionality using predetermined phases and amplitude
US20210392689A1 (en) * 2020-06-12 2021-12-16 Ahmad Jalali Signaling and procedures for idle mode beam tracking for mu mimo systems
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101626265A (zh) * 2008-07-10 2010-01-13 中兴通讯股份有限公司 一种无线通信***中实现下行波束赋形的方法
CN103905345A (zh) * 2012-12-27 2014-07-02 华为技术有限公司 通道校正装置、方法及***
CN104052691A (zh) * 2014-07-02 2014-09-17 东南大学 基于压缩感知的mimo-ofdm***信道估计方法
US20170019154A1 (en) * 2015-07-16 2017-01-19 Spirent Communications, Inc. Massive mimo array emulation
WO2017083000A1 (en) * 2015-11-10 2017-05-18 Qualcomm Incorporated Uplink channel information

Family Cites Families (44)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6266633B1 (en) * 1998-12-22 2001-07-24 Itt Manufacturing Enterprises Noise suppression and channel equalization preprocessor for speech and speaker recognizers: method and apparatus
US7248841B2 (en) * 2000-06-13 2007-07-24 Agee Brian G Method and apparatus for optimization of wireless multipoint electromagnetic communication networks
US7574214B2 (en) * 2005-05-25 2009-08-11 Intel Corporation Device, system and method of multiple access transmission
US7778211B2 (en) * 2006-09-26 2010-08-17 Cisco Technology, Inc. Method for computing a downlink beamforming weighting vector based on up link channel information
US20080192811A1 (en) * 2007-02-09 2008-08-14 Nokia Corporation Beamforming methods and apparatus
CN101364828A (zh) * 2007-08-09 2009-02-11 中兴通讯股份有限公司 一种下行波束形成方法
US8085653B2 (en) * 2007-09-08 2011-12-27 Intel Corporation Beamforming with nulling techniques for wireless communications networks
CN101409577B (zh) * 2007-10-10 2012-03-21 北京信威通信技术股份有限公司 一种基于码扩正交频分多址(cs-ofdma)的智能天线无线***
CN101447854B (zh) * 2007-11-27 2012-11-07 上海华为技术有限公司 数据发送/转发/处理方法及装置
CN101465683B (zh) * 2007-12-18 2012-10-10 中兴通讯股份有限公司 基于双极化天线的上行接收方法及下行发射方法
US8150399B2 (en) * 2007-12-21 2012-04-03 Intel Corporation Techniques for wireless communications networks employing beamforming
US9467210B2 (en) * 2009-04-28 2016-10-11 Telefonaktiebolaget Lm Ericsson (Publ) Transmission parameter adaptation in cooperative signal communication
CN102045097A (zh) * 2009-10-13 2011-05-04 鼎桥通信技术有限公司 一种用户终端高速移动时的下行波束赋形方法和装置
WO2011091586A1 (zh) * 2010-01-27 2011-08-04 中兴通讯股份有限公司 多输入多输出波束赋形数据发送方法和装置
US8559294B2 (en) * 2010-07-29 2013-10-15 Motorola Mobility Llc Method and apparatus for major group scheduling in a fixed beam communication system
CN102547953B (zh) * 2010-12-09 2014-07-23 普天信息技术研究院有限公司 一种获得波束赋形增益的方法
WO2013063424A1 (en) * 2011-10-27 2013-05-02 Comtech Ef Data Corp. Es/no based carrier-in-carrier rf power control
US8990194B2 (en) * 2012-11-02 2015-03-24 Google Inc. Adjusting content delivery based on user submissions of photographs
US8976884B2 (en) * 2012-12-20 2015-03-10 Google Technology Holdings LLC Method and apparatus for antenna array channel feedback
US8942302B2 (en) * 2012-12-20 2015-01-27 Google Technology Holdings LLC Method and apparatus for antenna array channel feedback
US8971437B2 (en) * 2012-12-20 2015-03-03 Google Technology Holdings LLC Method and apparatus for antenna array channel feedback
WO2014101170A1 (zh) * 2012-12-31 2014-07-03 上海贝尔股份有限公司 Fdd***中信道互易性补偿方法和装置
US9402191B2 (en) * 2013-04-15 2016-07-26 Alcatel Lucent Dual-tier wireless communication system
KR102085003B1 (ko) * 2013-04-30 2020-04-14 삼성전자주식회사 빔포밍 시스템에서 최적의 송수신 빔 제공 방법 및 장치
CN203775416U (zh) * 2014-03-26 2014-08-13 华为技术有限公司 基站
US9294171B2 (en) * 2014-03-26 2016-03-22 Alcatel Lucent Base station calibration
EP2945307A1 (en) * 2014-05-12 2015-11-18 Telefonica S.A. Method and transmitter for channel coding and modulation in the frequency domain of Orthogonal Frequency-Division Multiplexing wireless networks
CN105356924B (zh) 2014-08-21 2019-05-10 中兴通讯股份有限公司 双极化天线***doa-bf权值估计方法和装置
EP3038270B1 (en) * 2014-12-23 2017-07-19 Telefonica, S.A. Method for performing multiple access in wireless OFDM cellular systems over multipath wireless channels considering both space and frequency domains, base station and computer programs thereof
WO2016114548A1 (en) * 2015-01-12 2016-07-21 Samsung Electronics Co., Ltd. Signal transmission and receiving method, system and apparatus based on filter bank
WO2016123588A1 (en) * 2015-01-30 2016-08-04 Scientific Drilling International, Inc. Dual mode telemetry
KR102289946B1 (ko) * 2015-04-10 2021-08-13 한국전자통신연구원 편파 빔형성 통신 방법 및 장치
US9948354B2 (en) * 2015-04-28 2018-04-17 At&T Intellectual Property I, L.P. Magnetic coupling device with reflective plate and methods for use therewith
US10154493B2 (en) * 2015-06-03 2018-12-11 At&T Intellectual Property I, L.P. Network termination and methods for use therewith
US10103801B2 (en) * 2015-06-03 2018-10-16 At&T Intellectual Property I, L.P. Host node device and methods for use therewith
US10348391B2 (en) * 2015-06-03 2019-07-09 At&T Intellectual Property I, L.P. Client node device with frequency conversion and methods for use therewith
US10142086B2 (en) * 2015-06-11 2018-11-27 At&T Intellectual Property I, L.P. Repeater and methods for use therewith
WO2017025116A1 (en) 2015-08-07 2017-02-16 Huawei Technologies Co., Ltd. Analog beamforming devices
US10079661B2 (en) * 2015-09-16 2018-09-18 At&T Intellectual Property I, L.P. Method and apparatus for use with a radio distributed antenna system having a clock reference
US10136434B2 (en) * 2015-09-16 2018-11-20 At&T Intellectual Property I, L.P. Method and apparatus for use with a radio distributed antenna system having an ultra-wideband control channel
US10009063B2 (en) * 2015-09-16 2018-06-26 At&T Intellectual Property I, L.P. Method and apparatus for use with a radio distributed antenna system having an out-of-band reference signal
US9705571B2 (en) * 2015-09-16 2017-07-11 At&T Intellectual Property I, L.P. Method and apparatus for use with a radio distributed antenna system
US10051629B2 (en) * 2015-09-16 2018-08-14 At&T Intellectual Property I, L.P. Method and apparatus for use with a radio distributed antenna system having an in-band reference signal
CN110870216B (zh) * 2017-07-14 2021-06-15 华为技术有限公司 一种波束成形方法及设备

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101626265A (zh) * 2008-07-10 2010-01-13 中兴通讯股份有限公司 一种无线通信***中实现下行波束赋形的方法
CN103905345A (zh) * 2012-12-27 2014-07-02 华为技术有限公司 通道校正装置、方法及***
CN104052691A (zh) * 2014-07-02 2014-09-17 东南大学 基于压缩感知的mimo-ofdm***信道估计方法
US20170019154A1 (en) * 2015-07-16 2017-01-19 Spirent Communications, Inc. Massive mimo array emulation
WO2017083000A1 (en) * 2015-11-10 2017-05-18 Qualcomm Incorporated Uplink channel information

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3648364A4 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11265054B2 (en) * 2017-07-14 2022-03-01 Huawei Technologies Co., Ltd. Beamforming method and device

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EP3648364A4 (en) 2020-06-10
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