CN112311703A - Channel estimation method, device, readable medium and system thereof - Google Patents
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Abstract
The application relates to the technical field of wireless communication, and discloses a channel estimation method, which comprises the following steps: acquiring a reference symbol in a received signal; performing channel estimation on the received signal based on the acquired reference symbol by using a pilot frequency auxiliary channel estimation technology to obtain a first channel estimation result of the signal; performing equalization demodulation on the signal based on the first channel estimation result; adopting a decision-directed channel estimation technology to carry out channel estimation on the demodulated signal to obtain a second channel estimation result of the signal; generating a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result. The channel estimation method disclosed by the application can effectively avoid the defects of the single use of a channel estimation method, is beneficial to obtaining a quick and accurate channel estimation result, and further improves the wireless communication quality.
Description
Technical Field
The present invention relates to the field of wireless communication technologies, and in particular, to a method, an apparatus, a readable medium, and a system for estimating a channel of an orthogonal frequency division multiplexing system according to the technical specification of the ieee802.11ah protocol.
Background
With the booming of the internet of things in recent years, more and more wireless communication technologies are applied to various applications of the internet of things. Aiming at the defects of insufficient signal range coverage, high equipment power consumption, relatively higher cost, insufficient accessed equipment nodes, poor network security and the like in the application of the traditional Wi-Fi technologies such as 802.11n/ac and the like in the Internet of things. The IEEE (institute of electrical and electronics engineers) introduced the 802.11ah specification in 2016. The technology makes up the gap of the existing Wi-Fi technology in the aspect of application of the Internet of things from the aspects of safety, power consumption, cost, transmission distance, networking capability and the like, and meanwhile, the inherent advantages of Wi-Fi are kept.
The 802.11ah physical layer uses Orthogonal Frequency Division Multiplexing (OFDM) technology. It is a special multi-carrier transmission technology, and can well resist frequency selective attenuation and narrow-band interference. Since the 802.11ah receiver needs to operate in a low signal-to-noise ratio range, it is very important to achieve accurate channel estimation. Particularly, under the background that high-speed rails, light rails and motor cars are increasingly popularized at present, the time-varying property of a channel is more obvious, and the channel characteristics must be estimated and tracked when a receiving end needs to obtain channel state information in time. Therefore, a high-precision channel estimation method is of great significance for realizing reliable wireless communication.
At present, channel estimation methods can be mainly classified into a decision-directed channel estimation method, a pilot-assisted channel estimation method, and a blind channel estimation method. The decision-directed channel estimation method does not need reference training or pilot symbols, and the main process for realizing channel estimation comprises the following steps: after the data signal of the sending end reaches the receiving end and is processed by fast Fourier transform, the data signal is calculated by the channel estimation of the previous symbol to obtain the data symbol compensated by the equalization module, and the value after hard decision is obtained by the demodulation module. And after recalculating the feedback information used for obtaining the current channel estimation and the current OFDM data symbol, obtaining the channel state estimation of the current data symbol. The pilot frequency auxiliary channel estimation method is characterized in that training or pilot frequency information is inserted into a sending signal, channel information of a pilot frequency position is obtained at a receiving end through a corresponding implementation criterion, then, some interpolation algorithms are carried out on the channel information of the pilot frequency position to fit channel response of a data position, and further, a total channel information estimation value is obtained.
Disclosure of Invention
The channel estimation method provided by the application can effectively avoid the defects of independently using one channel estimation method by comprehensively using the channel estimation methods based on different principles, is beneficial to optimizing the traditional channel estimation method, and further provides a basis for quick and accurate wireless communication.
To solve the above technical problem, an aspect of the present application discloses a channel estimation method, including: acquiring a reference symbol in a received signal; performing channel estimation on the received signal based on the acquired reference symbol by using a pilot frequency auxiliary channel estimation technology to obtain a first channel estimation result of the signal; performing equalization demodulation on the signal based on the first channel estimation result; performing channel estimation on the signal after equalization demodulation by adopting a decision-directed channel estimation technology to obtain a second channel estimation result of the signal; generating a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result.
Another aspect of the present application discloses a channel estimation apparatus, including: a channel estimation module, configured to acquire a reference symbol in a received signal, and perform channel estimation on the received signal based on the acquired reference symbol to obtain a first channel estimation result of the signal by using a pilot-assisted channel estimation technique, and perform channel estimation on the signal after equalization demodulation by an equalization demodulation module by using a decision-directed channel estimation technique to obtain a second channel estimation result of the signal, and generate a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result; and the equalization demodulation module is used for carrying out equalization demodulation on the signal based on the first channel estimation result.
Another aspect of the present application discloses a machine-readable medium having stored thereon instructions, which when executed on a machine, cause the machine to perform the data processing method for channel estimation disclosed herein.
Another aspect of the present application discloses a system comprising: a memory to store instructions for execution by one or more processors of a system; and a processor, which is one of the processors of the system, for performing the data processing method for channel estimation disclosed herein.
Drawings
The present application is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
fig. 1 is a schematic diagram illustrating a system for channel estimation, according to some embodiments of the present application;
fig. 2 is a block diagram illustrating an apparatus for channel estimation according to some embodiments of the present application;
fig. 3 is a flow diagram illustrating a method of channel estimation according to some embodiments of the present application;
fig. 4 is a flow diagram illustrating a method of channel estimation according to some embodiments of the present application;
fig. 5 is a flow diagram illustrating a method of channel estimation according to some embodiments of the present application;
FIG. 6 is a schematic diagram illustrating a computer system for channel estimation, according to some embodiments of the present application;
fig. 7 is a schematic diagram illustrating an SoC system for channel estimation, in accordance with some embodiments of the present application;
fig. 8 is a schematic diagram illustrating the S1G _ SHORT format in a Physical layer Data Unit (PPDU) defined by a Protocol 802.11ah, according to some embodiments of the present application.
Detailed Description
The illustrative embodiments of the present application include, but are not limited to, a method of channel estimation.
Various aspects of the illustrative embodiments will be described using terms commonly employed by those skilled in the art to convey the substance of their work to others skilled in the art. It will be apparent, however, to one skilled in the art that some alternative embodiments may be practiced using portions of the described aspects. For purposes of explanation, specific numbers, materials and configurations are set forth in order to provide a thorough understanding of the illustrative embodiments. It will be apparent, however, to one skilled in the art that alternative embodiments may be practiced without the specific details. In other instances, well-known features are omitted or simplified in order not to obscure the illustrative embodiments.
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings. Specifically, based on a specific implementation manner of a Physical layer defined by the 802.11ah Protocol, S1G _ SHORT in one of three Physical layer Data Unit (PPDU) formats is taken as an example for explanation, and it is understood that the present application is also applicable to other formats in the Protocol, for example: S1G _ LONG or S1G _ 1M.
Fig. 1 schematically illustrates a computing system 100 for channel estimation according to an embodiment of the application. Computing system 100 includes memory 102, processor 103, network interface 104, and bus 101. The memory 102, processor 103, and network interface 104 are interconnected via a bus 101.
The network interface 104 may include a wireless signal transceiver for implementing the channel estimation methods disclosed herein for providing a radio interface for the computing system 100 to communicate with any other suitable device (e.g., front end module, antenna, etc.) over one or more networks. In various embodiments, the network interface 104 may be integrated with other components of the computing system 100. For example, the network interface may include processors of the processor 103, memories of the memory 102, and/or firmware devices (not shown) having instructions that, when executed by at least one of the processors 103, cause the computing system 100 to implement the channel estimation method as disclosed herein.
The network interface 104 may further include any suitable hardware and/or firmware to provide a multiple-input multiple-output radio interface. For example, network interface 104 for one embodiment may be a network adapter, a wireless network adapter, a telephone modem, and/or a wireless modem.
Fig. 2 is a schematic diagram illustrating a wireless signal transceiver that may be used in the computing system 100 shown in fig. 1. According to some embodiments of the present application, the signal transceiver comprises: a signal receiving module 201, a channel estimation module 202, a signal equalization module 203 and a signal demodulation module 204.
According to some embodiments of the present application, in the process of wireless communication, the signal receiving module 201 first receives a wireless signal and processes the received signal to extract a training symbol located in a long training field of a signal data structure and a pilot symbol located in a signal field (a second field in a data unit of an S1G _ SHORT type in an 802.11ah protocol) respectively. Fig. 8 shows a Data format of S1G _ SHORT, which can be specifically divided into a long training field (LTF1), a signal field (SIG), and a Data field (Data). Where the long training field includes 2 LTS symbols. While in other data formats, such as S1G _1M, where the long training field includes 4 LTS symbols. Specifically, the processing of the received signal by the signal receiving module 201 mainly includes timing synchronization, Carrier Frequency Offset (CFO) correction, etc. to ensure correct fast fourier transform operation, because the phase and amplitude of the signal are changed due to signal attenuation, multipath channel delay, and doppler shift during transmission, and it is necessary for the signal receiving module 201 to recover the transmitted data first.
The channel estimation module 202 uses the reference symbols in the long training field and the signal field of the signal data structure sent by the signal receiving module 201 as references, and performs channel estimation by using a pilot-assisted channel estimation technique to obtain two channel estimation results. Subsequently, the channel estimation module 202 performs an average calculation on the two obtained channel estimation results to obtain a first channel estimation result and sends a related channel estimation result parameter to the signal equalization module 203. It should be understood that the reference symbols are only schematically illustrated and not limited in the long training field and the signal field, respectively. In other embodiments, the reference symbols may be located only in the long training field, in which case signal receiving module 201 extracts the training symbols in the long training field and sends the training symbols to channel estimation module 202. Subsequently, the channel estimation module 202 performs channel estimation by using a pilot-assisted channel estimation technique, so as to obtain a first channel estimation result; similarly, the reference symbols may be located only in the signal domain, in which case the signal receiving module 201 extracts the pilot symbols in the signal domain and sends the pilot symbols to the channel estimation module 202. Then, the channel estimation module 202 performs channel estimation by using a pilot-assisted channel estimation technique to obtain a first channel estimation result.
The signal equalization module 203 performs equalization processing on the signal from the signal receiving module 201 according to the parameters of the channel estimation result provided by the channel estimation module 202, specifically including adjusting and compensating for differences of phase rotation and frequency attenuation caused by the channel. Subsequently, the signal equalization module 203 sends the compensated signal to the signal demodulation module 204. The signal demodulation module 204 demodulates the signal equalized by the signal equalization module 203 to obtain each demodulated subcarrier.
In order to reduce the performance degradation of the communication system caused by the error of the detected symbol in the signal transmission process, each demodulated subcarrier needs to be preprocessed. For example, the triangular weighted moving average method may be used to perform the smoothing filtering process on each subcarrier demodulated by the signal demodulation module 204, and specifically, the case of N subcarriers is taken as an example, the smoothing filtering process is applied to each subcarrier and its adjacent subcarriersThe triangle weights are respectively: (N-1)/2.. 2, 1. according to the selected smooth value symmetry interval w, the K-th subcarrier of the N subcarriers is subjected to the smoothed frequency domain value S'kCan be calculated by the following formula: s'k＝1/sum(w)*w*[Sk-i…Sk-1SkSk-1…Sk+i]′
In the formula, sum (w) is the sum of triangular weights of subcarriers, wiIs the ith triangle weight value in the w interval, SkIs the frequency-domain value of the kth subcarrier before smoothing.
Next, based on each preprocessed subcarrier, the channel estimation module 202 performs channel estimation by using a decision-directed channel estimation technique to obtain a second channel estimation result. Subsequently, the channel estimation module 202 calculates a third channel estimation result based on the first channel estimation result obtained by using the pilot-assisted channel estimation method and the second channel estimation result obtained by using the decision-directed channel estimation method according to the following formula:
Hk＝αHDDCE,k+(1－α)Hpilot,k
wherein HkRepresents the third channel estimation result, HDDCE,kRepresents the second channel estimation result, Hpilot,kRepresenting the first channel estimation result and alpha representing the weighting factor.
It is worth noting that the value of the weighting factor α is greater than 0 and smaller than 1, the weighting factor can be adjusted according to the magnitude of the doppler frequency, and when the doppler frequency is higher, the value of the weighting factor α can be adjusted to be smaller; when the Doppler frequency is low, the value of the weighting factor alpha can be adjusted to be larger, and the influence of the Doppler effect on the accuracy of the channel estimation result can be effectively reduced by adjusting the weighting factor alpha in a targeted manner according to the severity of the Doppler frequency shift. In addition, under the condition that the channel attenuation is serious, the proportion occupied by the decision-directed channel estimation is smaller, so the value of the weighting factor alpha should be properly adjusted smaller, and the result of the channel estimation is more accurate. On the contrary, under the condition that the channel attenuation is not obvious, the proportion occupied by the decision-directed channel estimation is relatively large, so the value of the weighting factor alpha should be properly increased to enable the result of the channel estimation to be more accurate.
Fig. 3 schematically illustrates a flow diagram of a channel estimation method according to some embodiments of the present application, which in some embodiments may be implemented by a component described throughout this application (e.g., the signal transceiver of fig. 2/the channel estimation computing system of fig. 1), the channel estimation method specifically including:
1) reference symbols in a received signal are acquired (301). The reference symbols in this embodiment include training symbols inserted into a long training field of a signal data unit in advance at a wireless signal transmitting end according to the prior art, and are used for channel estimation at a receiving end.
2) A pilot-assisted channel estimation technique is used, and channel estimation is performed on a received signal based on training symbols in a long training field to obtain a first channel estimation result (302) of the signal. This step uses existing pilot-assisted channel estimation techniques for channel estimation.
3) Performing equalization demodulation (303) on the signal based on the first channel estimation result;
4) and performing channel estimation on the demodulated signal by adopting a decision-directed channel estimation technology to obtain a second channel estimation result (304) of the signal. The decision-directed channel estimation technique adopted in this step performs channel estimation on the demodulated signal, and the second channel estimation result of the signal can also be achieved by the prior art. It should be noted that any error in the signal is easily propagated in the decision-making process, which in turn reduces the performance of the overall system. Therefore, in this embodiment, before adopting the decision-directed channel estimation technique, a triangular weighted moving average algorithm is first adopted to perform smoothing filtering processing on each subcarrier in the demodulated signal, so as to obtain each smoothed subcarrier.
5) A third channel estimation result of the signal is generated based on the first channel estimation result and the second channel estimation result (305). In this step, based on the first channel estimation result obtained in step 302 and the second channel estimation result obtained in step 304, a third channel estimation result is calculated by the following formula:
Hk＝αHDDCE,k+(1－α)Hpilot,k
wherein HkRepresents the third channel estimation result, HDDCE,kRepresents the second channel estimation result, Hpilot,kRepresenting the first channel estimation result and alpha representing the weighting factor. It is worth noting that the value of the weighting factor α is greater than 0 and smaller than 1, and the weighting factor can be adjusted according to the magnitude of the doppler frequency, so that the channel estimation result is more accurate.
Fig. 4 schematically illustrates a flow chart of a channel estimation method according to further embodiments of the present application, which in some embodiments may be implemented by a component described throughout this application (e.g., the signal transceiver of fig. 2/the channel estimation computing system of fig. 1), the channel estimation method specifically including the steps of:
1) reference symbols in a received signal are acquired (401). The reference symbols in this embodiment include pilot symbols inserted in the signal field of the signal data unit in advance at the wireless signal transmitting end according to the prior art, and are used for channel estimation at the receiving end.
2) A first channel estimation result of the signal is obtained (402) by performing channel estimation on the received signal based on pilot symbols in a signal domain using a pilot-assisted channel estimation technique. This step uses existing pilot-assisted channel estimation techniques for channel estimation.
3) Based on the first channel estimation result, the signal is equalized and demodulated (403).
4) And performing channel estimation on the demodulated signal by adopting a decision-directed channel estimation technology to obtain a second channel estimation result (404) of the signal. The decision-directed channel estimation technique adopted in this step performs channel estimation on the demodulated signal, and the second channel estimation result of the signal can also be achieved by the prior art. It should be noted that any error in the signal is easily propagated in the decision-making process, which in turn reduces the performance of the overall system. Therefore, in this embodiment, before adopting the decision-directed channel estimation technique, a triangular weighted moving average algorithm is first adopted to perform smoothing filtering processing on each subcarrier in the demodulated signal, so as to obtain each smoothed subcarrier.
5) A third channel estimation result of the signal is generated based on the first channel estimation result and the second channel estimation result (405). In this step, based on the first channel estimation result obtained in step 402 and the second channel estimation result obtained in step 404, a third channel estimation result is calculated by the following formula:
Hk＝αHDDCE,k+(1－α)Hpilot,k
wherein HkRepresents the third channel estimation result, HDDCE,kRepresents the second channel estimation result, Hpilot,kRepresenting the first channel estimation result and alpha representing the weighting factor. It is worth noting that the value of the weighting factor α is greater than 0 and smaller than 1, and the weighting factor can be adjusted according to the magnitude of the doppler frequency, so that the channel estimation result is more accurate.
Fig. 5 schematically illustrates a flow chart of a channel estimation method according to further embodiments of the present application, which in some embodiments may be implemented by a component described throughout this application (e.g., the signal transceiver of fig. 2/the channel estimation computing system of fig. 1), the channel estimation method specifically including the steps of:
1) reference symbols in a received signal are acquired (501). The reference symbols in this embodiment include training symbols in a signal data unit long training field and pilot symbols in a signal field, which are inserted in advance at a wireless signal transmitting end according to the prior art, and are used for channel estimation at a receiving end.
2) And performing channel estimation based on the training symbols in the long training domain and the pilot symbols in the signal domain respectively by adopting a pilot frequency auxiliary channel estimation technology, and averaging parameters in the two obtained channel estimation results to obtain a first channel estimation result (502). This step uses existing pilot-assisted channel estimation techniques for channel estimation.
3) Based on the first channel estimation result, the signal is equalized and demodulated (503).
4) And performing channel estimation on the demodulated signal by adopting a decision-directed channel estimation technology to obtain a second channel estimation result (504) of the signal. The decision-directed channel estimation technique adopted in the step performs channel estimation on the demodulated signal, and the second channel estimation result of the signal can also be obtained by the prior art. It should be noted that any error in the signal is easily propagated in the decision-making process, which in turn reduces the performance of the overall system. Therefore, in this embodiment, before adopting the decision-directed channel estimation technique, a triangular weighted moving average algorithm is first adopted to perform smoothing filtering processing on each subcarrier in the demodulated signal, so as to obtain each smoothed subcarrier.
5) A third channel estimation result of the signal is generated based on the first channel estimation result and the second channel estimation result (505). In this step, based on the first channel estimation result obtained in step 502 and the second channel estimation result obtained in step 504, a third channel estimation result is calculated by the following formula:
Hk＝αHDDCE,k+(1－α)Hpilot,k
wherein HkRepresents the third channel estimation result, HDDCE,kRepresents the second channel estimation result, Hpilot,kRepresenting the first channel estimation result and alpha representing the weighting factor. It is worth noting that the value of the weighting factor α is greater than 0 and smaller than 1, and the weighting factor can be adjusted according to the magnitude of the doppler frequency, so that the channel estimation result is more accurate.
Fig. 6 schematically illustrates an example system 600 in accordance with various embodiments of the present application. In one embodiment, system 600 may include one or more processors 602, system control logic 604 coupled to at least one of processors 602, system memory 606 coupled to system control logic 604, non-volatile memory (NVM) memory 607 coupled to system control logic 604, and network interface 606 coupled to system control logic 604.
NVM/memory 607 may include one or more tangible, non-transitory computer-readable media for storing data and/or instructions. For example, NVM/memory 607 may include any suitable non-volatile memory, such as flash memory, and/or any suitable non-volatile storage device, such as one or more hard disk drives (hdd (s)), one or more Compact Disc (CD) drives, and/or one or more Digital Versatile Disc (DVD) drives.
NVM/memory 607 may comprise a portion of a storage resource on the device on which system 600 is installed or it may be accessible by, but not necessarily a part of, a device. For example, NVM/storage 607 may be accessed over a network via network interface 606.
In particular, system memory 606 and NVM/memory 607 may each include: temporary and permanent copies of instructions 603. The instructions 603 may include: instructions that when executed by at least one of processors 602 cause system 600 to implement the channel estimation methods disclosed herein. In various embodiments, the instructions 603 or hardware, firmware, and/or software components thereof may additionally/alternatively be disposed in the system control logic 604, the network interface 606, and/or the processor 602.
The network interface 606 may include the transceiver 206 of the eNB101, the transceiver 202 of the RAN controller 102, and/or other components as shown in fig. 2 to provide a radio interface for the system 600 to communicate with any other suitable devices (e.g., front end modules, antennas, etc.) over one or more networks. In various embodiments, the network interface 606 may be integrated with other components of the system 600. For example, the network interface may include a processor of processor 602, a memory of system memory 606, a NVM/storage of NVM/storage 607, and/or a firmware device (not shown) having instructions that, when executed by at least one of processors 602, cause system 600 to implement the channel estimation methods disclosed herein.
The network interface 606 may further include any suitable hardware and/or firmware to provide a multiple-input multiple-output radio interface. For example, network interface 606 for certain embodiments may be a network adapter, a wireless network adapter, a telephone modem, and/or a wireless modem.
For one embodiment, at least one of the processors 602 may be packaged together with logic for one or more controllers of system control logic 604. For one embodiment, at least one of the processors 602 may be packaged together with logic for one or more controllers of system control logic 604 to form a System In Package (SiP). For one embodiment, at least one of processors 602 may be integrated on the same die with logic for one or more controllers of system control logic 604. For one embodiment, at least one of the processors 504 may be integrated on the same die with logic for one or more controllers of system control logic 604 to form a system on a chip (SoC).
The system 600 may further include: input/output (I/O) devices 605. I/O device 605 may include a user interface designed to enable a user to interact with system 600; the design of the peripheral component interface enables peripheral components to also interact with the system 600; and/or sensors are designed to determine environmental conditions and/or location information associated with system 600.
In various embodiments, the user interface may include, but is not limited to, a display (e.g., a liquid crystal display, a touch screen display, etc.), a speaker, a microphone, one or more cameras (e.g., still images) cameras and/or video cameras, a flashlight (e.g., a light emitting diode flash), and a keyboard.
Fig. 7 is a schematic diagram of a SoC700 system according to an embodiment of the present application. Wherein the dashed box is an optional feature of more advanced socs. In FIG. 7, interconnect unit 705 is coupled to application processor 701, which includes, but is not limited to, a set of one or more core units and shared cache units and registers; a system agent unit 707; a bus controller unit 708; an integrated memory controller unit 704; a set or one or more coprocessors 702 which may include integrated graphics logic, an image processor, an audio processor, and a video processor; a Static Random Access Memory (SRAM) unit 703; a Direct Memory Access (DMA) unit 706. In one embodiment, coprocessor 702 comprises a special-purpose processor, such as, for example, a network or communication processor, compression engine, GPGPU, a high-throughput MIC processor, embedded processor, or the like.
As used herein, the term module or unit may refer to or include an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and/or memory (shared, dedicated, or group) that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality, or may be part of an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and/or memory (shared, dedicated, or group) that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.
In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried by or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed via a network or via other computer readable media. Thus, a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), including, but not limited to, floppy diskettes, optical disks, read-only memories (CD-ROMs), magneto-optical disks, read-only memories (ROMs), Random Access Memories (RAMs), erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, flash memory, or a tangible machine-readable memory for transmitting information (e.g., carrier waves, infrared digital signals, etc.) using the internet in an electrical, optical, acoustical or other form of propagated signal. Thus, a machine-readable medium includes any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).
The present application also discloses some embodiments, in particular:
acquiring a reference symbol in a received signal;
performing channel estimation on the received signal based on the acquired reference symbol by using a pilot frequency auxiliary channel estimation technology to obtain a first channel estimation result of the signal;
performing equalization demodulation on the signal based on the first channel estimation result;
adopting a decision-directed channel estimation technology to carry out channel estimation on the demodulated signal to obtain a second channel estimation result of the signal;
generating a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result.
Embodiment 3 may include the method of embodiment 1, the reference symbols comprising pilot symbols located in a signal domain of a data unit of the signal.
Embodiment 4 may include the method of embodiment 1, the reference symbols comprising training symbols located in a long training field and pilot symbols located in a signal field of a data unit of the signal.
Embodiment 5 may include the method of any one of embodiments 1 and 4, wherein the performing channel estimation on the received signal based on the acquired reference symbols using a pilot-assisted channel estimation technique comprises:
and performing channel estimation based on the training symbols in the long training domain and the pilot symbols in the signal domain respectively by adopting a pilot frequency auxiliary channel estimation technology, and averaging parameters in the two obtained channel estimation results to obtain the first channel estimation result.
Embodiment 6 may include the method of any one of embodiments 1 to 5, wherein the performing channel estimation on the demodulated signal by using a decision-directed channel estimation technique to obtain the second channel estimation result of the signal includes:
smoothing each subcarrier in the demodulated signal;
and performing channel estimation on each smoothed subcarrier by adopting a decision-directed channel estimation technology to obtain a second channel estimation result of the signal.
Embodiment 7 may include the method of any one of embodiments 1 to 6, wherein the smoothing of each subcarrier in the demodulated signal includes:
and smoothing each subcarrier in the demodulated signal by adopting a triangular weighted moving average algorithm.
Embodiment 8 may include the method of any of embodiments 1 to 7, wherein generating a third channel estimation result for the signal based on the first and second channel estimation results comprises:
calculating the third channel estimation result by the following formula:
Hk＝αHDDCE,k+(1－α)Hpilot,k
wherein HkRepresents the third channel estimation result, HDDCE,kRepresents the second channel estimation result, Hpilot,kRepresenting the first channel estimation result and alpha representing the weighting factor.
Embodiment 9 may include the method of any one of embodiments 1 to 8, where the weighting factor α is greater than 0 and smaller than 1 according to the doppler effect and the channel attenuation.
Embodiment 10 may include a channel estimation apparatus comprising:
a channel estimation module for acquiring reference symbols in the received signal, and
performing channel estimation on the received signal based on the obtained reference symbols by using a pilot-assisted channel estimation technique to obtain a first channel estimation result of the signal, and
adopting a decision-directed channel estimation technology to carry out channel estimation on the signal demodulated by the demodulation module to obtain a second channel estimation result of the signal, and
generating a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result;
a demodulation module, configured to demodulate the signal based on the first channel estimation result.
Embodiment 11 may include the apparatus of embodiment 10, the reference symbols comprising training symbols located in a long training field of a data unit of the signal.
Embodiment 12 may include the apparatus of embodiment 10, the reference symbols comprising pilot symbols located in a signal domain of a data unit of the signal.
Embodiment 13 may include the apparatus of embodiment 10, the reference symbols comprising training symbols located in a long training field and pilot symbols located in a signal field of a data unit of the signal.
Embodiment 14 may include the circuitry of any of embodiments 10 and 13, wherein the channel estimation module employs a pilot-assisted channel estimation technique, and wherein channel estimating the received signal based on the acquired reference symbols comprises:
and the channel estimation module adopts a pilot frequency auxiliary channel estimation technology, carries out channel estimation based on the training symbols in the long training domain and the pilot symbols in the signal domain respectively, and averages each parameter in the two obtained channel estimation results to obtain the first channel estimation result.
Embodiment 15 may include a machine-readable medium having stored thereon instructions which, when executed on a machine, cause the machine to perform the channel estimation method of any of embodiments 1 to 9.
Embodiment 16 may include a system comprising: a memory for storing instructions for execution by one or more processors of the system, an
A processor, which is one of processors of a system, configured to perform the channel estimation method according to any one of embodiments 1 to 9.
In the drawings, some features of the structures or methods may be shown in a particular arrangement and/or order. However, it is to be understood that such specific arrangement and/or ordering may not be required. Rather, in some embodiments, the features may be arranged in a manner and/or order different from that shown in the illustrative figures. In addition, the inclusion of a structural or methodical feature in a particular figure is not meant to imply that such feature is required in all embodiments, and in some embodiments, may not be included or may be combined with other features.
It should be noted that, in the embodiments of the apparatuses in the present application, each unit/module is a logical unit/module, and physically, one logical unit/module may be one physical unit/module, or may be a part of one physical unit/module, and may also be implemented by a combination of multiple physical units/modules, where the physical implementation manner of the logical unit/module itself is not the most important, and the combination of the functions implemented by the logical unit/module is the key to solve the technical problem provided by the present application. Furthermore, in order to highlight the innovative part of the present application, the above-mentioned device embodiments of the present application do not introduce units/modules which are not so closely related to solve the technical problems presented in the present application, which does not indicate that no other units/modules exist in the above-mentioned device embodiments.
It is noted that, in the examples and descriptions of this patent, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the use of the verb "comprise a" to define an element does not exclude the presence of another, same element in a process, method, article, or apparatus that comprises the element.
While the present application has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present application.
Claims (16)
1. A method of channel estimation, comprising:
acquiring a reference symbol in a received signal;
performing channel estimation on the received signal based on the acquired reference symbol by using a pilot frequency auxiliary channel estimation technology to obtain a first channel estimation result of the signal;
performing equalization demodulation on the signal based on the first channel estimation result;
adopting a decision-directed channel estimation technology to carry out channel estimation on the demodulated signal to obtain a second channel estimation result of the signal;
generating a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result.
2. The channel estimation method of claim 1, wherein the reference symbols comprise training symbols located in a long training field of a data unit of the signal.
3. The channel estimation method of claim 1, wherein the reference symbols comprise pilot symbols located in a signal domain of a data unit of the signal.
4. The channel estimation method of claim 1, wherein the reference symbols include training symbols located in a long training field and pilot symbols located in a signal field of a data unit of the signal.
5. The channel estimation method of claim 4, wherein the employing a pilot-assisted channel estimation technique and performing channel estimation on the received signal based on the acquired reference symbols comprises:
and performing channel estimation based on the training symbols in the long training domain and the pilot symbols in the signal domain respectively by adopting a pilot frequency auxiliary channel estimation technology, and averaging parameters in the two obtained channel estimation results to obtain the first channel estimation result.
6. The channel estimation method of any one of claims 1 to 5, wherein the performing channel estimation on the demodulated signal by using a decision-directed channel estimation technique to obtain a second channel estimation result of the signal comprises:
smoothing each subcarrier in the demodulated signal;
and performing channel estimation on each smoothed subcarrier by adopting a decision-directed channel estimation technology to obtain a second channel estimation result of the signal.
7. The channel estimation method of claim 6, wherein the smoothing of each subcarrier in the demodulated signal comprises:
and smoothing each subcarrier in the demodulated signal by adopting a triangular weighted moving average algorithm.
8. The channel estimation method of any of claims 1 to 7, wherein the generating a third channel estimation result for the signal based on the first and second channel estimation results comprises:
calculating the third channel estimation result by the following formula:
Hk＝αHDDCE,k+(1－α)Hpilot,k
wherein HkRepresents the third channel estimation result, HDDCE,kRepresents the second channel estimation result, Hpilot,kRepresenting the first channel estimation result and alpha representing the weighting factor.
9. The channel estimation method of claim 8, wherein the weighting factor α is greater than 0 and smaller than 1 according to the magnitude of the doppler effect and the fading condition of the channel.
10. A channel estimation device, comprising:
a channel estimation module for acquiring reference symbols in the received signal, and
performing channel estimation on the received signal based on the obtained reference symbols by using a pilot-assisted channel estimation technique to obtain a first channel estimation result of the signal, and
adopting a decision-directed channel estimation technology to carry out channel estimation on the signal demodulated by the demodulation module to obtain a second channel estimation result of the signal, and
generating a third channel estimation result of the signal based on the first channel estimation result and the second channel estimation result;
a demodulation module, configured to demodulate the signal based on the first channel estimation result.
11. The channel estimation apparatus of claim 10 wherein the reference symbols comprise training symbols located in a long training field of a data unit of the signal.
12. The channel estimation apparatus of claim 10, wherein the reference symbols comprise pilot symbols located in a signal domain of a data unit of the signal.
13. The channel estimation apparatus of claim 10, wherein the reference symbols comprise training symbols located in a long training field and pilot symbols located in a signal field of a data unit of the signal.
14. The channel estimation apparatus as claimed in claim 13, wherein the channel estimation module employs a pilot-assisted channel estimation technique, and the channel estimation of the received signal based on the obtained reference symbols comprises:
and the channel estimation module adopts a pilot frequency auxiliary channel estimation technology, carries out channel estimation based on the training symbols in the long training domain and the pilot symbols in the signal domain respectively, and averages each parameter in the two obtained channel estimation results to obtain the first channel estimation result.
15. A machine-readable medium having stored thereon instructions which, when executed on a machine, cause the machine to perform the channel estimation method of any one of claims 1 to 9.
16. A system, comprising:
a memory for storing instructions for execution by one or more processors of the system, an
A processor, being one of the processors of the system, for performing the channel estimation method of any one of claims 1 to 9.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115174320A (en) * | 2022-07-04 | 2022-10-11 | 深圳鹏龙通科技有限公司 | MIMO receiver and signal receiving method thereof |
| WO2024012164A1 (en) * | 2022-07-15 | 2024-01-18 | 中兴通讯股份有限公司 | Signal processing method, electronic device, and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115174320A (en) * | 2022-07-04 | 2022-10-11 | 深圳鹏龙通科技有限公司 | MIMO receiver and signal receiving method thereof |
| WO2024012164A1 (en) * | 2022-07-15 | 2024-01-18 | 中兴通讯股份有限公司 | Signal processing method, electronic device, and storage medium |
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