CN106604300B - Small cell base station self-energy supply and self-return method based on full duplex and large-scale antenna technology - Google Patents

Small cell base station self-energy supply and self-return method based on full duplex and large-scale antenna technology Download PDF

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CN106604300B
CN106604300B CN201610996997.XA CN201610996997A CN106604300B CN 106604300 B CN106604300 B CN 106604300B CN 201610996997 A CN201610996997 A CN 201610996997A CN 106604300 B CN106604300 B CN 106604300B
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small cell
cell base
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纪红
陈磊
李曦
张鹤立
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Beijing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/14—Two-way operation using the same type of signal, i.e. duplex
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power

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Abstract

The invention discloses a small cell base station self-energy supply and self-return method based on full duplex and large-scale antenna technology, belonging to the technical field of wireless communication; the method specifically comprises the following steps: firstly, establishing system models of a user, a macro base station and a small cell base station; then, the macro base station and all the small cell base stations respectively measure the channel state information of each link in a certain period, and record an energy arrival rate value and a battery residual energy value, so as to calculate respective pre-beamforming vectors. Respectively modeling link rates of any user accessing a macro base station and accessing an nth cell base station; modeling the return link rate between the small cell base station and the macro base station; thereby calculating the sum of the spectrum efficiency of all the access network users; establishing an optimization problem combining user access selection and power distribution by taking the frequency spectrum efficiency as an optimization target; the invention greatly reduces the network cost and improves the flexibility of the small cell base station deployment, so that the deployment is not influenced by the terrain and the energy supply level.

Description

Small cell base station self-energy supply and self-return method based on full duplex and large-scale antenna technology
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a small cell base station self-powered self-feedback method based on full duplex and large-scale antenna technologies.
Background
Since the 21 st century, the global economy has been rapidly developed, the science and technology are changing day by day, and the high-speed communication technology is gradually applied to various fields of social life. The information age has focused on the requirements for future communications: high reliability, high energy efficiency, low time delay and high quality. The requirements are partly fulfilled by the current third and fourth generation mobile communication technologies, while also sacrificing some other aspects of performance. Today, as the communication industry is rapidly developing, these technologies have not been able to meet the needs of users; how to effectively process massive information and timely and efficiently transmit the information to meet the high requirements of users on communication service quality becomes a key point of attention of next-generation communication technology.
The fifth generation Mobile communication technology (5G) is based on key technologies of large-scale antenna arrays, ultra-dense networking, novel multiple access, full-spectrum access and novel network architectures, brings Gigabit per second (Gbps) level rate experience to users, and realizes high reliability, high energy efficiency, low time delay and high-quality communication. As a new hierarchical heterogeneous cellular network architecture, a small cell network can shorten the distance between a user and a base station, improve the spectrum reuse rate, and reduce the power consumption of the base station, and has been generally accepted by the academic and industrial circles as the most important network architecture in 5G. However, with the large-scale deployment of small cell base stations, a large amount of energy supply and optical fiber backhaul infrastructure needs to be built, which greatly increases the deployment and operation cost of the network, and in some non-urban areas or areas with complex terrain, the power line network and the optical fiber backhaul network are difficult to reach, which hinders the deployment of small cell base stations in these areas and further affects the network service quality of users in these areas, so how to solve the energy supply and backhaul problem has been a significant challenge for small cell networks.
The prior art records, in the aspect of self-energy supply: professor Khaled b.letaief, university of hong kong science and technology, and professor Jeffrey g.andrews, university of texas, propose an energy collection scheme by installing a solar or wind energy collection device at a small cell base station, collecting solar or wind energy, and storing the collected energy in a battery, through which the small cell base station is then powered.
Self-backhauling aspect: the researchers in ericsson propose a scheme for realizing wireless backhaul by using a microwave technology, and realize backhaul of data between a small cell base station and a macro base station by using microwave communication through installing microwave communication equipment at the small cell base station and the macro base station.
Professor et al David j.love at the university of promion proposed a similar solution, but using millimeter wave communication technology instead of microwave communication technology.
However, the prior art is developed for self-powered or self-backhauled respectively, and there is no scheme for self-powered and self-backhauled simultaneously, and existing research, which assumes that the small cell base station backhauls through an optical fiber for self-powered research, so only the energy consumed by the user access is considered, but not the energy consumed by the base station backhauling; most of the self-feedback devices need to consume energy, and if the two technologies are simply put together for use, the self-powered devices may not be able to simultaneously guarantee the energy consumption of the small cell user access and the base station feedback, so that the combined consideration of the self-powered devices and the self-feedback is very necessary to guarantee the normal operation of the small cell base station.
On the other hand, the existing self-backhaul technology, no matter using microwave technology or millimeter wave technology, is only suitable for line-of-sight transmission and is not suitable for urban environments with a large number of shelters, and microwave and millimeter waves hardly have any penetration capability, and cannot complete backhaul function for small cell base stations deployed in indoor environments. In addition, microwave and millimeter wave communication devices are expensive, and must be deployed at a relatively high place, and the requirement on the antenna direction is also high, so that deployment is inconvenient, and rapid large-scale deployment of small cell base stations is not facilitated.
Disclosure of Invention
Aiming at the problems, the invention provides a small cell base station self-powered self-feedback method based on full duplex and large-scale antenna technology, which aims to solve the problems of high deployment cost and low environment matching degree of the existing self-feedback scheme, and enables a network to reasonably perform user access and power distribution according to the energy levels of different small cell base stations and the number and distribution conditions of users in the current network, and finally enables the network to normally and efficiently operate at the current self-powered level.
The method comprises the following specific steps:
step one, aiming at a certain single-cell heterogeneous cellular network, establishing system models of a user, a macro base station and a small cell base station;
large-scale antenna deployed by macro base stationNumber AmSupplying power through a power grid; the number of the small cell base stations is N, the small cell base stations are randomly distributed in the system model, and the number of the antennas of each small cell base station is AsAnd self-powered power supply is adopted; k single antenna users are randomly distributed within the system model.
Step two, aiming at a certain time period, respectively transmitting pilot signals by the macro base station and all the small cell base stations, and measuring the channel state information of each link;
the measurement channel state information includes two parts:
the macro base station transmits pilot signals to the coverage area of the macro base station, all users and the small cell base stations which receive the pilot signals respectively measure respective channel state information and report the information to the macro base station;
each small cell base station respectively transmits a pilot signal with respective maximum transmission power, and each user receiving the pilot signal respectively reports the self measurement channel state to the corresponding small cell base station;
step three, aiming at the time period, different small cell base stations monitor respective self-powered energy reaching conditions and respective battery storage energy conditions, and report energy reaching rate values and battery residual energy values to a macro base station;
and step four, respectively calculating the pre-beamforming vectors of the macro base station and each small cell base station according to the channel state information of each link collected in the step two.
The pre-beamforming vector of the macro base station comprises two parts: pre-beamforming vectors of all users and pre-beamforming vectors of a back link of a small cell base station are processed;
u for set of all users receiving pilot signal of macro base stationmRepresents, UmThe number of the elements is K;
1) for any user U ∈ UmPre-beamforming vector ofComprises the following steps:
Figure BDA0001149300570000032
Figure BDA0001149300570000033
is a matrix
Figure BDA0001149300570000034
Submatrix of corresponding zero singular value in singular value matrix on right side
Figure BDA0001149300570000035
Any column vector of;
Figure BDA0001149300570000036
set U representing all users and small cell base stations within the coverage of a macro base stationubExcept for the user u, all elements are aggregated to a downlink fading matrix of the macro base station;
Figure BDA0001149300570000037
is the power allocated by the macro base station to user u;
2) the pre-beamforming vector for the base station backhaul link of the nth cell is:
Figure BDA0001149300570000038
Figure BDA0001149300570000039
is a matrix
Figure BDA00011493005700000310
The sub-matrix of the corresponding zero singular value in the right side singular value matrix;
Figure BDA00011493005700000311
representation set Uu,bExcept for the nth small cell base station, all elements to the macro base station.
Figure BDA00011493005700000312
And the matrix to be determined comprises power information allocated by the macro base station to the nth small cell base station backhaul link.
The pre-beamforming vector of each small cell base station refers to a pre-beamforming vector of a user receiving a pilot signal of the small cell base station;
for the set of all users receiving pilot signals of the base station of the nth cellRepresents; n ═ 1,2,. N }.
For any user
Figure BDA00011493005700000314
The pre-beamforming vector of (a) is:
Figure BDA00011493005700000315
Figure BDA00011493005700000316
is a matrix
Figure BDA00011493005700000317
Of the right-hand singular value matrix of the corresponding zero singular values of the sub-matrix
Figure BDA00011493005700000318
Any column vector of (1), wherein
Figure BDA00011493005700000320
Is a set of users
Figure BDA00011493005700000321
Except for user u, all elements to the downlink aggregation link fading matrix of the nth small cell base station,
Figure BDA00011493005700000322
is a user set interfered by the pilot signal of the nth small cell base station
Figure BDA00011493005700000323
And (4) the downlink aggregated link fading matrix from all the users to the nth small cell base station.
Figure BDA00011493005700000324
Is the power allocated to user u by the base station of the nth cell.
Step five, aiming at any user u, respectively modeling the link rate of the user accessing the macro base station and the link rate of the user accessing the base station of the nth cell according to the Shannon formula and the pre-beam forming vector;
user U belongs to UmIf the link rate of the user accessing the macro base station is:
Figure BDA00011493005700000325
Figure BDA00011493005700000326
is the channel fading vector, σ, from user u to the macro base station2Is the power spectral density of white noise.
If the user is
Figure BDA00011493005700000327
The link rate of the user accessing the nth small cell base station is as follows:
Figure BDA0001149300570000041
Figure BDA0001149300570000042
is the channel fading vector of user u to the nth small cell base station.
Step six, aiming at the nth small cell base station, modeling the return link rate between the small cell base station and the macro base station according to a Shannon formula and a pre-beam forming vector;
Figure BDA0001149300570000043
Figure BDA0001149300570000044
is that
Figure BDA0001149300570000045
The unit vector of the dimension(s),
Figure BDA0001149300570000046
is a channel matrix
Figure BDA0001149300570000047
The rank of (d);
Figure BDA0001149300570000048
and after pre-beam forming, a channel matrix between the macro base station and the nth cell base station.
Figure BDA0001149300570000049
Is a channel matrix
Figure BDA00011493005700000410
A matrix of singular values of;
Figure BDA00011493005700000411
the macro base station allocates a power matrix of a backhaul link to the nth cell base station; γ is a self-interference cancellation factor;is a self-interference channel matrix;
step seven, according to the link rate modeling of the user accessing the macro base station and the link rate modeling of the user accessing the nth small cell base station, calculating the sum of the frequency spectrum efficiency of all the users accessing the network;
sum of spectral efficiency of all access network users:
Figure BDA00011493005700000413
a denotes the access scheme of all users, wherein
Figure BDA00011493005700000414
Indicating whether user u is attached to the macro base station,
Figure BDA00011493005700000415
representing the access of a user u to a macro base station;
Figure BDA00011493005700000416
indicating whether the user u is accessed to the nth cell base station;
Figure BDA00011493005700000417
representing that a user u is accessed into the base station of the nth cell; if both are 0, it indicates that the user u is denied access.
P denotes the power allocation scheme of the macro base station and all small cell base stations.
Step eight, with the frequency spectrum efficiency as an optimization target, modeling is performed by combining the feedback link rate between the nth small cell base station and the macro base station
Figure BDA00011493005700000418
As a constraint condition, establishing an optimization problem combining user access selection and power distribution;
the power allocation comprises power allocation of a macro base station and power allocation of a small cell base station; the power allocation of the macro base station comprises the power allocation of users accessing the macro base station and the power allocation of return links of different small cell base stations; the power allocation of the small cells is to allocate power to users accessed to each small cell;
the optimization problem is to obtain the user access and power allocation scheme which can make the system spectrum most efficient under the condition of satisfying the constraint.
The constraints are as follows:
Figure BDA0001149300570000051
s.t.C1:
Figure BDA0001149300570000052
C2:
Figure BDA0001149300570000053
C3:
Figure BDA0001149300570000054
C4:
Figure BDA0001149300570000055
C5:
Figure BDA0001149300570000056
C6:
Figure BDA0001149300570000057
C7:
Figure BDA0001149300570000058
constraint condition C1 represents the backhaul link rate between the nth small cell base station and the macro base station
Figure BDA0001149300570000059
It must be equal to or greater than the sum of all user rates in the small cell base station. B issRepresenting a set of small cell base stations with user access.
Constraint C2 represents that the sum of the power consumed by all users accessing the macro base station and the power allocated by the macro base station to the backhaul link of the small cell base station cannot exceed the maximum transmit power of the macro base station
Figure BDA00011493005700000510
Constraint CAnd 3, the user of the nth small cell base station consumes less energy than the sum of the residual capacity of the battery in the small cell base station and the energy collected from the outside in one energy collection period. RhosIndicating the transmission efficiency of the small cell base station, T indicating the length of the period,
Figure BDA00011493005700000511
which represents the power consumption of the circuit loop,
Figure BDA00011493005700000512
indicating the energy arrival rate of the nth small cell base station in this period,
Figure BDA00011493005700000513
representing the remaining battery energy of the nth small cell base station.
The constraint conditions C4 and C5 are that the link rate of the user u accessing the macro base station and the link rate of the user u accessing the small cell base station both need to satisfy the minimum service rate RminThe requirements of (a).
Constraints C6 and C7 indicate that a user can only access the macro base station or any small cell base station at most.
And step nine, aiming at the optimization problem, calculating a problem suboptimal solution by using a differential convex optimization theory and an iterative algorithm based on a limited concave-convex process to obtain a user access selection and power distribution scheme which ensures the service rate of each user, meets the emission power of a macro base station and the energy supply limitation of a small cell base station and has the maximum system spectrum efficiency.
The invention has the advantages that:
1) the small cell base station self-powered self-feedback method based on the full duplex and large-scale antenna technology greatly reduces the network cost, improves the flexibility of the deployment of the small cell base station, and enables the deployment of the small cell base station not to be influenced by the terrain and the power supply level.
2) The small cell base station self-energy supply self-feedback method based on the full duplex and large-scale antenna technology supports a self-feedback scheme by utilizing the latest full duplex and large-scale antenna technology, greatly improves the frequency spectrum efficiency of a system, and ensures the service quality of a network.
3) The interference elimination scheme based on the large-scale antenna technology can effectively eliminate cross-layer interference in the traditional small cell network and multi-user interference introduced by the large-scale antenna technology, thereby improving the system spectrum efficiency and improving the network performance.
4) The invention discloses a small cell base station self-powered self-feedback method based on full duplex and large-scale antenna technologies, provides a combined user access selection and power distribution algorithm, and effectively ensures the smooth implementation of the scheme provided by the invention.
Drawings
Figure 1 is a diagram of the wireless backhaul architecture for small cell base stations using cellular communications bands in accordance with the present invention;
FIG. 2 is a system model for establishing a user, a macro base station and a small cell base station in a single cell heterogeneous cellular network according to the present invention;
fig. 3 is a flow chart of a self-powered self-feedback method for a small cell base station based on full-duplex and large-scale antenna technologies according to the present invention;
FIG. 4 is a graph comparing grid power consumption and SBS deployment density for the method of the present invention and three comparison schemes;
FIG. 5 is a graph comparing network cost and SBS deployment density for the method of the present invention and three comparison schemes;
FIG. 6 is a graph comparing spectral efficiency and SBS number for the method of the present invention and three comparison schemes;
fig. 7 is a graph comparing the minimum rate requirement of the user with the number of the admitted users in the three comparison schemes according to the present invention.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The following describes in detail a specific embodiment of the present invention with reference to the drawings.
The invention relates to a small cell base station self-powered self-feedback method based on a full duplex technology and a large-scale antenna technology. An enhanced block diagonalization beamforming scheme for eliminating interference is adopted, and cross-layer interference and multi-user interference are eliminated simultaneously; the method is suitable for an algorithm combining user access and power distribution, can effectively utilize energy according to the current energy level of the network, ensures the service quality of the user and improves the spectrum efficiency of the network.
The invention provides a method for carrying out wireless return of a small cell base station by using a cellular communication frequency band, wherein the frequency band has good non-line-of-sight retransmission performance and is very suitable for urban terrains. The specific scheme is as follows: as shown in fig. 1, full-duplex communication hardware is installed at the small cell base station, so that the small cell base station has the same-frequency full-duplex communication capability. In the downlink, the small cell base station receives data from the macro base station while transmitting the received data to its served users on the same resource blocks. In the uplink, the small cell base station receives data from the user while transmitting the data back to the macro base station in the same resource block. At the moment, simultaneous same-frequency transmission of an access link and a return link of a user in a single small cell is realized.
Furthermore, the invention deploys large-scale antennas on the macro base station and the small cell base station, the number of the antennas of the small cell base station is far less than that of the macro base station, and the simultaneous same-frequency access transmission of users in each cell is realized by using the space division multiple access technology. By jointly using the same-frequency full duplex technology and the large-scale antenna technology, the access of users in the cell and the return of the small cell base station can be realized at the same frequency, and the frequency spectrum efficiency of the network is greatly improved.
However, due to the limited frequency spectrum of the cellular band, it is unable to provide enough frequency spectrum to support users, and in addition, due to the limited maximum transmission power of the macro base station, the self-powered level of the small cell base station is limited, and the throughput of the small cell backhaul link must be greater than the throughput of all users in the small cell, so it is very important how to guarantee the service quality of the access users and ensure the efficient operation of the network.
The invention provides a small cell base station self-powered self-feedback method based on full duplex and large-scale antenna technology based on the following algorithm;
the specific algorithm comprises the following steps:
1) user admission control and access selection algorithms.
In case of a large number of users making access requests, it is not possible for the network to satisfy all user requests, so it has to select which users are rejected and which users are admitted, and since both macro and small cell base stations can serve the users, the admitted users also need to select which base station to access to.
2) And a power allocation algorithm.
In the process of user access selection, the power or energy level of different base stations is an important reference factor, because a large number of users cannot be flooded into the same base station, and thus the power or energy level of the users cannot guarantee the service quality of the users. In addition, after the user accesses the base station, how to reasonably allocate the resources and energy of the base station to the user is very important, so that the service quality of the user is ensured, and the normal backhaul of the small cell base station is also ensured.
3) And an interference cancellation algorithm.
Since the macro base station and the small cell base station both use the same frequency transmission, the cross-layer interference of the macro base station to the small cell base station and the same-layer interference between the small cells are very serious. In addition, due to the use of large-scale antenna technology, users in each base station are simultaneously transmitted with the same frequency, which results in the existence of multi-user interference. If cross-layer interference, same-layer interference and multi-user interference are not processed, the frequency spectrum efficiency of the network is influenced, the high-efficiency operation of the self-powered self-feedback scheme provided by the invention is influenced, and a precoding scheme aiming at eliminating the interference is provided.
As shown in fig. 3, the specific steps are as follows:
step one, aiming at a certain single-cell heterogeneous cellular network, establishing system models of a user, a macro base station and a small cell base station;
as shown in fig. 2, in a single-cell cellular network, a macro base station is powered by a conventional power line network and deploys a large number of antennasMesh is Am(ii) a In the coverage area of the cell, a large number of small cell base stations are randomly distributed, the number of the small cell base stations is N, and the number of antennas of each small cell base station is AsA solar energy or wind energy collecting device is arranged at the base station to supply power in a self-power supply mode; meanwhile, K single-antenna users are randomly distributed in the system model area.
Each user can access the macro base station or any small cell base station, and does not access in the initial state.
U for aggregation of all usersmRepresents, UmThe number of the elements is K; if a user is located within a small cell base station, the user can access to the macro base station or the small cell base station, BsRepresents a set of small cell base stations with user access,denotes the set of all small cell base stations interfering with a certain user u for that user.
Step two, aiming at a certain time period, respectively transmitting pilot signals by the macro base station and all the small cell base stations, and measuring the channel state information of each link;
the measurement channel state information includes two parts:
firstly, a macro base station sends pilot signals to a coverage area of the macro base station, all users and small cell base stations receiving the pilot signals respectively measure respective channel state information and report the measured channel state information to the macro base station;
Figure BDA0001149300570000081
representing the channel fading vectors of user u to MBS,
Figure BDA0001149300570000082
indicating the channel fading matrix of the nth SBS to MBS.
Secondly, each small cell base station transmits a pilot signal with respective maximum transmission power, and each user receiving the pilot signal reports the self measurement channel state to the corresponding small cell base station;
one user may receive pilot signals of a plurality of SBS and need to report respectively;
Figure BDA0001149300570000083
representing the channel fading vectors of users u through the nth SBS,
Figure BDA0001149300570000084
step three, aiming at the time period, different small cell base stations monitor respective self-powered energy reaching conditions and respective battery storage energy conditions, and report energy reaching rate values and battery residual energy values to a macro base station;
Figure BDA0001149300570000085
indicating the energy arrival rate of the nth SBS during that time period,
Figure BDA0001149300570000086
indicating the nth SBS battery residual energy.
And step four, respectively calculating the pre-beamforming vectors of the macro base station and each small cell base station according to the channel state information of each link collected in the step two.
The beam forming is generally carried out after the user access scheme is determined, the pre-beam forming carried out in the invention is suitable for any access scheme, and the pre-beam forming carried out in the invention aims to eliminate multi-user interference and cross-layer interference and reduce the complexity of a user access and power allocation algorithm.
Firstly, a pre-beamforming vector of a macro base station comprises two parts: pre-beamforming vectors of all users in the coverage of a macro base station and pre-beamforming vectors of a back link of a small cell base station;
firstly, defining the set of all users and small cell base stations in the coverage area of a macro base station in the system model as Uu,b；
Then, two aggregate downlink fading matrices are calculated
Figure BDA0001149300570000087
And
Figure BDA0001149300570000088
representation set Uu,bExcept for user u, all elements are transmitted to the aggregated downlink fading matrix of MBS;
to pairAfter SVD decomposition, the following results are obtained:
Figure BDA00011493005700000811
Figure BDA00011493005700000812
is an aggregated downlink fading matrix
Figure BDA00011493005700000813
The left singular matrix of (a) is,
Figure BDA00011493005700000814
is an aggregated downlink fading matrix
Figure BDA00011493005700000815
The matrix of singular values of (a) is,
Figure BDA00011493005700000816
is an aggregated downlink fading matrix
Figure BDA00011493005700000817
The right-side singular value matrix of the array is a submatrix corresponding to non-zero singular values;
Figure BDA00011493005700000818
is an aggregated downlink fading matrix
Figure BDA00011493005700000819
The right-side singular value matrix of (1) corresponds to a submatrix of zero singular values.
Representation set Uu,bExcept for the nth SBS, all elements to the MBS's aggregate downlink fading matrix.
To pair
Figure BDA00011493005700000821
After SVD decomposition, the following results are obtained:
Figure BDA00011493005700000822
Figure BDA00011493005700000823
is an aggregated downlink fading matrix
Figure BDA00011493005700000824
The left singular matrix of (a) is,
Figure BDA00011493005700000825
is an aggregated downlink fading matrix
Figure BDA00011493005700000826
The matrix of singular values of (a) is,
Figure BDA0001149300570000091
is an aggregated downlink fading matrix
Figure BDA0001149300570000092
The right-side singular value matrix of the array is a submatrix corresponding to non-zero singular values;is aggregate downlink fadingMatrix array
Figure BDA0001149300570000094
The right-side singular value matrix of (1) corresponds to a submatrix of zero singular values.
And finally, constructing pre-beamforming matrixes of the access link of the user and the return link of the SBS.
1) For any user U ∈ UmIf the number of antennas of the MBS satisfies the condition Am≥||Um||+AsxN-1, pre-beamforming vector for user
Figure BDA0001149300570000095
Comprises the following steps:
Figure BDA0001149300570000096
wherein
Figure BDA0001149300570000097
Is a sub-matrix
Figure BDA0001149300570000098
Any of the above-mentioned columns of (a),
Figure BDA0001149300570000099
the power allocated to the user u by the macro base station is obtained in the subsequent steps.
2) The pre-beamforming vector for the base station backhaul link of the nth cell is:
Figure BDA00011493005700000910
Figure BDA00011493005700000911
and the matrix to be determined comprises power information allocated by the macro base station to the nth small cell base station backhaul link. Because the SBS is also provided with multiple antennas, a transmission link between the MBS and the SBS is an MIMO link, so thatThe configuration is more complex, but includes the power information allocated to the backhaul link by the MBS, which is further processed by the following steps.
Secondly, the pre-beamforming vector of each small cell base station refers to the pre-beamforming vector of the user receiving the pilot signal of the small cell base station;
first, define
Figure BDA00011493005700000913
Represents the set of all users in the nth SBS maximum coverage area, whereinN is the set of all users that can access the nth cell base station, where N is {1, 2.. N };
Figure BDA00011493005700000915
representing a set of users located within the interference area of the nth cell base station.
Then, an aggregate downlink fading matrix is calculated
Figure BDA00011493005700000916
Figure BDA00011493005700000918
Is a set of users
Figure BDA00011493005700000919
Except for user u, all elements to the downlink aggregation link fading matrix of the nth small cell base station,
Figure BDA00011493005700000920
is a set
Figure BDA00011493005700000921
All users in to the nthA downlink aggregated link fading matrix of the small cell base station.
To pair
Figure BDA00011493005700000922
After SVD decomposition, the following results are obtained:
Figure BDA00011493005700000923
Figure BDA00011493005700000924
is an aggregated downlink fading matrix
Figure BDA00011493005700000925
Left singular value matrix of (a);
Figure BDA00011493005700000926
is an aggregated downlink fading matrixThe matrix of singular values of (a) is,is an aggregated downlink fading matrix
Figure BDA00011493005700000929
The right-hand singular value matrix of (a) corresponds to a sub-matrix of non-zero singular values.
Figure BDA00011493005700000930
Is an aggregated downlink fading matrix
Figure BDA00011493005700000931
The right-hand singular value matrix of (a) corresponds to the zero singular value sub-matrix.
Finally, any user is constructed
Figure BDA00011493005700000932
The pre-beamforming matrix of (a).
If the number of SBS base station antennas satisfies the condition
Figure BDA00011493005700000933
The beamforming vector for the user of the nth SBS is constructed as:
Figure BDA00011493005700000934
is thatThe column vector of (a) is,
Figure BDA00011493005700000937
is the power allocated to user u by the base station of the nth cell.
Step five, aiming at any user u, respectively modeling the link rate of the user accessing the macro base station and the link rate of the user accessing the base station of the nth cell according to the Shannon formula and the pre-beam forming vector;
any user has different access options due to different positions;
first, if the user U belongs to UmSignals received from macro base stationComprises the following steps:
Figure BDA0001149300570000102
wherein the content of the first and second substances,
Figure BDA0001149300570000103
for a transmitted signal from a macro base station,
Figure BDA0001149300570000104
is white gaussian noise;
user U belongs to UmAccess macro base stationThe link rates of (a) are:
is the channel fading vector, σ, from user u to the macro base station2Power spectral density of white noise.
If the user is
Figure BDA0001149300570000107
The signal received by the user from the base station of the nth cell
Figure BDA0001149300570000108
Comprises the following steps:
Figure BDA0001149300570000109
wherein the content of the first and second substances,
Figure BDA00011493005700001010
is the transmitted signal from this small cell base station,
Figure BDA00011493005700001011
is gaussian white noise;
user' s
Figure BDA00011493005700001012
The link rate of the base station accessed to the nth cell is as follows:
Figure BDA00011493005700001013
Figure BDA00011493005700001014
is the channel fading vector of user u to the nth small cell base station.
Step six, aiming at the nth small cell base station, modeling the return link rate between the small cell base station and the macro base station according to a Shannon formula and a pre-beam forming vector;
firstly, calculating a backhaul link signal received by the nth small cell base station from the macro base station as follows:
Figure BDA00011493005700001015
wherein the content of the first and second substances,
Figure BDA00011493005700001016
is a transmitted signal vector from the macro base station,
Figure BDA00011493005700001017
is gaussian white noise;
Figure BDA00011493005700001018
the interference signal of the access link of the SBS is received by the backhaul link and is represented as:
Figure BDA00011493005700001019
where γ is a self-interference cancellation factor,
Figure BDA00011493005700001020
is a self-interference channel matrix that is,
Figure BDA00011493005700001021
is the sum matrix of all user beamforming vectors in the nth SBS, i.e.
Figure BDA00011493005700001022
Figure BDA00011493005700001023
Is a diagonal matrix of the power allocated to all users in the nth SBS, i.e.
Figure BDA00011493005700001025
Represents the sum vector of signals transmitted by the nth small cell base station to the affiliated user,
Figure BDA00011493005700001027
Figure BDA00011493005700001028
then, because MIMO channels are formed between the macro base station and the small cell base station, effective MIMO channel analysis is conducted through research
Figure BDA00011493005700001029
The composition of (1). Definition of
Figure BDA00011493005700001030
As a channel matrix between the MBS and the nth SBS after pre-beamforming.
To pair
Figure BDA00011493005700001031
The SVD decomposition is performed as follows:
Figure BDA00011493005700001032
wherein the content of the first and second substances,is a channel matrix
Figure BDA0001149300570000112
The matrix of left singular values of (a),
Figure BDA0001149300570000113
is a channel matrixThe matrix of right-hand singular values of (c),
Figure BDA0001149300570000115
is a channel matrix
Figure BDA0001149300570000116
Singular value matrix of
Figure BDA0001149300570000117
Is of rank
Figure BDA0001149300570000118
According to the MIMO channel transmission theory, the original MIMO channel can be converted into several independent parallel single-input single-output channels by multiplying the left singular matrix of the channel matrix at the receiving end
Figure BDA0001149300570000119
Multiplication by
Figure BDA00011493005700001110
A new received signal will be obtained at SBS as follows:
Figure BDA00011493005700001111
wherein the content of the first and second substances,
Figure BDA00011493005700001112
is thatThe effective transmission of the signals for the dimension,
Figure BDA00011493005700001114
is that
Figure BDA00011493005700001115
Unit vector of dimension. Then, the rate of the backhaul link between the nth small cell base station and the macro base station is expressed as:
Figure BDA00011493005700001116
Figure BDA00011493005700001117
the macro base station allocates a power matrix of a backhaul link to the nth cell base station; the matrix is a diagonal matrix, and each element on the diagonal line is respectively converted into a power value on an independent parallel channel corresponding to the MIMO channel; γ is a self-interference cancellation factor;
Figure BDA00011493005700001118
is a self-interference channel matrix;
step seven, according to the link rate modeling of the user accessing the macro base station and the link rate modeling of the user accessing the nth small cell base station, calculating the sum of the frequency spectrum efficiency of all the users accessing the network;
the invention concerns the influence of a self-powered self-feedback scheme on the network spectrum efficiency, and the target function of all models is the sum of the spectrum efficiencies of the users accessing the network:
Figure BDA00011493005700001119
a denotes the access scheme of all users, the user access selection is modeled with a variable a,
Figure BDA00011493005700001120
indicating whether user u is attached to the macro base station,
Figure BDA00011493005700001121
representing the access of a user u to a macro base station;
Figure BDA00011493005700001122
indicating whether the user is accessed to the nth cell base station;
Figure BDA00011493005700001123
representing that a user u is accessed into the base station of the nth cell; if both are 0, it indicates that the user u is denied access. P denotes a macro base stationAnd power allocation schemes of all small cell base stations.
The power allocation of the macro base station comprises the power allocation of users accessing the macro base station and the power allocation of return links of different small cell base stations;
the power allocation of the small cells is to allocate power to users accessing each small cell.
Step eight, with the frequency spectrum efficiency as an optimization target, modeling is performed by combining the feedback link rate between the nth small cell base station and the macro base station
Figure BDA00011493005700001124
As a constraint condition, establishing an optimization problem combining user access selection and power distribution;
since the transmission power of macro base stations is limited, the energy supply level of small cell base stations is limited, and the network must guarantee the service quality of users, the objective of this optimization problem is to obtain a user access and power allocation scheme that maximizes the system spectrum efficiency under the constraint of being satisfied.
The constraints are as follows:
Figure BDA0001149300570000121
s.t.C1:
Figure BDA0001149300570000122
C2:
Figure BDA0001149300570000123
C3:
C4:
Figure BDA0001149300570000125
C5:
Figure BDA0001149300570000126
C6:
Figure BDA0001149300570000127
C7:
Figure BDA0001149300570000128
constraint condition C1 represents the backhaul link rate between the nth small cell base station and the macro base station
Figure BDA0001149300570000129
It must be equal to or greater than the sum of all user rates in the small cell base station. B issA set of small cell base stations representing user access;
constraint C2 denotes all users accessing the macro base station
Figure BDA00011493005700001210
The sum of the power consumed and the power allocated by the macro base station to the small cell base station backhaul link cannot exceed the maximum transmit power of the macro base station
Figure BDA00011493005700001211
Figure BDA00011493005700001212
Representing the power consumed by the user u to access the macro base station;
Figure BDA00011493005700001213
representing the sum of the powers distributed by the macro base station to the base station backhaul link of the nth cell;
constraint C3 indicates that the user of the nth small cell base station consumes less energy than the sum of the remaining capacity of the battery in the small cell base station and the energy collected from the outside during an energy collection period. RhosIndicating the transmission efficiency of the small cell base station, T indicating the length of the period,
Figure BDA00011493005700001214
which represents the power consumption of the circuit loop,
Figure BDA00011493005700001215
indicating the energy arrival rate of the nth small cell base station in this period,
Figure BDA00011493005700001216
representing the remaining battery energy of the nth small cell base station.
The constraint conditions C4 and C5 are that the link rate of the user u accessing the macro base station and the link rate of the user u accessing the small cell base station both meet the minimum service rate RminThe requirements of (a).
Constraints C6 and C7 indicate that a user can only access the macro base station or any small cell base station at most.
And step nine, aiming at the optimization problem, calculating a problem suboptimal solution by using a differential convex optimization theory and an iterative algorithm based on a limited concave-convex process to obtain a user access selection and power distribution scheme which ensures the service rate of each user, meets the emission power of a macro base station and the energy supply limitation of a small cell base station and has the maximum system spectrum efficiency.
Because the modeling problem is mixed integer programming and the solving complexity is very high, a method for solving a suboptimal solution is adopted, and the concrete steps are as follows:
step 901, relaxing the limiting variable a in the constraint condition C6 into a continuous variable of [0,1 ];
since the constraint variable a in the constraint condition C6 is an integer of 0 or 1, which may have a great influence on the problem solution, after the variable a is relaxed, the user may access multiple base stations, and the specific access proportion is determined by the relaxed variable, at this time, the constraint conditions C4, C5, and C6 may be rewritten as:
C4'&C5':
Figure BDA0001149300570000131
C6':
Figure BDA0001149300570000132
step 902, rate of backhaul link between nth SBS and MBS
Figure BDA0001149300570000133
Performing variable replacement on the self-interference item in the step (2);
the on-rate is due to the SBS return link being interfered by the SBS access link
Figure BDA0001149300570000134
The middle denominator term has a corresponding interference term, which has a very adverse effect on the solution of the problem, so Q is defined as the self-interference temperature, and the rate is defined
Figure BDA0001149300570000135
Lower boundary of (1)
Figure BDA0001149300570000136
The following were used:
Figure BDA0001149300570000137
by introducing new constraints: c8:
Figure BDA0001149300570000138
obtaining:
Figure BDA0001149300570000139
and step 903, reconstructing a modeled objective function.
Through constraint relaxation and interference item replacement, the reacquire optimization problem is as follows:
Figure BDA00011493005700001310
s.t.C1':
Figure BDA00011493005700001311
C2:
Figure BDA00011493005700001312
C3:
Figure BDA00011493005700001313
C4'&C5':
Figure BDA00011493005700001314
C6':
Figure BDA00011493005700001315
C7:
Figure BDA00011493005700001316
C8:
Figure BDA00011493005700001317
since the reconstructed object function is convex except for the constraint C1 'and the constraint C1' is in the form of a concave function minus a concave function, the reconstructed object function is a DCP, which can be solved with the prior art.
In order to prove the economy of the self-powered self-feedback method and the effectiveness of the correspondingly proposed support algorithm, two simulation scenes are specially designed for verification.
Simulation scenario 1: in a multi-cell scene, a classical 7-cell model is adopted, one MBS is arranged in the center of each cell, the distance between different MBS is 1 km, and users and SBS are uniformly distributed in the area;
simulation scenario 2: in a single-cell scene, the MBS is deployed in the center of a 500-meter square area, and users and SBS are uniformly distributed in the area.
Other simulation parameters are shown in the following table:
parameter name Numerical value
Carrier frequency 2.5GHz
White noise power spectral density -174dBm/Hz
Number of MBS antennas 256
Number of SBS antennas 32
MBS maximum transmission power 46dBm
Maximum transmission power of SBS 20dBm
Power consumption of MBS loop 54dBm
SBS loop power consumption 20dBm
MBS power amplifier loss 5％
SBS power amplifier loss 5％
Multi-cell simulation scenario:
scenario 1 is mainly used to verify the economy of the self-powered self-feedback scheme proposed by the present invention, and the comparison scheme includes: 1) the power supply optical fiber of the power grid passes back; 2) the power supply of the power grid wirelessly passes back; 3) self-powered optical fiber return; 4) self-powered and self-returning.
As shown in fig. 4, the network power consumed by the two self-powered schemes is much less than the conventional two-grid power supply scheme, mainly because the small cell base station no longer needs to supply power from the grid, but the power consumed by the self-powered self-backhaul scheme is greater than that consumed by the self-powered fiber backhaul scheme, which mainly because the self-powered self-backhaul scheme needs to consume extra power at the MBS, but the power consumed by the self-powered fiber backhaul scheme is very low.
As shown in fig. 5, the network cost of the self-backhauling self-powered scheme proposed by the present invention is much lower than that of other schemes, on one hand, because the self-powered scheme reduces the network power consumption cost, and on the other hand, because the self-backhauling scheme avoids the expensive construction cost when constructing the optical fiber backhauling.
Single-cell simulation scenario:
scenario 2 is mainly used to verify the impact of the full-duplex technology and the large-scale antenna technology introduced by the present invention and the proposed interference cancellation algorithm on the system performance. The comparative scheme includes scheme 1: a half-duplex backhaul scheme without large-scale antennas and interference cancellation; scheme 2: a half-duplex backhaul scheme with large-scale, interference-free antenna cancellation; scheme 3: a full duplex backhaul scheme with large-scale, interference-free antenna cancellation; scheme 4: the invention provides a full-duplex backhaul scheme with large-scale antennas and interference cancellation.
As shown in fig. 6, as the number of SBS increases, the spectrum efficiency of the system increases, mainly because as SBS increases, more users access to the base station closer to the base station, so that the link loss is greatly reduced, and the spectrum efficiency is greatly improved;
as shown in fig. 7, as the minimum rate requirement of the user increases, the number of users that the system can accommodate decreases exponentially, because the system has limited resources and limited users. Meanwhile, fig. 6 and 7 both show the effectiveness of introducing full duplex technology and large-scale antenna technology and the proposed interference cancellation method in the self-backhauling technology, and because of the two novel technologies, all users in the system simultaneously access and return on the same frequency band, the system spectrum efficiency is greatly improved, and by eliminating cross-layer and multi-user interference, the interference cancellation scheme further improves the spectrum efficiency, and simultaneously lays a foundation for the system to serve more users.
The invention provides a self-powered self-return scheme in a small cell network, which can effectively reduce the network cost and improve the flexibility of small cell deployment, wherein full duplex and large-scale antenna technologies are used for improving the self-return reliability and improving the spectrum efficiency of the network. In summary, the present invention provides a small cell self-backhaul self-power scheme based on full-duplex technology and large-scale antenna technology, and provides a beamforming scheme for interference cancellation and a joint user access and power allocation algorithm to ensure the operation of the self-power self-backhaul scheme.

Claims (3)

1. A small cell base station self-powered self-feedback method based on full duplex and large-scale antenna technology is characterized by comprising the following specific steps:
step one, aiming at a certain single-cell heterogeneous cellular network, establishing system models of a user, a macro base station and a small cell base station;
step two, aiming at a certain time period, respectively transmitting pilot signals by the macro base station and all the small cell base stations, and measuring the channel state information of each link;
step three, aiming at the time period, different small cell base stations monitor respective self-powered energy reaching conditions and respective battery storage energy conditions, and report energy reaching rate values and battery residual energy values to a macro base station;
step four, respectively calculating respective pre-beam forming vectors by the macro base station and each small cell base station according to the channel state information of each link collected in the step two;
first, the pre-beamforming vector of the macro base station includes two parts: pre-beamforming vectors of all users and pre-beamforming vectors of a back link of a small cell base station are processed;
u for set of all users receiving pilot signal of macro base stationmRepresents, UmThe number of the elements is K;
1) for any user U ∈ UmPre-beamforming vector of
Figure FDA0002252480190000011
Comprises the following steps:
Figure FDA0002252480190000012
is a matrix
Figure FDA0002252480190000014
Submatrix of corresponding zero singular value in singular value matrix on right sideAny column vector of;set U representing all users and small cell base stations within the coverage of a macro base stationu,bExcept for the user u, all elements are aggregated to a downlink fading matrix of the macro base station;
Figure FDA0002252480190000017
is the power allocated by the macro base station to user u;
2) the pre-beamforming vector for the base station backhaul link of the nth cell is:
Figure FDA0002252480190000018
Figure FDA0002252480190000019
is a matrix
Figure FDA00022524801900000110
The sub-matrix of the corresponding zero singular value in the right side singular value matrix;
Figure FDA00022524801900000111
representation set Uu,bExcept for the nth small cell base station, all elements are aggregated to a macro base station to form a downlink fading matrix;
Figure FDA00022524801900000112
the matrix to be determined comprises power information distributed by the macro base station to the nth small cell base station backhaul link;
then, the pre-beamforming vector of each small cell base station refers to the pre-beamforming vector of the user receiving the pilot signal of the small cell base station;
for the set of all users receiving pilot signals of the base station of the nth cell
Figure FDA00022524801900000113
Represents; n ═ 1,2,. N };
for any user
Figure FDA00022524801900000114
The pre-beamforming vector of (a) is:
Figure FDA00022524801900000115
Figure FDA00022524801900000116
is a matrix
Figure FDA00022524801900000117
Of the right-hand singular value matrix of the corresponding zero singular values of the sub-matrixAny column vector of (1), wherein
Figure FDA00022524801900000119
Figure FDA00022524801900000120
Is a set of users
Figure FDA00022524801900000121
Except for user u, all elements to the downlink aggregation link fading matrix of the nth small cell base station,
Figure FDA00022524801900000122
is a user set interfered by the pilot signal of the nth small cell base stationA downlink aggregation link fading matrix from all users to the nth small cell base station;
Figure FDA00022524801900000124
is the power allocated to user u by the nth cell base station;
step five, aiming at any user u, respectively modeling the link rate of the user accessing the macro base station and the link rate of the user accessing the base station of the nth cell according to the Shannon formula and the pre-beam forming vector;
user U belongs to UmIf the link rate of the user accessing the macro base station is:
Figure FDA0002252480190000021
Figure FDA0002252480190000022
is the channel fading vector, σ, from user u to the macro base station2Is the power spectral density of white noise;
if the user is
Figure FDA0002252480190000023
The link rate of the user accessing the nth small cell base station is as follows:
Figure FDA0002252480190000025
is the channel fading vector from the user u to the nth small cell base station;
step six, aiming at the nth small cell base station, modeling the return link rate between the small cell base station and the macro base station according to a Shannon formula and a pre-beam forming vector;
is that
Figure FDA0002252480190000028
The unit vector of the dimension(s),
Figure FDA0002252480190000029
is a channel matrixThe rank of (d);after pre-beam forming, a channel matrix between a macro base station and an nth cell base station;
Figure FDA00022524801900000212
is a channel matrix
Figure FDA00022524801900000213
A matrix of singular values of;the macro base station allocates a power matrix of a backhaul link to the nth cell base station; γ is a self-interference cancellation factor;
Figure FDA00022524801900000215
is a self-interference channel matrix;
step seven, according to the link rate modeling of the user accessing the macro base station and the link rate modeling of the user accessing the nth small cell base station, calculating the sum of the frequency spectrum efficiency of all the users accessing the network;
sum of spectral efficiency of all access network users:
Figure FDA00022524801900000216
a represents the access scheme of all users, and P represents the power allocation scheme of a macro base station and all small cell base stations;indicating whether user u is attached to the macro base station,
Figure FDA00022524801900000218
representing the access of a user u to a macro base station;
Figure FDA00022524801900000219
indicates whether user u isAccessing to the nth cell base station;
Figure FDA00022524801900000220
representing that a user u is accessed into the base station of the nth cell; if both are 0, it represents that the user u is refused to access;
step eight, with the frequency spectrum efficiency as an optimization target, modeling is performed by combining the feedback link rate between the nth small cell base station and the macro base station
Figure FDA00022524801900000221
As a constraint condition, establishing an optimization problem combining user access selection and power distribution;
the power allocation comprises power allocation of a macro base station and power allocation of a small cell base station; the power allocation of the macro base station comprises the power allocation of users accessing the macro base station and the power allocation of return links of different small cell base stations; the power allocation of the small cells is to allocate power to users accessed to each small cell;
the optimization problem is to obtain a user access and power distribution scheme which enables the spectrum efficiency of the system to be the highest under the condition of meeting the constraint;
the constraints are as follows:
Figure FDA0002252480190000031
s.t.C1:
Figure FDA0002252480190000032
C2:
C3:
Figure FDA0002252480190000034
C4:
Figure FDA0002252480190000035
C5:
C6:
Figure FDA0002252480190000037
C7:
Figure FDA0002252480190000038
constraint condition C1 represents the backhaul link rate between the nth small cell base station and the macro base station
Figure FDA0002252480190000039
The sum of all user rates in the small cell base station must be greater than or equal to; b issA set of small cell base stations representing user access;
constraint C2 represents that the sum of the power consumed by all users accessing the macro base station and the power allocated by the macro base station to the backhaul link of the small cell base station cannot exceed the maximum transmit power of the macro base station
Constraint C3 indicates that the user of the nth small cell base station consumes less energy than the sum of the remaining battery capacity of the small cell base station and the energy collected from the outside during an energy collection period; rhosIndicating the transmission efficiency of the small cell base station, T indicating the length of the period,
Figure FDA00022524801900000311
which represents the power consumption of the circuit loop,
Figure FDA00022524801900000312
indicating the energy arrival rate of the nth small cell base station in this period,
Figure FDA00022524801900000313
representing the battery residual energy of the base station of the nth cell;
the constraint conditions C4 and C5 are that the link rate of the user u accessing the macro base station and the link rate of the user u accessing the small cell base station both need to satisfy the minimum service rate RminThe need of (c);
constraints C6 and C7 indicate that a user can only access the macro base station or any small cell base station at most;
and step nine, aiming at the optimization problem, calculating a problem suboptimal solution by using a differential convex optimization theory and an iterative algorithm based on a limited concave-convex process to obtain a user access selection and power distribution scheme which ensures the service rate of each user, meets the emission power of a macro base station and the energy supply limitation of a small cell base station and has the maximum system spectrum efficiency.
2. The self-powered self-backhauling method for small cell base station based on full duplex and large scale antenna technology as claimed in claim 1, wherein the first step is specifically: the number of large-scale antennas deployed by the macro base station is AmSupplying power through a power grid; the number of the small cell base stations is N, the small cell base stations are randomly distributed in the system model, and the number of the antennas of each small cell base station is AsAnd self-powered power supply is adopted; k single antenna users are randomly distributed within the system model.
3. The small cell base station self-powered self-backhauling method based on full-duplex and large-scale antenna technology as claimed in claim 1, wherein the second step of measuring the channel state information comprises two parts:
the macro base station transmits pilot signals to the coverage area of the macro base station, all users and the small cell base stations which receive the pilot signals respectively measure respective channel state information and report the information to the macro base station;
each small cell base station respectively transmits pilot signals with respective maximum transmission power, and each user receiving the pilot signals respectively reports the self measurement channel state to the corresponding small cell base station.
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