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CN111181615A - Multi-cell wireless communication method based on intelligent reflector - Google Patents

Multi-cell wireless communication method based on intelligent reflector Download PDF

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CN111181615A
CN111181615A CN201911206324.XA CN201911206324A CN111181615A CN 111181615 A CN111181615 A CN 111181615A CN 201911206324 A CN201911206324 A CN 201911206324A CN 111181615 A CN111181615 A CN 111181615A
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base station
beam forming
user terminal
reflecting surface
intelligent
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CN111181615B (en
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许杰
谢海亮
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Guangdong University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/04013—Intelligent reflective surfaces
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0632—Channel quality parameters, e.g. channel quality indicator [CQI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/0848—Joint weighting
    • H04B7/0857—Joint weighting using maximum ratio combining techniques, e.g. signal-to- interference ratio [SIR], received signal strenght indication [RSS]
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    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The application discloses a multi-cell wireless communication method based on an intelligent reflecting surface, wherein a system aimed at by the method comprises a plurality of cooperative cells, the cooperative cells are provided with the intelligent reflecting surface, and each cooperative cell is provided with a base station and a user terminal; the method comprises the following steps: a user terminal transmits pilot signals to base stations in each cooperative cell, each base station estimates and shares channel state information, acquires global channel state information and formulates a transmitting beam forming model; and the intelligent reflecting surface formulates a reflecting beam forming model, and the coefficients of transmitting beam forming and reflecting beam forming are obtained through modeling solution, so that interference suppression signals are formed. According to the method and the device, higher signal gain can be obtained when the distance between the cell base station and the corresponding user terminal is far, fairness among the user terminals is considered, mutual interference among the user terminals can be effectively reduced through joint optimization of sending beam forming and reflecting beam forming, and transmission efficiency of wireless communication transmission is improved.

Description

Multi-cell wireless communication method based on intelligent reflector
Technical Field
The application relates to the technical field of wireless communication, in particular to a multi-cell wireless communication method based on an intelligent reflector.
Background
Under the push of the emerging internet of things and the explosive growth of artificial intelligence applications, mobile cellular networks of the fifth generation (5G) and beyond need to meet various strict communication requirements, thereby being able to serve a large number of wireless devices. To this end, base stations are densely deployed to shorten the distance to user terminals, and Device-to-Device (D2D) communication enables traditional cellular network transmissions to provide more spectrum reuse opportunities. However, the presence of multiple base stations and D2D communication existing in 5G and above cellular networks also introduces severe signal interference to system user terminals, which is an urgent problem to be addressed.
The conventional solution is to utilize multiple-input multiple-output and inter-cell cooperative beamforming techniques. The multiple input multiple output is that a plurality of antennas are configured at a transmitter and a receiver, a plurality of parallel transmission channels are formed in space, and the capacity of the channels is improved without reducing the frequency spectrum utilization rate. The inter-cell cooperative beam forming means that the multi-antenna cooperative base stations share respective channel state information, then the optimal beam forming is calculated in a centralized manner, signals are separated from each other in space, and user terminals among different cells are prevented from interfering with each other. However, even a dense network using the above-described techniques has many problems. First, as the number of base stations and the number of transmit antennas increase, the cost of building base stations and corresponding radio frequency links also increases. Second, as the distance between the base stations is reduced, the user terminal is more likely to approach the edge of the cell, which makes the interference problem worse. Thirdly, the existence of the shelter is inevitable in the signal transmission process, which also causes the signal to be sheltered, and causes the problems of too small signal intensity, narrow transmission coverage range and the like.
Disclosure of Invention
The purpose of the application is to provide a multi-cell wireless communication method based on an intelligent reflecting surface, and the minimum user terminal signal-to-interference-and-noise ratio of a multi-cell system is maximized by setting the intelligent reflecting surface in multi-cell cooperation and jointly optimizing emission beam forming at a base station and reflection beam forming of the intelligent reflecting surface.
In order to realize the task, the following technical scheme is adopted in the application:
a multi-cell wireless communication method based on an intelligent reflecting surface aims at a system comprising a plurality of cooperative cells and the intelligent reflecting surface with a plurality of reflecting elements, wherein each cooperative cell is provided with a base station with a plurality of transmitting antennas and a user terminal with a single antenna; the method comprises the following steps:
a user terminal transmits pilot signals to base stations in each cooperative cell, and each base station estimates channel state information through the pilot signals and shares the channel state information with an intelligent reflecting surface and other base stations;
each base station acquires global channel state information according to the shared channel state information and formulates a transmitting beam forming model; the intelligent reflecting surface formulates a reflecting beam forming model according to the global channel state information, a transmitting beam forming coefficient and a reflecting beam forming coefficient are obtained through modeling solving, and the base station and the intelligent reflecting surface transmit corresponding transmitting beam forming and reflecting beam forming according to the transmitting beam forming coefficient and the reflecting beam forming coefficient;
the user terminal receives a superimposed signal of the transmit beamforming and the reflected beamforming.
Further, the estimating, by the base stations, the channel state information through the pilot signals includes:
each base station estimates the channel state information from the direct downlink link and the reflected link to the user terminal by utilizing channel reciprocity according to the received pilot signals; order to
Figure BDA0002297010170000021
Representing the channel matrix from base station i to the intelligent reflecting surface,
Figure BDA0002297010170000022
and
Figure BDA0002297010170000023
respectively representing the channel vectors from the intelligent reflecting surface to the user terminal i and from the base station k to the user terminal i, wherein
Figure BDA0002297010170000024
Representing a complex matrix of spatial size mxn; m is the number of antennas of the base station, and N is the number of reflecting elements on the intelligent reflecting surface;
the channel state information is denoted as fi、hi,kAnd Gi。
Further, the process of making the transmit beamforming model by each base station includes:
transmit beamforming by base stations i based on global channel state information
Figure BDA0002297010170000025
Setting a transmit signal siIs a random variable with a mean value of 0 and a variance of 1, which obey normal distribution, the transmission signal of each base station is
Figure BDA0002297010170000026
Figure BDA0002297010170000027
Representing a set of base stations.
Further, the process of making the reflection beam forming model comprises:
order to
Figure BDA0002297010170000028
representing a reflection beam forming made by an intelligent reflecting surface, wherein beta is more than or equal to βn1 or less and
Figure BDA0002297010170000029
respectively representing the reflection amplitude and the reflection phase shift of a reflecting element n on the intelligent reflecting surface, j representing an imaginary unit, exDenotes an exponential function with e as the base, and the nth element in v
Figure BDA00022970101700000210
Must satisfy
Figure BDA00022970101700000211
Wherein | vnI represents the pair vnAnd (4) taking a modulus value.
Further, the modeling solution obtains coefficients of transmit beamforming and coefficients of reflection beamforming, and includes:
and establishing a receiving signal model at the user terminal, establishing a signal to interference and noise ratio model of the user terminal by taking the interference as noise, and establishing a mathematical optimization problem according to the model, so as to solve a transmitting beam forming coefficient and a reflecting beam forming coefficient by taking the minimum signal to interference and noise ratio as an aim.
Further, the received signal model at the user terminal is represented as:
Figure BDA0002297010170000031
where v denotes reflected beam forming,. phi.i,k＝diag(fi H)Gk，Φi,i＝diag(fi H)Gi，Gk、GiRespectively representing the channel matrices from base station k, base station i to the intelligent reflecting surface, fiRepresenting the channel vector, h, from the intelligent reflecting surface to the user terminal ii,i、hi,kRespectively representing a channel vector from a base station i to a user terminal i and a channel vector from a base station k to the user terminal i; w is ai、wkRespectively representing the transmit beamforming, s, of base station i, base station ki、skRespectively representing the transmitted signals of base station i, base station k, niMeans that user i receives a mean value of 0 and a variance of σi 2White gaussian noise.
Further, the signal-to-interference-and-noise ratio model of the user equipment is expressed as:
Figure BDA0002297010170000032
further, the mathematical optimization problem is established and expressed as:
Figure BDA0002297010170000033
Figure BDA0002297010170000034
Figure BDA0002297010170000035
wherein alpha isiRepresenting a weight parameter, P, for a user terminal iiDenotes the maximum transmit power of base station i, v denotes reflection beamforming, v denotesnIs the n-th element in v, wiRepresenting the transmit beamforming of base station i and N being the number of reflective elements on the intelligent reflective surface.
Further, the solution method of the mathematical optimization problem adopts an alternating optimization algorithm based on semi-definite relaxation or an alternating optimization algorithm based on continuous convex approximation.
Further, the base station includes a first communication module, a decision model and a beam forming module, where the first communication module is configured to perform channel estimation to obtain channel state information or pilot signals from each user terminal, other base stations and an intelligent reflecting surface; the decision module calculates a transmitting beam forming coefficient according to the current global channel state information; the beam forming control module concentrates the transmitting energy in the corresponding direction according to the calculated transmitting beam forming coefficient to form a beam and transmit the beam;
the user terminal comprises a second communication module and a processing module, wherein the second communication module is used for receiving signals and transmitting pilot signals used for channel estimation; the processing module is used for decoding the received signals and acquiring information sent by the base station;
the intelligent reflecting surface comprises a reflecting array and a controller, wherein the controller comprises a control module and a third communication module, the reflecting array changes the resonant frequency of each reflecting element by loading an electronic control capacitor on the microstrip patch of each reflecting element so as to control the phase shift and the amplitude of a reflected signal; the third communication module is used for receiving the global channel state information sent by the base station and sending the information of the current reflection coefficient of the intelligent reflecting surface to the base station; and the control module adjusts the capacitance value of the electronic control capacitor of each microstrip patch according to the global channel state information, so as to control the phase shift and amplitude of the reflected beam forming.
The application has the following technical characteristics:
1. according to the method and the device, the intelligent reflecting surface is added in the original multi-cell cooperation, the reflecting wave beam forming is generated by adaptively adjusting parameters such as reflecting phase shift and amplitude on the intelligent reflecting surface, and the interference suppression and the signal enhancement are realized at the user terminal with serious interference by matching with the transmitting wave beam forming of the base station.
2. By utilizing the technical scheme of the application, even if the distance between the cell base station and the corresponding user terminal is far and the shelter exists, the higher signal gain can be obtained compared with the signal gain without the intelligent reflecting surface, the fairness among the user terminals is considered, and the mutual interference among the user terminals can be effectively reduced and the transmission efficiency of wireless communication transmission is improved by jointly optimizing the beam forming of the base station and the reflecting beam forming of the intelligent reflecting surface.
Drawings
FIG. 1 is a schematic flow diagram of the present application;
fig. 2 is a conceptual diagram of a system formed by a user terminal, a base station, and an intelligent reflector according to the present application;
FIG. 3 is a schematic structural diagram of a user terminal, a base station, and an intelligent reflector;
FIG. 4 is a graph of the relationship between the minimum SINR and the maximum transmission power of the base station when the user terminals are symmetrically distributed;
fig. 5 is a graph of the minimum sir at random distribution of ues versus the maximum transmit power of the bs.
Detailed Description
In the wireless communication transmission process of the multi-cell system, when too many obstacles exist between the user terminal and the base station, the signal strength is faded too much, which causes inefficient wireless communication transmission, and has the problems of small coverage, serious interference and the like. Therefore, the application provides a wireless communication method based on an intelligent reflecting surface, the method adds an intelligent reflecting surface formed by metamaterial near a user terminal, the intelligent reflecting surface is a reflecting array formed by a large number of cheap metamaterial reflecting elements, certain parameters such as phase shift, amplitude and the like can be superposed on an incident signal, so that the reflected signal and a direct signal are subjected to coherent superposition or inhibition at a receiving end of the user terminal, and the method has the advantages of easiness in deployment, low cost, light weight and the like. By setting the intelligent reflecting surface, beam forming of the multi-antenna base station and parameters such as reflection phase shift and amplitude of the intelligent reflecting surface are optimized in a combined mode, so that the signal-to-interference-and-noise ratio of the user terminal of the system is improved, interference among the user terminals is restrained, the spectrum efficiency is improved, and the like.
The application provides a cooperative multi-cell wireless communication method based on an intelligent reflecting surface, and the system aimed by the method comprises K cooperative cells and an intelligent reflecting surface with N reflecting elements, as shown in figure 1. Defining a set of cooperating cells as
Figure BDA0002297010170000051
The set of the reflection elements on the intelligent reflection surface is
Figure BDA0002297010170000052
Wherein each cooperating cell has a base station equipped with M transmit antennas and a single antenna user terminal, the set of base stations and user terminals is also denoted
Figure BDA0002297010170000053
Each base station only communicates with the corresponding user terminal in the cell, the intelligent reflecting surface is deployed at the edge of the cell, for example, the intelligent reflecting surface is installed on the wall of a building which is far away from the base station and has a direct-view path with the user terminal, and the strong reflecting signal enables the user terminal behind the shelter to receive the strong signal so as to assist the communication between the base station and the user terminal among the cells.
Referring to fig. 2, the base station part is composed of three modules, a first communication module, a decision module, and a beamforming module. The first communication module is mainly used for estimating channels and acquiring channel state information or pilot signals from each user terminal, other base stations and the intelligent reflecting surface. The decision module calculates a transmitting beam forming coefficient according to the current global channel state information; and the beam forming control module concentrates the transmitting energy in the corresponding direction according to the calculated specific numerical value of the beam forming to form a beam and transmit the beam.
The user terminal part is composed of a second communication module and a processing module. The second communication module is mainly used for receiving signals and transmitting pilot signals used for channel estimation; the processing module performs subsequent operations such as decoding on the received signal and the like to acquire information sent by the base station.
The intelligent reflective surface comprises a reflective array and a controller, wherein the controller comprises a control module and a third communication module. The reflective array is composed of a large number of low-cost printed dipoles, microstrip patches or other metamaterial reflective elements and a substrate. The reflector array changes the resonant frequency of each reflector element by loading an electronic control capacitor on the microstrip patch of each reflector element, thereby controlling the phase shift and amplitude of the reflected signal; the third communication module is used for receiving the global channel state information sent by the base station and sending the information of the current reflection coefficient of the intelligent reflecting surface to the base station; the control module adjusts the capacitance value of the electronic control capacitor of each microstrip patch according to the global channel state information, and then controls the phase shift and amplitude of the reflected beam forming.
On the basis of the above system, referring to fig. 3, the multi-cell wireless communication method based on the intelligent reflector of the present application includes the following steps:
step 1, user terminal transmits pilot signal to base station in each cooperation district
The pilot signals are used for the base station to carry out channel estimation, and when the user terminal needs to communicate with the base station, the pilot signals are transmitted to the base stations in all the cooperative cells. By transmitting the pilot signal, each base station can actually acquire the channel state information, thereby providing necessary channel information for subsequent formulation of transmitting and reflecting beam forming.
In this embodiment, a specific application example is given, and referring to fig. 1, in this example, 3 cells are included, and each cell has one base station and one user terminal. If a user terminal needs to obtain information from the base station, the user terminal needs to transmit a pilot signal to each base station through the second communication module, and then transmits the information according to the channel state information after the corresponding base station finishes estimating the channel.
And 2, each base station estimates channel state information through the pilot signal and shares the channel state information with the intelligent reflecting surface and other base stations.
Each base station estimates the channel state information from the downlink direct link and the reflected link to the user terminal by using channel reciprocity according to the received pilot signals, and it is assumed that each base station can perfectly estimate the actual channel.
Order to
Figure BDA0002297010170000061
Representing the channel matrix from base station i to the intelligent reflecting surface,
Figure BDA0002297010170000062
and
Figure BDA0002297010170000063
respectively representing the channel vectors from the intelligent reflecting surface to the user terminal i and from the base station k to the user terminal i, wherein
Figure BDA0002297010170000064
Representing a complex matrix of spatial size mxn; for convenience of illustration, in the same cooperative cell, the base station, the user terminal in the cooperative cell, and the cooperative cell are all represented by the same parameter, such as i or k, that is, the user terminal i and the base station i are the user terminal and the base station located in the cooperative cell i,
Figure BDA0002297010170000065
after obtaining the channel state information, each base station shares the channel state information and the current coefficient information of the transmitting beam forming with the intelligent reflecting surface and other base stations through the first communication module. The method specifically comprises the steps that the first communication module of the base station wirelessly communicates with the third communication module of the intelligent reflecting surface and the first communication modules of other base stations, and the exchange of channel state information is achieved. In the examples given in this application, the channel state informationInformation is represented as fi、hi,kAnd Gi，
Figure BDA0002297010170000071
And 3, each base station acquires global channel state information according to the shared channel state information and formulates a transmitting beam forming model.
After sharing the channel state information, each base station obtains global channel state information. Subsequently, the decision module of each base station i performs transmit beamforming according to the global channel state information
Figure BDA0002297010170000072
And assumes a transmitted signal siIs a random variable with a mean value of 0 and a variance of 1, which obey normal distribution, the transmission signal of each base station is
Figure BDA0002297010170000073
Here, it is set that the maximum transmission power P exists for each base stationiI.e. E (| x)i||2)＝||wi||2≤PiWhere E (-) represents a statistical expectation; each base station transmits a customized beam forming, and different beam forming causes different signal strengths received by different user terminals.
And 4, making a reflection beam forming model by the intelligent reflecting surface according to the global channel state information.
After the intelligent reflecting surface receives and obtains the global channel state information sent by the base stations and the vector information of the transmitting beam forming of each base station through the third communication module, parameters such as reflecting phase shift, amplitude and the like on the reflecting element are adjusted in a self-adaptive mode, so that different reflecting beam forming models are formulated, and the method specifically comprises the following steps:
order to
Figure BDA0002297010170000074
a control module for representing the intelligent reflecting surface makes a reflection beam forming, wherein, beta is more than or equal to 0n1 or less and
Figure BDA0002297010170000075
respectively representing the reflection amplitude and reflection phase shift of a reflective element n, j representing an imaginary unit, ex representing an exponential function with e as base, and the nth element in v
Figure BDA0002297010170000076
Must satisfy
Figure BDA0002297010170000077
Wherein | vnI represents the pair vnAnd (4) taking a modulus value. Here the superscript H denotes the conjugate transpose of the vector or matrix.
Thus, the reflected channel from base station k to user terminal i is vHdiag (f)i H)Gk＝vHΦi,kHere phii,k＝diag(fi H)Gk，GkRepresenting the channel matrix from the base station k to the intelligent reflecting surface; diag (x) denotes a diagonal matrix whose diagonal element is the corresponding element of x.
Hereinafter, different subscripts of a parameter indicate that the parameter corresponds to different user terminals or base stations, e.g. hi,kRepresents the channel vector from base station k to user terminal i, then hi,iThen represents the channel vector from base station i to user terminal i; gkRepresenting the channel matrix from base station k to the intelligent reflecting surface, GiA channel matrix from the base station i to the intelligent reflecting surface, etc., and the following explanation on the parameter of replacing the subscript is not repeated.
And 5, modeling and solving to obtain a transmitting beam forming coefficient and a reflecting beam forming coefficient, and transmitting corresponding transmitting beam forming and reflecting beam forming by the base station and the intelligent reflecting surface according to the transmitting beam forming coefficient and the reflecting beam forming coefficient.
In this step, by combining the transmit beam forming model and the reflected beam forming model established in steps 3 and 4, the decision module of the base station and the control module of the intelligent reflecting surface solve the corresponding transmit beam forming coefficient and the reflected beam forming coefficient with the purpose of maximizing the minimum signal-to-interference-and-noise ratio of all user terminals in the system.
First, a received signal model at user terminal i is established:
Figure BDA0002297010170000081
wherein n isiMeans that user i receives a mean of 0 and a variance of
Figure BDA0002297010170000082
White gaussian noise. The second term of the above equation is interference from other cooperative cells, and by regarding the interference as noise, the signal to interference and noise ratio model received by the user terminal i is:
Figure BDA0002297010170000083
the mathematical optimization problem thus characterized is:
Figure BDA0002297010170000084
Figure BDA0002297010170000085
Figure BDA0002297010170000086
wherein alpha isiAnd the weight parameter of the user terminal i is expressed, and the fairness among the K user terminals is represented. To facilitate the optimization solution, an auxiliary variable t is first introduced, and the problem (P1) is restated as an equivalent problem as follows:
Figure BDA0002297010170000087
Figure BDA0002297010170000088
Figure BDA0002297010170000089
Figure BDA00022970101700000810
since the optimization variables transmit beamforming and reflected beamforming are coupled together at the signal to interference and noise ratio, the problem (P1) or (P1.1) is not a convex optimization problem and is difficult to solve. Next, an alternate optimization method is presented to solve this problem. In particular, transmit beamforming and reflected beamforming are each optimized at another fixed time. For convenience, order
Figure BDA0002297010170000091
And v(l)Representing beamforming at the l-th iteration. The specific solving process is as follows:
setting a combined channel vector from a base station k to a user terminal i as
Figure BDA0002297010170000092
Then the problem (P1.1) is equivalent to:
Figure BDA0002297010170000093
Figure BDA0002297010170000094
Figure BDA0002297010170000095
obviously, the problem (P2) is still not a convex problem. To solve (P2), fix t, the following feasibility problem (P2.1) is obtained
(P2.1):find{wi}
Figure BDA0002297010170000096
Figure BDA0002297010170000097
Let t*Is the optimal solution of the problem (P2). If the problem (P2.1) is feasible given t, then t ≦ t*Otherwise t > t*. The problem (P2) can therefore be solved for t by bisection. In particular, let the matrix
Figure BDA0002297010170000098
The ith row and the jth column of elements of
Figure BDA0002297010170000099
Figure BDA00022970101700000910
Representing a vector where only the ith element is 1 and all the others are 0.
(P2.1) the equivalent transformation becomes the following second order cone programming problem:
(P2.2):find{wi}
Figure BDA00022970101700000911
Figure BDA00022970101700000912
Figure BDA00022970101700000913
the problem (P2.2) can be solved with a specialized software tool CVX.
(II) then fixing the derived transmit beamforming { w }iH to optimize the reflected beam shaping v. Let ci.k＝Φi,kwk，
Figure BDA00022970101700000914
And
Figure BDA00022970101700000915
comprises the following steps:
Figure BDA0002297010170000101
accordingly, the problem (P1.1) can be expressed as
Figure BDA0002297010170000102
Figure BDA0002297010170000103
Figure BDA0002297010170000104
Next, the solution is solved by using semi-definite relaxation and continuous convex approximation methods respectively (P3), and the specific steps of the alternating optimization algorithm are given.
(1) An alternative optimization algorithm based on semi-definite relaxation:
order to
Figure BDA0002297010170000105
And
Figure BDA0002297010170000106
and is provided with
Figure BDA0002297010170000107
Then there is a constraint V? 0 and rank (V) ≦ 1, wherein V? 0 denotes that the matrix V is a semi-positive definite matrix, and rank (V) denotes the rank of the matrix V. By applying semi-definite relaxation, the non-convex constraint rank (V) is removed less than 1, and then (P3) is made the following problem:
Figure BDA0002297010170000108
Figure BDA0002297010170000109
Figure BDA00022970101700001010
VN+1,N+1＝1
V？0.
the problem (P3.1) is the same as the solution to the problem (P2). In particular, when binary solving for t, the following feasibility problem may be solved:
(P3.2):find V
Figure BDA00022970101700001011
Figure BDA00022970101700001012
VN+1,N+1＝1
V？0.
the problem (P3.2) can be solved with a specialized software tool CVX. After the solution (P3), if rank (V) > 1 is obtained, it is necessary to perform gaussian randomization on V, that is: firstly, the characteristic value of V is decomposed into V ═ U ∑ UHWherein U is unitary matrix and Sigma is diagonal matrix. Get
Figure BDA0002297010170000111
Wherein r is a circularly symmetric complex Gaussian random vector with a mean value of 0 and a covariance matrix as a unit matrix. Then, get
Figure BDA0002297010170000112
Wherein [ x ]](1:N)The first N elements of the vector x are taken. Multiple gaussian randomization, take v that maximizes the minimum signal-to-interference-and-noise ratio as the solution to the problem (P3).
Therefore, the problem (P1) can be solved by an alternative optimization algorithm based on semi-definite relaxation, the specific steps being shown by algorithm 1:
Figure BDA0002297010170000113
(2) an alternating optimization algorithm based on successive convex approximation:
by means of a user terminal
Figure BDA0002297010170000114
Defining an auxiliary function:
Figure BDA0002297010170000115
accordingly, in the first iteration/the reflected beam-forming v can be updated by the following problem:
Figure BDA0002297010170000121
Figure BDA0002297010170000122
however, the problem (P4) is not convex. By using a first order taylor expansion, there are:
Figure BDA0002297010170000123
the problem (P4) can thus be approximated as the following:
Figure BDA0002297010170000124
Figure BDA0002297010170000125
Figure BDA0002297010170000126
the problem (P4.1) is a convex problem and can therefore be solved with a specialized software tool CVX. By solving for (P4.1), a feasible solution of (P4) can be obtained. The specific steps of the successive convex approximation based alternative optimization algorithm are given below, and are shown by algorithm 2:
Figure BDA0002297010170000127
finally, the coefficients of the transmit beam forming and the coefficients of the reflection beam forming (i.e. specific values) in steps 3 and 4 can be obtained by an alternate iteration method according to algorithm 1 or algorithm 2, and the beam forming module of the base station and the control module of the intelligent reflective surface send out corresponding beam forming.
And 6, the user terminal receives the superposed signal of the transmitting beam forming from the base station and the reflecting beam forming from the intelligent reflecting surface.
After the base station and the intelligent reflecting surface send the transmit beam forming and the reflection beam forming, the second communication module of the user terminal may receive a superimposed signal of the transmit beam forming and the reflection beam forming, where the signal is a signal from which interference has been suppressed.
With the development of 5G and the Internet of things, base stations are greatly increased to provide more and more user terminal access requirements, the cooperation among multi-cell base stations can reduce more and more serious interference problems to a certain extent, and the increased intelligent reflecting surface can assist the base stations to improve the signal strength and suppress interference and improve the communication quality.
For the method proposed in the present application, the inventors performed corresponding performance simulation and control experiment.
Fig. 4 shows a relationship curve between the minimum signal-to-interference-and-noise ratio of the ue and the maximum transmission power of the bs when the ue coordinates are (-5m,0), (5m,0), and (-0,5m), the bs coordinates are (-100m,0), (100m,0), and (-0,100m), and the coordinates of the intelligent reflector are (0, -10m) in the system structure designed in this application. The parameters are designed as follows: the transmitting antenna M of the base station is 2, the number of reflecting elements on the intelligent reflecting surface is 20, the noise power of each user is-80 dBm, and the path fading model
Figure BDA0002297010170000131
d represents the distance between the user terminal and the base station, reference distance d0＝1m，C0the path fading index alpha from the base station to the user terminal, from the base station to the intelligent reflecting surface and from the intelligent reflecting surface to the user terminal is 3.6, 2 and 2.5 respectively, and the base station is setThe channel from the base station to the intelligent reflecting surface is a direct-path channel. As can be seen from fig. 4, the minimum signal to interference plus noise ratio of the user terminal is greater when the intelligent reflecting surface is added than when the intelligent reflecting surface is not added.
Fig. 5 is a graph of the minimum signal-to-interference-and-noise ratio versus the maximum transmission power of the base station when the user terminals are randomly distributed in the regions with the vertices of the triangle being (-100m,0), (100m,0), and (-0,100 m). Other parameters are the same as those of fig. 4. As can be seen from fig. 5, the optimization performance of the joint transmit and reflect beam forming proposed by the present solution is greatly improved compared to the case without the intelligent reflecting surface.

Claims (10)

1. A multi-cell wireless communication method based on an intelligent reflecting surface is characterized in that the method aims at a system comprising a plurality of cooperative cells and the intelligent reflecting surface with a plurality of reflecting elements, wherein each cooperative cell is provided with a base station with a plurality of transmitting antennas and a user terminal with a single antenna; the method comprises the following steps:
a user terminal transmits pilot signals to base stations in each cooperative cell, and each base station estimates channel state information through the pilot signals and shares the channel state information with an intelligent reflecting surface and other base stations;
each base station acquires global channel state information according to the shared channel state information and formulates a transmitting beam forming model; the intelligent reflecting surface formulates a reflecting beam forming model according to the global channel state information, a transmitting beam forming coefficient and a reflecting beam forming coefficient are obtained through modeling solving, and the base station and the intelligent reflecting surface transmit corresponding transmitting beam forming and reflecting beam forming according to the transmitting beam forming coefficient and the reflecting beam forming coefficient;
the user terminal receives a superimposed signal of the transmit beamforming and the reflected beamforming.
2. The method of claim 1, wherein the estimating the channel state information by the base stations via pilot signals comprises:
each base station estimates the channel state information from the direct downlink link and the reflected link to the user terminal by utilizing channel reciprocity according to the received pilot signals; order to
Figure FDA0002297010160000011
Representing the channel matrix from base station i to the intelligent reflecting surface,
Figure FDA0002297010160000012
and
Figure FDA0002297010160000013
respectively representing the channel vectors from the intelligent reflecting surface to the user terminal i and from the base station k to the user terminal i, wherein
Figure FDA0002297010160000014
Representing a complex matrix of spatial size mxn; m is the number of antennas of the base station, and N is the number of reflecting elements on the intelligent reflecting surface;
the channel state information is denoted as fi、hi,kAnd Gi。
3. The method of claim 1, wherein the step of making the transmit beamforming model by each base station comprises:
transmit beamforming by base stations i based on global channel state information
Figure FDA0002297010160000015
Setting a transmit signal siIs a random variable with a mean value of 0 and a variance of 1, which obey normal distribution, the transmission signal of each base station is
Figure FDA0002297010160000016
Figure FDA0002297010160000017
Representing a set of base stations.
4. The intelligent reflector-based multi-cell wireless communication method as claimed in claim 1, wherein the process of formulating the reflection beam forming model comprises:
order to
Figure FDA0002297010160000021
representing a reflection beam forming made by an intelligent reflecting surface, wherein beta is more than or equal to βn1 or less and
Figure FDA0002297010160000022
respectively representing the reflection amplitude and the reflection phase shift of a reflecting element n on the intelligent reflecting surface, j representing an imaginary unit, exDenotes an exponential function with e as the base, and the nth element in v
Figure FDA0002297010160000023
Must satisfy
Figure FDA0002297010160000024
Wherein | vnI represents the pair vnAnd (4) taking a modulus value.
5. The method of claim 1, wherein the modeling solution for obtaining the coefficients of transmit beamforming and the coefficients of reflected beamforming comprises:
and establishing a receiving signal model at the user terminal, establishing a signal to interference and noise ratio model of the user terminal by taking the interference as noise, and establishing a mathematical optimization problem according to the model, so as to solve a transmitting beam forming coefficient and a reflecting beam forming coefficient by taking the minimum signal to interference and noise ratio as an aim.
6. An intelligent reflector-based multi-cell wireless communication method as claimed in claim 5, wherein the received signal model at the user terminal is represented as:
Figure FDA0002297010160000025
where v denotes reflected beam forming,. phi.i,k＝diag(fi H)Gk，Φi,i＝diag(fi H)Gi，Gk、GiRespectively representing the channel matrices from base station k, base station i to the intelligent reflecting surface, fiRepresenting the channel vector, h, from the intelligent reflecting surface to the user terminal ii,i、hi,kRespectively representing a channel vector from a base station i to a user terminal i and a channel vector from a base station k to the user terminal i; w is ai、wkRespectively representing the transmit beamforming, s, of base station i, base station ki、skRespectively representing the transmitted signals of base station i, base station k, niMeans that user i receives a mean of 0 and a variance of
Figure FDA0002297010160000027
White gaussian noise.
7. The method of claim 5, wherein the SINR model of the UE is expressed as:
Figure FDA0002297010160000026
8. the method of claim 5, wherein the mathematical optimization problem is expressed as:
Figure FDA0002297010160000031
Figure FDA0002297010160000032
Figure FDA0002297010160000033
wherein alpha isiRepresenting a weight parameter, P, for a user terminal iiDenotes the maximum transmit power of base station i, v denotes reflection beamforming, v denotesnIs the n-th element in v, wiRepresenting the transmit beamforming of base station i and N being the number of reflective elements on the intelligent reflective surface.
9. The intelligent reflector-based multi-cell wireless communication method as claimed in claim 1, wherein the solution method of the mathematical optimization problem adopts an alternating optimization algorithm based on semi-definite relaxation or an alternating optimization algorithm based on continuous convex approximation.
10. The method of claim 1, wherein the base station comprises a first communication module, a decision-making model and a beam-forming module, wherein the first communication module is configured to perform channel estimation and obtain channel state information or pilot signals from each ue, other bss and the intelligent reflector; the decision module calculates a transmitting beam forming coefficient according to the current global channel state information; the beam forming control module concentrates the transmitting energy in the corresponding direction according to the calculated transmitting beam forming coefficient to form a beam and transmit the beam;
the user terminal comprises a second communication module and a processing module, wherein the second communication module is used for receiving signals and transmitting pilot signals used for channel estimation; the processing module is used for decoding the received signals and acquiring information sent by the base station;
the intelligent reflecting surface comprises a reflecting array and a controller, wherein the controller comprises a control module and a third communication module, the reflecting array changes the resonant frequency of each reflecting element by loading an electronic control capacitor on the microstrip patch of each reflecting element so as to control the phase shift and the amplitude of a reflected signal; the third communication module is used for receiving the global channel state information sent by the base station and sending the information of the current reflection coefficient of the intelligent reflecting surface to the base station; and the control module adjusts the capacitance value of the electronic control capacitor of each microstrip patch according to the global channel state information, so as to control the reflection phase shift and amplitude.
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