CN113852402B - IRS (intelligent communications system) -assisted NOMA-MIMO (non-multiple input multiple output) high-capacity access method - Google Patents

IRS (intelligent communications system) -assisted NOMA-MIMO (non-multiple input multiple output) high-capacity access method Download PDF

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CN113852402B
CN113852402B CN202111040174.7A CN202111040174A CN113852402B CN 113852402 B CN113852402 B CN 113852402B CN 202111040174 A CN202111040174 A CN 202111040174A CN 113852402 B CN113852402 B CN 113852402B
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irs
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CN113852402A (en
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张崇富
刘斯年
谭巍
黄欢
邱昆
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University of Electronic Science and Technology of China
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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
    • H04B7/0413—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
    • H04B7/08—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
    • H04B7/0854—Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
    • 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]
    • 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
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
    • 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

Abstract

The invention discloses an IRS (intelligent resilient multimedia system) -assisted NOMA (non-multiple input multiple output) high-capacity access method, belonging to the technical field of wireless communication. The invention uses a 2D-DFT codebook to quantize IRS reflection phase shift, and converts the joint optimization problem of active and passive precoding in an IRS-assisted MIMO system into an optimal code word optimization problem. Thereby solving the problem of integer programming which is difficult to solve by the traditional scheme. Through reasonable user grouping, each user can be served by the optimal beam mode, thereby avoiding the use of a suboptimal mode and improving the spectrum efficiency. The limitation of the number of RF links to large-scale access is broken, and the cost for deploying a large number of RF chains is saved. The invention provides a simple mode to combine RIS and NOMA-MIMO technology, and improves the system performance of NOMA-MIMO, especially the performance of remote users, by using the potential of IRS to reconstruct channel vectors.

Description

IRS (intelligent resilient framework) -assisted NOMA (non-multiple input multiple output) high-capacity access method
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an Intelligent Reflector (IRS) -assisted NOMA-MIMO high-capacity access method.
Background
IRS is a subversive technology in the field of wireless communications to improve the spectral and energy efficiency of communication systems in a low cost manner. The IRS is composed of a large number of reconfigurable passive reflection elements, the amplitude and the phase of a reflection signal can be changed by controlling a reflection coefficient, and due to the obvious passive beam forming gain, the IRS can be introduced into a millimeter wave communication system to support blind spot coverage and local hot spot scenes, so that the coverage range is expanded.
Non-orthogonal multiple access (NOMA) is a key technology of future wireless communication, and has remarkable advantages in the aspects of improving the spectrum efficiency of a system, supporting large-scale access and the like. The basic principle of NOMA is to deploy Superposition Coding (SC) and Successive Interference Cancellation (SIC) at the transmitting end and the receiving end, respectively, so that multiple users can share the same radio resource.
NOMA has a higher spectral efficiency than traditional Orthogonal Multiple Access (OMA), especially in situations where the user channel gain difference is large. From a spatial multiplexing point of view, NOMA can serve multiple users in the same direction with the same beam, which is difficult to handle in conventional beamforming. However, in the NOMA scheme, if the user channel vectors are not "aligned", performance loss is caused, and an ideal situation that a plurality of user channel vectors are "aligned" often does not occur in an actual communication scene. In conventional wireless communication systems, the channel vector of the user is fixed, which limits the performance of NOMA. The IRS can be simply deployed between a base station and a user, a reflection channel is added, equivalent channel vectors are adjusted, the potential of artificially changing the equivalent channel vectors is achieved, and the characteristics bring more advantages to an IRS-assisted NOMA communication system. In the current IRS-assisted communication system research, the idea of alternative optimization is mainly adopted to process the joint optimization of the problems of active beam forming, passive beam forming and the like. Unlike conventional MIMO systems, in IRS-assisted NOMA-MIMO systems, not only does joint optimization of active beamforming, passive beamforming and power allocation be required, but also an integer programming problem of user grouping is involved, whereas convex optimization is difficult to solve the integer optimization problem.
Disclosure of Invention
The invention provides an IRS-assisted NOMA-MIMO large-capacity access method, which introduces IRS into a NOMA-MIMO system in a simple mode.
The technical scheme adopted by the invention is as follows:
an IRS-assisted NOMA-MIMO large-capacity access method comprises the following steps:
step S1: quantizing IRS reflection phase shift by a codebook;
reflecting surface IRS-based reflecting element number M R Configuring a two-dimensional discrete Fourier transform (2D-DFT) codebook:
Figure BDA0003248982940000021
wherein the codebook +>
Figure BDA0003248982940000022
Any column v of s Called a codeword, and codebooks>
Figure BDA0003248982940000023
Is the s-th column v s The t-th element of (2): />
Figure BDA0003248982940000024
Wherein j represents an imaginary unit, the function floor (x) represents the maximum integer less than or equal to x, e represents a natural base number, and the parameter W 2 ＝M R ；/>
Slave codebook
Figure BDA0003248982940000025
Selecting the code word that maximizes the spectral efficiency of the system as the reflection phase shift of the IRS, based on the selected code word v s Resulting in a phase shift matrix Φ = diag (v) s )；
The channel vector for user k is defined as: h is k ＝h RU,k ΦH AR +h AU,k ；
Wherein h is RU,k Representing the channel vector between IRS and user k, H AR Representing the channel matrix between the base station and the IRS, h AU,k Representing a channel vector between a base station and a user K, wherein the user number K =1,2, and K represents the number of users;
step S2: simulating precoding based on a codebook;
the codebook for the analog precoding is as follows:
Figure BDA0003248982940000026
wherein, N T Denotes the number of base station antennas, M denotes the number of beam patterns that can be supported, w m′ Represents the M 'th codeword, and M' =1, \ 8230m, each codeword corresponding to one beam pointing direction;
finding out matched wave beam mode for each user to obtain estimated simulation precoding matrix
Figure BDA0003248982940000027
And step S3: grouping users;
dividing users with the same optimal beam pattern into the same group, serving by one beam pattern, and defining the user with the highest channel gain in the nth beam as the mth beam n A user, with dimension N T ×N RF The analog precoding matrix of (a) is represented as:
Figure BDA0003248982940000028
wherein, N RF Represents the number of RF (Radio Frequency) links;
and step S4: digital pre-coding;
obtaining the equivalent channel of each user through analog precoding:
Figure BDA0003248982940000029
defining the user with highest channel gain in the nth beam as the mth beam n For each user, the equivalent channel matrix is:
Figure BDA00032489829400000210
and N is RF ×N RF The digital precoding matrix of (a) is:
Figure BDA0003248982940000031
obtaining the digital pre-coding vector of the nth wave beam through normalization processing
Figure BDA0003248982940000032
Wherein N =1, \ 8230, N RF ；
Step S5: configuring the optimal power distribution of each user based on a pre-configured power distribution mode to obtain the transmitting power of each user of each wave beam;
step S6: ergodic codebook
Figure BDA0003248982940000033
Finding an optimal mode;
traverse M R Each code word respectively calculates the frequency spectrum efficiency R of the beam direction corresponding to each code word sum Based on spectral efficiency R sum Obtaining a phase shift matrix phi by the highest code word;
wherein the content of the first and second substances,
Figure BDA0003248982940000034
/>
R m,n representing the speed, R, of the mth user of the nth beam m,n ＝log 2 (1+γ m,n ) Wherein γ is m,n The SINR of the mth user representing the nth beam,
Figure BDA0003248982940000035
h m,n channel, p, representing mth user of nth beam m,n Representing the transmission power of different users of different beams, i.e. p m,n Represents the transmit power of the ith user of the nth beam by an intermediate amount +>
Figure BDA0003248982940000036
p i,n Representing the transmission power, p, of the ith user of the nth beam j,t Representing the transmission power of the t user of the j beam, d j A digital precoding vector, S, representing the jth beam j I denotes the number of users of the jth beam, σ 2 Representing the noise variance.
Further, in step S2, a final orthogonal matching manner is adopted to find a matched beam pattern for each user.
Further, in step S5, the power allocation manner is a dynamic power allocation manner.
The technical scheme provided by the embodiment of the invention at least has the following beneficial effects:
(1) The joint optimization problem of active and passive precoding in an IRS-assisted MIMO system is transformed into an optimal codeword optimization problem by quantizing IRS reflection phase shifts using a 2D-DFT codebook. Therefore, the problem of integer programming which is difficult to solve by the traditional scheme is solved.
(2) The deployment of NOMA enables one beam to serve multiple users, and each user can be served by the optimal beam pattern through reasonable user grouping, thereby avoiding the use of suboptimal patterns and improving the spectrum efficiency. The limitation of the number of the RF links to large-scale access is broken, and the cost for deploying a large number of RF chains is saved.
(3) The invention provides a simple mode to combine RIS and NOMA-MIMO technology, and improves the system performance of NOMA-MIMO, especially the performance of remote users, by using the potential of IRS to reconstruct channel vectors.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of a NOMA-MIMO millimeter wave communication system with IRS assistance in an embodiment of the present invention
Fig. 2 is a structure of a millimeter wave MIMO system according to an embodiment of the present invention, where 2 (a) is an all-digital MIMO structure, and 2 (b) is a hybrid precoding structure;
FIG. 3 is a schematic diagram of a deployment of an IRS assisted NOMA-MIMO system in an embodiment of the present invention;
FIG. 4 is a beam pattern in an embodiment of the present invention;
FIG. 5 is a simulation result of an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The embodiment of the invention provides an IRS-assisted NOMA-MIMO high-capacity access method, which converts a complex non-convex optimization problem into a simple optimal code word selection problem by quantizing the reflection phase shift of an IRS by using a two-dimensional discrete Fourier transform (2D-DFT) codebook, thereby avoiding a mixed integer optimization process which is difficult to solve and introducing the IRS into a NOMA-MIMO system in a simple mode.
The access method provided by the embodiment of the invention is applied to the NOMA-MIMO system shown in figure 1, and the system mainly comprises a system configured with N T Root antenna, N RF A base station with RF (radio frequency) chains, K single-antenna users, and an IRS. Wherein IRS comprises M R A passive reflection unit and a controller connected with the passive reflection unit. The controller may dynamically adjust the reflection coefficient of each reflection unit to intelligently reconstruct the wireless communication environment. Fig. 2 is a structural diagram of a millimeter wave MIMO system, where fig. 2 (a) is an all-digital MIMO structure and fig. 2 (b) is a hybrid precoding structure. Each antenna in the all-digital MIMO structure is connected with one RF chain, so the number of transmitting antennas is equal to the number of RF chains, and this structure will deploy a large number of expensive RF chains, raising the cost of hardware, and the deployment of a large number of RF chains will cause extra energy consumption, especially in a large-scale MIMO system. The hybrid precoding is composed of analog precoding and digital precoding, and each RF chain is connected with all N antennas through phase shifters, so that deployment of a large number of RF chains is avoided. In order to reduce the cost, in the embodiment of the invention, a hybrid precoding structure is adopted.
In order to better explain the technical solution of the embodiment of the present invention, a brief description is first given of the technical derivation process of the embodiment of the present invention.
In a MIMO system based on hybrid precoding, the number of beams cannot exceed the number of RF chains, and the deployment of NOMA allows multiple users to be served per beam. Let S n Set of users serving the nth beam, | S n L is the number of users of the nth beam, where g =1,2 \ 8230n RF In the nth beam
Figure BDA0003248982940000051
The signal received by the mth user of the n groups is:
Figure BDA0003248982940000052
wherein h is m,n Denotes the channel of the mth user of the nth beam, the superscript "H" denotes the conjugate, w n A codeword representing the nth beam, A is an analog precoding matrix, d is a digital precoding vector, indexed by a specifier, d i A digital precoding vector representing the ith beam, d m A digital precoding vector, | S, representing the mth user j I denotes the number of users of the jth beam, s i,j Signal, s, representing the transmission of the jth user of the ith beam m,n Is the transmitted signal of the mth user of the nth beam, E { | s m,n | 2 =1,e { } denotes mathematical expectation, p m,n Is the power of the mth user of the nth beam, n m,n ～
Figure BDA0003248982940000053
Obeying a mean value of 0 and a variance of σ 2 Additive White Gaussian Noise (AWGN). The SINR (Signal to Interference plus Noise Ratio) of the mth user of the nth beam is expressed as:
Figure BDA0003248982940000054
wherein the content of the first and second substances,
Figure BDA0003248982940000055
/>
the velocity of the mth user of the nth beam is:
R m,n ＝log 2 (1+γ m,n ) (3)
the spectral efficiency is:
Figure BDA0003248982940000056
the goal is to optimize active beamforming, passive beamforming, power allocation to maximize the spectral efficiency of the system. The optimization problem can be expressed as:
Figure BDA0003248982940000061
wherein P represents the transmitting power of the base station, phi represents the reflection phase shift matrix of the IRS, the constraint condition C1 represents that the sum of the transmitting power does not exceed the transmitting power of the base station, and the constraint condition C2 represents that the reflection phase shift of the IRS does not exceed the codebook
Figure BDA0003248982940000062
Constraint C3 indicates that the transmission power is a positive number, constraint C4 is a constant modulus constraint, and constraint C5 indicates that the analog precoding matrix is selected from codebook F.
1. Codebook quantization IRS reflection phase shift
An acquisition mode for quantizing the IRS reflection phase shift matrix Φ is given below.
Suppose IRS is defined by M R A reflection element, wherein M R ＝W 2 The 2D-DFT codebook may be expressed as:
Figure BDA0003248982940000063
wherein the content of the first and second substances,
Figure BDA0003248982940000064
is called a code word, v s Represents->
Figure BDA0003248982940000065
And v is the element of the s-th column s The t-th element of (2):
Figure BDA0003248982940000066
wherein floor (x) represents the largest integer of x or less.
By quantizing IRS through a codebook, the convex optimization problem is converted into the problem of selecting the optimal code word in a finite set, namely the method can be used for solving the problem of selecting the optimal code word from the limited set
Figure BDA0003248982940000067
The code word that maximizes the spectral efficiency of the system is selected as the reflection phase shift of the IRS, e.g., Φ = diag (v) s )。
After the IRS is deployed, the signal received by the user consists of a direct link signal transmitted by the base station and an IRS reflected signal. Given a phase shift matrix Φ, the channel vector for user k can be represented as:
h k ＝h RU,k ΦH AR +h AU,k (8)
wherein h is RU,k Is the channel vector between IRS and user k, H AR Is the channel matrix between the base station and the IRS, h AU,k Is the channel vector between the base station and user k, the channel matrix H = [ H ] 1 ,h 2 ,...h K ]。
2. Codebook-based analog precoding
Hybrid beamforming based on channel vectors of a synthesized channel, wherein a codebook implementing analog precoding may be represented as:
Figure BDA0003248982940000071
wherein j is 2 =1, m is the number of beam patterns that can be supported to cover all directions. One beam pattern is defined as one codeword, w, in deployed hybrid beamforming m Representing the mth (M =1, \ 8230;, M) codeword. Each codeword corresponds to a beam pointing direction. In the embodiment, the method is widely applied to the prior artThe hybrid precoding algorithm of millimeter wave channels, orthogonal Matching Pursuit (OMP), finds the optimal beam pattern for each user, and its process is summarized as algorithm 1. In Algorithm 1, the optimal precoding F for each user opt (k) The codebook corresponding to the optimal beam mode selected each time is formed into N through singular value decomposition T xK matrix
Figure BDA0003248982940000072
The algorithm 1 is specifically as follows:
inputting: a channel matrix H, a codebook F and a user number K;
and (3) outputting:
Figure BDA0003248982940000073
step (1): initializing a matrix
Figure BDA0003248982940000074
Its initial value is null;
step (2): traverse the channel vector h for each user k The following calculation processing is performed:
for channel vector h k Singular value decomposition is carried out:
Figure BDA0003248982940000075
calculating based on the decomposition result:
F opt (k)＝V k (:,1)，Ψ k ＝F H F opt (k)，
Figure BDA0003248982940000076
wherein, the user number K =1, \8230, K represents the number of users, V k (: 1) represents a specific column of the matrix, i.e., matrix V k The first column of (A), F (: u) represents the u-th column of F.
3. User grouping
In the conventional OMA scheme, one beam can serve only one user, and the number of users that can be served cannot exceedNumber of RF chains, i.e. K.ltoreq.N RF If multiple users select the same optimal beam pattern, it is inevitable that users will adopt a sub-optimal pattern. Different users can be served by the same beam in the NOMA scheme, all the users can be guaranteed to be served by the optimal beam mode through reasonable grouping, the limitation of the number of RF chains to large-scale access is broken, namely K is more than or equal to N RF 。
In the embodiment of the invention, users with the same optimal beam pattern are divided into the same group and are served by one beam pattern. The user channels in the same group are highly correlated, so that the channel of one of the users can be used as the channel of the group, and the user channel vector with the highest channel gain is generally used as the channel of the group. Suppose that the user with the highest channel gain in the nth beam is the mth beam n Each user (1 ≦ m n ≤K)，N T ×N RF Analog precoding matrix
Figure BDA0003248982940000081
4. Digital pre-coding.
In order to reduce the interference between users, a Zero Forcing (ZF) precoding method is adopted for digital precoding. With analog precoding, the equivalent channel of K users can be represented as
Figure BDA0003248982940000082
Wherein K =1,2. Suppose that the user with the highest channel gain in the nth beam is the mth beam n The users are:
Figure BDA0003248982940000083
N RF ×N RF the digital precoding matrix of (c) is:
Figure BDA0003248982940000084
normalized, the digital precoding vector for the nth beam can be written as:
Figure BDA0003248982940000085
5. power distribution
In the embodiment of the invention, the optimal power distribution is obtained by using a dynamic power distribution algorithm proposed in documents (B.Wang, L.Dai, Z.Wang, N.Ge, and S.Zhou, "Spectrum and energy-efficiency beam space MIMO-NOMA for millimeter-wave communications using lens array," IEEE J.Sel.areas communication., vol.35, no.10, pp.2370-2382, oct.2017.). In the NOMA scheme, more power is allocated to users with lower channel gain, less power is allocated to users with higher channel gain, and the signals of the users with higher channel gain are considered as noise when the users with lower channel gain are decoded. Therefore, not only can a higher signal-to-noise ratio be achieved, but also fairness among users is guaranteed.
6. The 2D-DFT codebook is traversed to find the optimal pattern.
Traverse M R And (3) calculating the system spectral efficiency of each mode according to the expressions (2), (3) and (4), and selecting one code word with the highest spectral efficiency as the reflection phase shift of the IRS.
Examples
Considering an IRS-assisted NOMA-MIMO system operating at 35GHz, the number of base station antennas N T =64,irs reflector number M R =49, number of users K =6, σ 2 = 110dBm. As shown in FIG. 3, the 6 single-antenna users are uniformly distributed in a semi-ring area with IRS as the center, and the semi-ring inner radius r 1 =5m, outer radius r 2 =10m. The base station is located at (0, 0), and the intelligent reflection surface is located at (0, 50).
In this embodiment, an IRS-assisted NOMA-MIMO large capacity access method of the present invention includes the following steps:
s1, IRS consists of 49 reflection elements, so a 49 × 49 2D-DFT codebook can be expressed as:
Figure BDA0003248982940000091
wherein the content of the first and second substances,
Figure BDA0003248982940000092
is called a codeword, is asserted>
Figure BDA0003248982940000093
The tth element of the tth column of (1) is:
Figure BDA0003248982940000094
using the 2D-DFT codebook described above
Figure BDA0003248982940000095
Quantizing from>
Figure BDA0003248982940000096
And selecting a code word as the reflection phase shift of the IRS to obtain a phase shift matrix phi.
S2, simulating precoding based on codebook
The wireless channel of the millimeter wave band is modeled according to a Saleh-Valenzuela model to obtain a channel matrix and a channel vector H of a base station-IRS, a base station-user k and a user k-IRS AR ，h AU,k ，h RU,k . According to the phase shift matrix Φ selected in S1, the user k composite channel vector can be represented as:
h k ＝h RU,k ΦH AR +h AU,k
performing hybrid beamforming based on a channel vector of a synthesized channel, wherein a codebook for realizing analog precoding is as follows:
Figure BDA0003248982940000097
f can support 64 beam patterns,
Figure BDA0003248982940000098
by algorithm 1, areEach user finds the optimal beam pattern. Selected code words form an analog precoding matrix>
Figure BDA0003248982940000099
Figure BDA00032489829400000910
Is a 64 x 6 matrix.
S3, grouping users
Users that choose the same optimal beam pattern are grouped into the same group, served by the same beam pattern. Fig. 4 shows 5 optimal beam patterns selected in S2 by 6 users in one simulation, and the number of required RF chains is equal to the number of packets, i.e., N RF And (5). To better describe the embodiment of the present invention, the following steps adopt a simulation process as shown in fig. 4. Wherein, the users 1 to 6 respectively select the 7 th, 18 th, 32 th, 36 th and 54 th columns of the codebook F as the optimal modes, and the user 3 and the user 4 select the same beam mode, so that the user 3 and the user 4 are placed in the same group and served by the same beam mode. The channels of users 3 and 4 are highly correlated and their channel gains are compared and the channel vector of user 3, where the channel gain is higher, is selected as the channel vector for the group. Therefore, in this simulation, the 64 × 5 analog precoding matrix a = [ f ] 7 ，f 18 ，f 32 ，f 36 ，f 54 ]。
S4, digital pre-coding
The digital precoding is performed by a Zero Forcing (ZF) precoding method. With analog precoding, the equivalent channel of 6 users can be represented as
Figure BDA0003248982940000101
Wherein k =1,2. Assuming that the 3 rd user is the user with the highest channel gain in the 3 rd beam, there are:
Figure BDA0003248982940000102
N RF ×N RF the digital precoding matrix of (a) is:
Figure BDA0003248982940000103
after normalization, the digital precoding vector of the nth beam is:
Figure BDA0003248982940000104
s5, power distribution
And obtaining the optimal power distribution by adopting a dynamic power distribution algorithm.
S6, calculating and rate
In the n-th group
Figure BDA0003248982940000105
The signal received by the mth user of the nth group can be written as: />
Figure BDA0003248982940000106
The SINR of the mth user of the nth beam is:
Figure BDA0003248982940000107
wherein the content of the first and second substances,
Figure BDA0003248982940000108
the velocity of the mth user of the nth beam is:
R m,n ＝log 2 (1+γ m,n ) (21)
and rate:
Figure BDA0003248982940000111
by traversing 49 codewords, repeating the above steps, an optimal pattern is found that maximizes the system and rate.
Fig. 5 shows a simulation result of the present embodiment, wherein the lines of IRS-NOMA, IRS-all digital MIMO, all-digital MIMO, IRS-OMA, and OMA shown in the figure respectively represent the spectral efficiency-transmit power curves of the IRS-assisted NOMA system, the IRS-assisted all-digital MIMO system, the IRS-assisted OMA system, and the OMA system. It can be seen from fig. 5 that NOMA can achieve higher spectral efficiency than OMA. The scheme provided by the embodiment of the invention obviously improves the spectrum efficiency of the NOMA system. With the help of IRS, the performance improvement of NOMA system is higher than that of all-digital MIMO system and OMA system.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
What has been described above are merely some of the embodiments of the present invention. It will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention.

Claims (3)

1. An IRS-assisted NOMA-MIMO high-capacity access method is characterized by comprising the following steps:
step S1: quantizing IRS reflection phase shift by a codebook;
reflecting surface IRS-based reflecting element number M R Configuring a 2D-DFT codebook:
Figure FDA0003248982930000011
wherein the codebook
Figure FDA0003248982930000012
Any column v of s Referred to as a codeword;
codebook
Figure FDA0003248982930000013
Is the s-th column v s The tth element of (2):
Figure FDA0003248982930000014
wherein j represents an imaginary unit, the function floor (x) represents a maximum integer less than or equal to x, W 2 ＝M R ；
Slave codebook
Figure FDA0003248982930000015
Selecting the code word that maximizes the spectral efficiency of the system as the reflection phase shift of the IRS, based on the selected code word v s Resulting in a phase shift matrix Φ = diag (v) s )；
The channel vector for user k is defined as: h is a total of k ＝h RU,k ΦH AR +h AU,k ；
Wherein h is RU,k Representing the channel vector between IRS and user k, H AR Representing the channel matrix between the base station and the IRS, h AU,k Representing a channel vector between a base station and a user K, wherein the user number K =1,2, and K represents the number of users;
step S2: codebook-based analog precoding;
the codebook for the analog precoding is as follows:
Figure FDA0003248982930000016
wherein, N T Denotes the number of base station antennas, M denotes the number of beam patterns that can be supported, w m′ Representing the M 'th codeword, and M' =1, \ 8230, M, one for each codewordBeam pointing;
finding out matched beam mode for each user to obtain estimated analog precoding matrix
Figure FDA0003248982930000017
And step S3: grouping users;
dividing users with the same optimal beam pattern into the same group and serving by one beam pattern;
defining the user with highest channel gain in the nth wave beam as the mth wave beam n A user with dimension N T ×N RF Is represented as:
Figure FDA0003248982930000018
wherein, N RF Represents the number of RF links;
and step S4: digital pre-coding;
obtaining the equivalent channel of each user through analog precoding:
Figure FDA0003248982930000021
defining the user with highest channel gain in the nth beam as the mth beam n For each user, the equivalent channel matrix is:
Figure FDA0003248982930000022
and N is RF ×N RF The digital precoding matrix of (c) is:
Figure FDA0003248982930000023
obtaining the digital pre-coding vector of the nth wave beam through normalization processing
Figure FDA0003248982930000024
Wherein N =1, \8230, N RF ；/>
Step S5: configuring the optimal power distribution of each user based on a pre-configured power distribution mode to obtain the transmitting power of each user of each wave beam;
step S6: ergodic codebook
Figure FDA0003248982930000025
Finding an optimal mode;
traverse M R Each code word respectively calculates the frequency spectrum efficiency R of the beam direction corresponding to each code word sum Based on spectral efficiency R sum Obtaining a phase shift matrix phi from the highest code word;
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003248982930000026
|S n i represents the number of users of the nth beam, R m,n Representing the speed, R, of the mth user of the nth beam m,n ＝log 2 (1+γ m,n ) Wherein gamma is m,n The SINR of the mth user representing the nth beam,
Figure FDA0003248982930000027
h m,n channel, p, representing mth user of nth beam m,n Representing the transmit power of different users of different beams;
intermediate volume
Figure FDA0003248982930000028
Wherein, d j A digital precoding vector, S, representing the jth beam j I denotes the number of users of the jth beam, σ 2 Representing the noise variance.
2. The method of claim 1, wherein in step S2, a final orthogonal matching manner is used to find a matching beam pattern for each user.
3. The method according to claim 1 or 2, wherein in step S5, the power allocation scheme is a dynamic power allocation scheme.
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