CN113852402A - 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 PDFInfo
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Abstract
The invention discloses an IRS (intelligent resilient multimedia system) -assisted NOMA-MIMO (multiple input multiple output) high-capacity access method, belonging to the technical field of wireless communication. The invention transforms the joint optimization problem of active and passive precoding in an IRS-assisted MIMO system into an optimal codeword optimization problem by quantizing IRS reflection phase shift by using a 2D-DFT codebook. 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 the 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
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 significant 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 the base station and the user, a reflection channel is added, an equivalent channel vector is adjusted, the potential of artificially changing the equivalent channel vector is achieved, and the characteristics bring more advantages to the IRS-assisted NOMA communication system. In the research of the existing IRS-assisted communication system, 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 high-capacity access method comprises the following steps:
step S1: quantizing IRS reflection phase shift by a codebook;
number of reflection elements M based on reflection surface IRSRConfiguring a two-dimensional discrete Fourier (2D-DFT) codebook:wherein the codebookAny column v ofsCalled a codeword, and a codebookIs the s-th column vsThe tth element of (2):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 W2=MR;
Slave codebookSelects 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 vsObtaining the phase shift matrix phi ═ diag (v)s);
The channel vector for user k is defined as: h isk=hRU,kΦHAR+hAU,k;
Wherein h isRU,kRepresenting the channel vector between IRS and user k, HARRepresenting the channel matrix between the base station and the IRS, hAU,kRepresenting a channel vector between a base station and a user K, wherein the user number K is 1,2, and K represents the number of users;
step S2: codebook-based analog precoding;
the codebook for simulating precoding is as follows:
wherein N isTRepresenting the number of base station antennas, M representing the number of beam patterns that can be supported, wm′Represents the mth code word, and M' is 1, …, M, each code word corresponds to a beam direction;
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 beamnA user, with dimension NT×NRFThe analog precoding matrix of (a) is represented as:wherein N isRFRepresents the number of RF (radio frequency) links;
step S4: digital pre-coding;
defining the user with highest channel gain in the nth wave beam as the mth wave beamnFor each user, the equivalent channel matrix is:
and N isRF×NRFThe digital precoding matrix of (a) is:
obtaining the digital pre-coding vector of the nth wave beam through normalization processingWherein N is 1, …, NRF;
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;
traverse MREach code word respectively calculates the frequency spectrum efficiency R of the beam direction corresponding to each code wordsumBased on spectral efficiency RsumObtaining a phase shift matrix phi from the highest code word;
Rm,nrepresenting the speed, R, of the mth user of the nth beamm,n=log2(1+γm,n) Wherein γ ism,nThe SINR of the mth user representing the nth beam,hm,nchannel, p, representing mth user of nth beamm,nRepresenting the transmission power of different users of different beams, i.e. pm,nRepresenting the transmission power, an intermediate quantity, of the ith user of the nth beampi,nRepresenting the transmission power, p, of the ith user of the nth beamj,tRepresenting the transmission power of the t user of the j beam, djA digital precoding vector, S, representing the jth beamjI denotes the number of users of the jth beam, σ2Representing the variance of the noise.
Further, in step S2, a final orthogonal matching manner is used to find a matching beam pattern for each user.
Further, in step S5, the power allocation method is a dynamic power allocation method.
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 shift 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 a suboptimal pattern 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.
Drawings
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 the 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
In order 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 as shown in figure 1, and the system mainly comprises a system which is configured with NTRoot antenna, NRFA base station with RF (radio frequency) chain, K single-antenna users and an IRS. Wherein IRS comprises MRA 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. Hybrid precoding consisting of analog precoding and digital precodingAnd coding is performed, each RF chain is connected with all N antennas through phase shifters, and 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 to 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 SnSet of users, | S, serving the nth beamnI is the number of users of the nth beam, where g is 1,2 … NRFIn the nth beamThe signal received by the mth user of the n groups is:
wherein h ism,nDenotes the channel of the mth user of the nth beam, the superscript "H" denotes the conjugate, wnA codeword representing the nth beam, A is an analog precoding matrix, d is a digital precoding vector, indexed by a specifier, diA digital precoding vector representing the ith beam, dmA digital precoding vector, | S, representing the mth userjI represents the number of users of the jth beam, si,jRepresenting the transmitted signal, s, of the jth user of the ith beamm,nIs the transmitted signal of the mth user of the nth beam, E { | sm,n|21, E { } denotes mathematical expectation, pm,nIs the power of the mth user of the nth beam, nm,n~Obeying a mean value of 0 and a variance of σ2Additive White Gaussian Noise (AWGN). SINR (Signal to Interference plus Noise Rate) of mth user of nth beamio) is expressed as:
the velocity of the mth user of the nth beam is:
Rm,n=log2(1+γm,n) (3)
the spectral efficiency is:
the goal is to optimize active beamforming, passive beamforming, and power allocation to maximize the spectral efficiency of the system. The optimization problem can be expressed as:
wherein P represents the base station transmitting power, phi represents the reflection phase shift matrix of IRS, the constraint condition C1 represents that the sum of the transmitting power does not exceed the base station transmitting power, and the constraint condition C2 represents that the reflection phase shift of IRS is from the codebookConstraint C3 indicates that the transmit power is positive, 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 composed of MRA reflection element, wherein MR=W2The 2D-DFT codebook can be expressed as:
wherein the content of the first and second substances,is called a code word, vsTo representAnd v is the element of the s-th columnsThe tth element of (2):
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 setThe 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:
hk=hRU,kΦHAR+hAU,k (8)
wherein h isRU,kIs the channel vector between IRS and user k, HARIs the channel matrix between the base station and the IRS, hAU,kIs the channel vector between the base station and user k, and the channel matrix H ═ H1,h2,...hK]。
2. Codebook-based analog precoding
Performing hybrid beamforming based on channel vectors of the synthesized channel, wherein a codebook implementing analog precoding may be represented as:
wherein j2M is the number of beam patterns that can be supported to cover all directions-1. One beam pattern is defined as one codeword, w, in deployed hybrid beamformingmDenotes an M (M ═ 1, …, M) th codeword. Each codeword corresponds to a beam pointing direction. In this embodiment, based on the hybrid precoding algorithm, Orthogonal Matching Pursuit (OMP), which is widely applied to the millimeter wave channel at present, an optimal beam pattern is found for each user, and the process is summarized as algorithm 1. In Algorithm 1, the optimal precoding F for each useropt(k) The codebook corresponding to the optimal beam mode selected each time is formed into N through singular value decompositionTxK matrix
The algorithm 1 is specifically as follows:
inputting: a channel matrix H, a codebook F and a user number K;
step (2): traverse the channel vector h for each userkThe following calculation processing is performed:
calculating based on the decomposition result:
where the user number K is 1, …, K, where K represents the number of users, Vk(: 1) represents a specific column of the matrix, i.e., matrix VkThe first column of (A), F (: u) represents the u-th column of F.
3. User grouping
In the conventional OMA scheme, one beam can only serve one user, and the number of users capable of serving can not exceed the number of RF chains, i.e. K is less than or equal to NRFIf multiple users select the same optimal beam pattern, it is inevitable that users will adopt a suboptimal 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, and the limitation of the number of RF chains to large-scale access is broken, namely K is more than or equal to NRF。
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 beamnIndividual user (1 ≦ mn≤K),NT×NRFAnalog precoding matrix
4. Digital pre-coding.
In order to reduce the interference between users, a Zero Forcing (ZF) precoding method is adopted for digital precoding. Through analog precoding, the equivalent channel of K users can be expressed asWherein K is 1,2. Suppose that the user with the highest channel gain in the nth beam is the mth beamnThe users are as follows:
NRF×NRFthe digital precoding matrix of (a) is:
normalized, the digital precoding vector for the nth beam can be written as:
5. power distribution
In the embodiment of the present invention, the optimal power allocation is obtained by using a dynamic power allocation algorithm proposed in the literature (b.wang, l.dai, z.wang, n.ge, and s.zhou, "Spectrum and energy-efficiency beam analysis MIMO-NOMA for millimeter-wave communication 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, a higher signal-to-noise ratio can be achieved, and fairness among users is guaranteed.
6. The 2D-DFT codebook is traversed to find the optimal mode.
Traverse MRAnd (4) respectively calculating the system spectral efficiency in each mode according to the formulas (2), (3) and (4), and selecting the 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 NT64, IRS number of reflection elements MRWhen the number K of users is 49, the number σ is 62-110 dBm. As shown in fig. 3, 6 single-antenna users are uniformIs distributed in a semi-ring area with IRS as the center of a circle, and the inner radius r of the semi-ring15m, outer radius r210 m. The base station is located at (0,0,0), and the intelligent reflecting surface is located at (0,0, 50).
In this embodiment, an IRS-assisted NOMA-MIMO large capacity access method of the present invention includes the following steps:
s1, IRS is composed of 49 reflectors, so the 49 × 49 2D-DFT codebook can be expressed as:
wherein the content of the first and second substances,the columns of (a) are called code words,the tth element of the tth column of (1) is:
using the 2D-DFT codebook described aboveQuantization fromAnd selecting a code word as the reflection phase shift of the IRS to obtain a phase shift matrix phi.
S2 codebook-based analog precoding
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-IRSAR,hAU,k,hRU,k. According to the phase shift matrix Φ selected at S1, the user k composite channel vector can be represented as:
hk=hRU,kΦHAR+hAU,k
performing hybrid beamforming based on a channel vector of a synthesized channel, wherein a codebook for realizing analog precoding is as follows:
f can support 64 beam patterns,by algorithm 1, the optimal beam pattern is found for each user. The selected code words form an analog precoding matrix 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 the 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 RF5. To better describe the embodiment of the present invention, the following steps adopt a simulation process as shown in fig. 4. Wherein, users 1 to 6 select the 7 th, 18 th, 32 th, 36 th, 54 th columns of the codebook F as the optimal modes, and user 3 and user 4 select the same beam mode, so that user 3 and 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 ═ f7,f18,f32,f36,f54]。
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 asWherein k is 1,2, 6. Assuming that the 3 rd user is the user with the highest channel gain in the 3 rd beam, there are:
NRF×NRFthe digital precoding matrix of (a) is:
through normalization, the digital precoding vector of the nth beam is:
s5, power distribution
And obtaining the optimal power distribution by adopting a dynamic power distribution algorithm.
S6, calculating and rate
the SINR of the mth user of the nth beam is:
the velocity of the mth user of the nth beam is:
Rm,n=log2(1+γm,n) (21)
and rate:
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 this embodiment, in which the lines of IRS-NOMA, IRS-all-digital MIMO, IRS-OMA, and OMA respectively represent the spectral efficiency-transmit power curves of the IRS-assisted NOMA system, IRS-assisted all-digital MIMO system, IRS-assisted OMA system, and 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 frequency 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, but 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 embodiments of the present invention. It will be apparent to those skilled in the art that various changes and modifications can be made without departing from the inventive concept thereof, and these changes and modifications can be made 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;
number of reflection elements M based on reflection surface IRSRConfiguring a 2D-DFT codebook:wherein the codebookAny column v ofsReferred to as a codeword;
wherein j represents an imaginary unit, the function floor (x) represents a maximum integer less than or equal to x, W2=MR;
Slave codebookSelects 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 vsObtaining the phase shift matrix phi ═ diag (v)s);
The channel vector for user k is defined as: h isk=hRU,kΦHAR+hAU,k;
Wherein h isRU,kRepresenting the channel vector between IRS and user k, HARRepresenting the channel matrix between the base station and the IRS, hAU,kRepresenting a channel vector between a base station and a user K, wherein the user number K is 1,2, and K represents the number of users;
step S2: codebook-based analog precoding;
the codebook for simulating precoding is as follows:
wherein N isTRepresenting the number of base station antennas, M representing the number of beam patterns that can be supported, wm′Represents the mth code word, and M' is 1, …, M, each code word corresponds to a beam direction;
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 beamnA user, with dimension NT×NRFThe analog precoding matrix of (a) is represented as:wherein N isRFRepresents the number of RF links;
step S4: digital pre-coding;
defining the user with highest channel gain in the nth wave beam as the mth wave beamnFor each user, the equivalent channel matrix is:
and N isRF×NRFNumber ofThe word precoding matrix is:
obtaining the digital precoding vector of the nth wave beam through normalization processingWherein N is 1, …, NRF;
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;
traverse MREach code word respectively calculates the frequency spectrum efficiency R of the beam direction corresponding to each code wordsumBased on spectral efficiency RsumObtaining a phase shift matrix phi from the highest code word;
|Sni represents the number of users of the nth beam, Rm,nRepresenting the speed, R, of the mth user of the nth beamm,n=log2(1+γm,n) Wherein γ ism,nThe SINR of the mth user representing the nth beam,hm,nchannel, p, representing mth user of nth beamm,nRepresenting the transmit power of different users of different beams;
2. The method of claim 1, wherein in step S2, an orthogonal matching final approach 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 manner is a dynamic power allocation manner.
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