Hybrid multiple access system transmission and optimization method for hybrid beam forming

Abstract

The invention provides a hybrid multiple access system transmission and optimization method for hybrid beam forming, which comprises the following steps: a base station is provided with an antenna and an RF (Radio Frequency) link, the base station acquires channel gains of users in a coverage area, the users are ranked according to the channel gains, the users with close channel gains are divided into the same group, and the users with close channel gains are distributed into the same group; the number of users contained in each group is not greater than the number of RF links; each user in each group sends a signal to the base station, the base station firstly demodulates a first group of signals with the strongest channel gain for the obtained superposed signals, the demodulation process is realized by adopting a hybrid beam forming method, and then the group of signals are subtracted from the received superposed signals to obtain new signals to be demodulated; and repeating the process, and demodulating each group of signals in sequence according to the channel gain until all groups of signals are demodulated. Through reasonable grouping of the users, the interference between the user groups is eliminated in the demodulation stage, and the target of reducing the total power consumption of the communication system is achieved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a hybrid beamforming hybrid multiple access system transmission and optimization method. Background Art

[0002] As the fifth generation of mobile communications evolves to the sixth generation, the integration of technologies such as space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) has become a key path to improve the spectrum efficiency and number of connections of wireless communication systems. NOMA is a promising technology in B5G / 6G networks. Compared with orthogonal multiple access (OMA), NOMA has higher spectrum efficiency and supports more users to communicate simultaneously. In NOMA mode, multiple users occupy the same time-frequency resource block and can transmit signals simultaneously, greatly improving resource utilization. Traditional power domain NOMA uses serial interference cancellation (SIC) during demodulation. Specifically, the weaker user signal is regarded as interference, and the signal of the strong user is demodulated first and deleted from the received signal. This process continues until all users are demodulated in turn. In the traditional NOMA scheme, NOMA is used for superposition transmission between single users and distinguished in the demodulation stage. When using the traditional hybrid beamforming SDMA / NOMA hybrid multiple access system design, the number of RF links is generally less than the number of users. There are multiple users in the same cluster sharing a beam. If the user channel correlation in the same cluster is small, it will inevitably lead to poor matching of the designed beam for some user channels.

[0003] Traditional SDMA systems use all-digital beamforming technology to configure an independent RF chain for each antenna. However, as the number of transmitting and receiving antennas in communication systems continues to increase, the demand for the number of RF chains is also increasing, which will result in high hardware costs and a lot of energy loss. Summary of the invention

[0004] In view of the signal interference and high power consumption problems of the above-mentioned SDMA / NOMA hybrid multiple access system, the present invention proposes a hybrid multiple access system transmission and optimization method with hybrid beamforming, which eliminates interference between user groups in the demodulation stage by reasonably grouping users, thereby achieving the goal of reducing the total power consumption of the communication system, so as to solve the problems raised in the above-mentioned background technology. The present invention provides the following technical solutions:

[0005] A hybrid multiple access system transmission method with hybrid beamforming, the method comprising the following steps:

[0006] Step 1: Base station is equipped with N R antennas and have N RF RF links, the base station obtains the channel gains of N users in the coverage area and sorts the users according to the channel gains;

[0007] Step 2: sort the users with similar channel gains into the same group according to the order, and divide them into G groups in total. Each group contains U users, and the number of users in the group is not greater than the number of RF links. The channel gain of group 1 is the strongest, and the channel gain of group G is the weakest.

[0008] Step 3, each user in each group sends a signal to the base station, and the base station receives the corresponding superimposed signal;

[0009] Step 4: For the received superimposed signals, the base station first demodulates the first group of signals with the strongest channel gain, and the demodulation process adopts a hybrid beamforming method, and then subtracts the signals of this group from the received superimposed signals to obtain a new signal to be demodulated;

[0010] Step 5: Repeat the process of step 4 to demodulate each group of signals in turn according to the channel gain until all groups of signals are demodulated.

[0011] Preferably, a reconfigurable intelligent surface RIS is deployed within the coverage area of ​​the base station to adjust the direction and phase of signal propagation.

[0012] Preferably, the channel gain between the ith user and the base station is: i =H R,B Φ R H i,R , where H R,B is the channel matrix from RIS to the base station, H i,R is the channel vector from the ith user to the RIS, Φ R is the RIS reflection phase shift matrix, θ n ∈S,S={0,2π / 2 B ,(2 B -1)2π / 2 B},1≤n≤N R ,θ n is the phase shift of the nth RIS reflector unit, B represents the accuracy of the phase shift, N R is the number of RIS reflection units. The channels from RIS to base station and from user to RIS adopt the Rice fading model.

[0013] Preferably, the base station demodulates each group of signals using a hybrid beamforming method, and the signal obtained by hybrid beamforming is:

[0014]

[0015] Among them, H g is the equivalent channel matrix of the g-th group of signals, H g =[h g,1 ,...,h g,u ], P g is the transmission power of the g-th group of signals, P g=diag{p g,1 ,···,p g,u},s g is the transmission signal of the g-th group of users, s g =[s g,1 ,...,s g,u ], is the digital beamforming matrix of the g-th group of signals, is the analog beamforming matrix of the g-th group of signals, n is the noise power spectral density σ with a mean of 0 and a variance of 2 The N×1 additive complex Gaussian noise signal, i g is the interference between user groups,

[0016] Preferably, the analog beamforming matrix uses a fully connected structure, where each RF link is connected to all antennas, and each antenna independently adjusts phase and amplitude: where the column vector

[0017] Preferably, the analog beamforming matrix adopts a partially connected structure, where each RF link connects M antennas, where M = N r / N RF is an integer:

[0018] where the column vector

[0019] A hybrid beamforming hybrid multiple access system optimization method minimizes the total power through the joint design of the following three aspects: transmit power optimization to reduce the total power consumption, digital beamforming matrix design to distinguish user signals in the same group, and RIS reflector unit phase shift design to enhance user signals.

[0020] Preferably, the best linear receiver is used to design the digital beamforming matrix. For the g-th group of digital beamforming matrices for:

[0021]

[0022] in Represents the equivalent channel of the gth group of users after simulating the beamforming matrix and user grouping.

[0023] Preferably, a parallel iterative algorithm is used to optimize the transmit power of each user group. First, the transmit power within the user group is iteratively optimized, and then the next user group is iteratively optimized between user groups. This step is repeated until convergence to obtain the optimal transmit power. When the transmit power within the user group is optimized, as the number of iterations increases, the transmit power of each user is monotonically non-increasing, and finally converges to a stable point:

[0024]

[0025] in, represents the transmission power of the u-th user in the g-th group for the t-th iteration, Represents the inter-group interference covariance matrix of the g-th group.

[0026] Preferably, after determining the transmit power, the system signal-to-interference-to-noise ratio ρ is improved by optimizing the RIS reflector unit phase shift g,u , using the sequential phase shift cycle method, the phase shift matrix of the RIS reflection unit at the tth iteration is expressed as:

[0027]

[0028] in, Represents the nth cyclic phase shift matrix, which satisfies the user's minimum transmission rate r g,u Under the constraint, the optimal phase shift of the nth RIS reflection unit at the tth iteration is:

[0029]

[0030] Among them, L is the penalty coefficient, which is a sufficiently large positive value. When β=min(ρ g,u ), the objective function obtains the optimal solution.

[0031] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0032] 1. The present invention adopts a NOMA transmission method between groups, namely the IGNOMA method. Based on the channel gain grouping method, the users in the cell are first grouped, and the groups are directly transmitted through NOMA superposition, so that the number of users in the group is not greater than the number of RF links. The interference between user groups can be eliminated in the demodulation stage. At the same time, each user beam is designed separately to further reduce the interference between users, thereby greatly improving the communication quality of users.

[0033] 2. Through the deployment of reconfigurable intelligent surface RIS, the direction and phase of signal propagation can be adjusted, so that there is a line-of-sight path between the user and RIS, and between the base station and RIS, avoiding the blind spot between the user and the base station due to building barriers, expanding the coverage of the base station, and enhancing the signal strength received by the base station terminal. In addition, by optimizing the phase shift of the RIS reflection unit, the total transmission power can be further reduced in power optimization, achieving the goal of reducing the total power consumption of the system.

[0034] 3. Through the design of hybrid beamforming, a small number of RF links are used to connect to the antenna, which can greatly reduce the number of RF links in the system without significantly losing the performance of the communication system, thereby reducing the system complexity, hardware cost and energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0036] Figure 1 is a schematic diagram of a scenario of a hybrid multiple access system of the present invention;

[0037] Figure 2 is a line graph showing the relationship between the total transmission power of the system and the minimum rate of the user in the embodiment;

[0038] Figure 3 It is a line graph showing the relationship between the total transmission power of the system and the number of RIS transmission units in the embodiment. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1-Figure 3 , the present invention provides a technical solution:

[0041] Embodiment 1:

[0042] A hybrid multiple access system transmission method with hybrid beamforming, comprising the following steps:

[0043] Step 1: Base station is equipped with N R antennas and have N RF The base station obtains the channel gains of N users in the coverage area and sorts the users according to the channel gains.

[0044] Step 2: sort the users with similar channel gains into the same group according to the order, which is divided into G groups in total. Each group contains U users. The number of users in the group is not greater than the number of RF links. The channel gain of group 1 is the strongest, and the channel gain of group G is the weakest.

[0045] Specifically, assuming that there are buildings blocking the user from the base station, by deploying a reconfigurable intelligent surface RIS within the coverage of the base station, there is a line-of-sight path between the user and RIS, and between the base station and RIS, and the channel is composed of small-scale fading and path loss. The channels between the user and RIS, and between the base station and RIS all use the Rice fading model:

[0046]

[0047] Where d is the propagation distance of the signal, α represents the path loss factor, and K is the Rice fading factor. It is the channel LoS path component composed of the arrival angle and departure angle. is the NLoS path component of the channel, which obeys a complex Gaussian distribution with a mean of 0 and a variance of 1.

[0048] The channel gain between the i-th user and the base station is:

[0049] h i =H R,B Φ R H i,R

[0050] Among them, H R,B is the channel matrix from RIS to the base station, H i,R is the channel vector from the ith user to the RIS, Φ R is the RIS reflection phase shift matrix, θ n is the phase shift of the nth RIS reflection unit. Due to hardware limitations, the RIS reflection unit uses discrete phase shift values ​​θ n ∈S,S={0,2π / 2 B ,(2 B -1)2π / 2 B},1≤n≤N R , B represents the accuracy of phase shift, N R is the number of RIS reflection units.

[0051] According to the IGNOMA method proposed in this embodiment, it is assumed that the base station has obtained the channel gain of each user in the cell || h i ||, sort users according to the channel gain||h 1 ||>…>||h N ||. According to the sorting results, the U users with the strongest channel gain are divided into group 1, the U users with the second strongest channel gain are divided into group 2, and so on, until each user is divided into the corresponding group, and finally a total of G groups are obtained, each of which contains U users.

[0052] Step 3: Each user in each group sends a signal to the base station, and the base station receives the corresponding superimposed signal. The superimposed signal can be expressed as:

[0053]

[0054] Among them, s g,u is the signal sent by the u-th user in the g-th group, satisfying E{|s g,u | 2}=1,p g,u is the corresponding user's transmission power, hg,u ∈C N×1 Represents the signal vector of the corresponding grouped user, n is subject to the mean of 0, and the variance is the noise power spectrum density σ 2 N×1 additive complex Gaussian noise signal.

[0055] Step 4: For the received superimposed signals, the base station first demodulates the first group of signals with the strongest channel gain, and the demodulation process adopts a hybrid beamforming method, and then subtracts the signals of this group from the received superimposed signals to obtain a new signal to be demodulated;

[0056] Step 5: Repeat the process of step 4 to demodulate each group of signals in turn according to the channel gain until all groups of signals are demodulated.

[0057] Specifically, the base station uses a hybrid beamforming method to demodulate each group of signals. The signal obtained by hybrid beamforming is:

[0058]

[0059] Among them, H g is the equivalent channel matrix of the g-th group of signals, H g =[h g,1 ,...,h g,u ], P g is the transmission power of the g-th group of signals, P g =diag{p g,1 ,···,p g,u},s g is the transmission signal of the g-th group of users, s g =[s g,1 ,...,s g,u ], is the digital beamforming matrix of the g-th group of signals, is the analog beamforming matrix of the g-th group of signals, i g is the interference between user groups,

[0060] In this embodiment, the analog beamforming matrix adopts a fully connected structure, each RF link is connected to all antennas, and each antenna independently adjusts the phase and amplitude, so that more precise control can be achieved during beamforming: where the column vector

[0061] Embodiment 2:

[0062] Different from the first embodiment, the analog beamforming matrix can also adopt a partial connection structure, where each RF link is connected to M antennas, where M = N r / N RF Must be an integer:

[0063] where the column vector

[0064] Compared with the fully connected structure of Example 1, this structure reduces the number of required phase shifters and connection lines, thereby reducing hardware complexity and cost.

[0065] Compared with Example 1 and Example 2, when using the traditional hybrid beamforming SDMA / NOMA hybrid multiple access system, the number of RF links is generally less than the number of users, and multiple users in the same cluster share one beam. If the correlation between user channels in the same cluster is small, it will inevitably lead to poor matching of the designed beam for some user channels. According to the IGNOMA structure designed in Examples 1 and 2, the users in the cell are first grouped, and the groups are directly transmitted through NOMA superposition, so that the number of users in the group is not greater than the number of RF links. Therefore, a beam can be designed separately for each user in the group, which is energy efficient.

[0066] Embodiment 3:

[0067] A hybrid beamforming hybrid multiple access system optimization method minimizes the total power through the joint design of three aspects: transmit power optimization to reduce total power consumption, digital beamforming matrix design to distinguish user signals in the same group, and RIS reflector unit phase shift design to enhance user signals. The specific optimization process is as follows:

[0068] Perform singular value decomposition of the user channel matrix H = U ∧ V and let the simulated beamforming matrix W A The phase of each element in is equal to the phase of the element at the corresponding position in the left singular matrix U. After simulated beamforming and user grouping, the equivalent channel of the g-th group of users can be further expressed as

[0069] According to the decoded signal y g , the signal-to-interference-noise ratio of a single user ρ g,u The expression is:

[0070]

[0071] in, is the inter-group interference covariance matrix of the gth group. The first term of the denominator represents the interference of other users in the current group to the current user, the second term represents the interference term of the demodulated user group signal to the current group user, and the third term is the noise interference. The optimization problem is as follows:

[0072]

[0073] stlog 2 (1+ρ g,u )≥r g,u(3)

[0074] θ n ∈S,1≤n≤N R (4)

[0075] Among them, r g,u is the minimum transmission rate of the user, and equation (2) reflects the service quality constraints of each user. Obviously, this optimization problem is non-convex and it is quite difficult to solve it directly. Therefore, we first need to transform problem (P1) into a form that is easy to solve.

[0076] For the design of the digital beamforming matrix, this embodiment adopts the best linear receiver, that is, the minimum mean square error receiver, and the digital beamforming matrix for the g-th group can be obtained: for:

[0077]

[0078] After substituting formula (5) into formula (1), the new expression of signal-to-interference-noise ratio is obtained as follows:

[0079]

[0080] Thus, problem (P1) is transformed into (P2):

[0081]

[0082] stlog 2 (1+ρ g,u )≥r g,u (8)

[0083] θ n ∈S,1≤n≤N R (9)

[0084] In order to solve this non-convex problem, the idea of ​​alternating optimization is adopted. Specifically, for the three variables involved, one variable is optimized each time while the other variables are fixed.

[0085] After fixing the phase shift of the RIS unit, the optimization problem (P2) can be transformed into (P3):

[0086]

[0087] stlog 2 (1+ρ g,u )≥r g,u (11)

[0088] The optimization problem (P3) is a power control problem, but (P3) is still non-convex. Therefore, when designing the transmit power, a parallel iterative algorithm is used to optimize the transmit power of each user group. Specifically, according to the decoding order of the uplink NOMA system, when iteratively optimizing the transmit power of the gth group, the transmit power of other groups remains fixed.

[0089] By contradiction, it can be proved that the optimal value can be obtained when the constraint condition of user service quality is equal. Proof process: Assumption is the optimal solution to problem (P3) and satisfies constraint (11). For any user in group g, substituting equation (6) into equation (11) yields:

[0090]

[0091] The new transmit power of user n is:

[0092]

[0093] So there is a new set of power allocations that is better than This contradicts the assumption, so when the equality of equation (11) holds, the optimization problem (P3) obtains the optimal solution. Therefore, the user transmission power can be expressed as:

[0094]

[0095] It can be seen from the denominator of formula (14) that the transmission power of different user groups and different users in the same user group affects each other, so iterative optimization within and between groups is required to obtain the optimal transmission power. First, perform iterative optimization of the transmission power within the user group, then use iterative optimization between user groups to optimize the next user group, and repeat this step until convergence to obtain the optimal transmission power. When optimizing the transmission power within the user group, as the number of iterations increases, the transmission power of each user is monotonically non-increasing, and finally converges to a stable point:

[0096]

[0097] in, represents the transmission power of the t-th iteration of the u-th user in the g-th group. It can be seen that

[0098] After determining the user transmit power, the system signal-to-interference-to-noise ratio is improved by optimizing the RIS reflector phase shift, which will further reduce the total transmit power in power optimization. The optimization problem is as follows:

[0099] (P4) Find:{Φ R}(15)

[0100] stlog 2(1+ρ g,u )≥r g,u (16)

[0101] θ n ∈S,1≤n≤N R (17)

[0102] Using the sequential phase shift cycle method, the phase shift matrix of the RIS reflection unit at the tth iteration is expressed as:

[0103]

[0104] in, represents the nth cyclic phase shift matrix. When β=min(ρ g,u ), the objective function can obtain the optimal solution. For constraint (16), the penalty function is introduced, and the optimal phase shift of the nth RIS reflection unit in the tth iteration is:

[0105]

[0106] Among them, L is the penalty coefficient, which is a sufficiently large positive value.

[0107] The following simulation experiments verify that the methods proposed in Examples 1-3 can achieve low-power transmission in a hybrid beamforming SDMA / NOMA hybrid multiple access system. The system parameters are as follows:

[0108]

[0109]

[0110] The relationship between the total system transmission power and the user's minimum rate requirement is as follows: Figure 2 As shown, the number of RIS transmitting units is 100 at this time. It can be found that with the increase of the minimum rate requirement of the user, the total system transmission power of each scheme has increased. For the scheme using the user grouping IGNOMA method proposed by the present invention, the total system power is always lower than that of the scheme using the traditional NOMA method. This is because IGNOMA uses group-level superposition transmission and interference elimination, which will cause less interference to users in the group, thereby achieving the purpose of low-power transmission.

[0111] At the same time, compared with the fully connected structure, each RF chain in the partially connected structure only connects to some antennas and cannot obtain higher gain. Therefore, the transmission power of the partially connected solution is higher than that of the fully connected structure. In addition, in the solution of deploying RIS, the system can also achieve lower power consumption.

[0112] Figure 3The relationship between the total system transmission power and the number of RIS transmission units is shown. At this time, the minimum user rate requirement is 2b / s / Hz. It can be found that the total system transmission power of the solution using the IGNOMA method is lower than that of the solution using the traditional NOMA method. Similarly, the fully connected solution also achieves lower transmission power.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A hybrid multiple access system transmission method with hybrid beamforming, characterized in that: The method comprises the following steps: Step 1: Base station is equipped with N R antennas and have N RF RF links, the base station obtains the channel gains of N users in the coverage area and sorts the users according to the channel gains; Step 2: sort the users with similar channel gains into the same group according to the order, and divide them into G groups in total. Each group contains U users, and the number of users in the group is not greater than the number of RF links. The channel gain of group 1 is the strongest, and the channel gain of group G is the weakest. Step 3, each user in each group sends a signal to the base station, and the base station receives the corresponding superimposed signal; Step 4: For the received superimposed signals, the base station first demodulates the first group of signals with the strongest channel gain, and the demodulation process adopts a hybrid beamforming method, and then subtracts the signals of this group from the received superimposed signals to obtain a new signal to be demodulated; Step 5: Repeat the process of step 4 to demodulate each group of signals in turn according to the channel gain until all groups of signals are demodulated.

2. The hybrid beamforming hybrid multiple access system transmission method according to claim 1, characterized in that: Reconfigurable smart surface RIS is deployed within the coverage area of ​​the base station to adjust the direction and phase of signal propagation.

3. The hybrid beamforming hybrid multiple access system transmission method according to claim 2, characterized in that: The channel gain between the i-th user and the base station is: h i =H R,B Φ R H i,R , where H R,B is the channel matrix from RIS to the base station, H i,R is the channel vector from the ith user to the RIS, Φ R is the RIS reflection phase shift matrix, θ n ∈S,S={0,2π / 2 B ,(2 B -1)2π / 2 B },1≤n≤N R ,θ n is the phase shift of the nth RIS reflector unit, B represents the accuracy of the phase shift, N R is the number of RIS reflection units. The channels from RIS to base station and from user to RIS adopt the Rice fading model.

4. The hybrid beamforming hybrid multiple access system transmission method according to claim 3, characterized in that: The base station uses a hybrid beamforming method to demodulate each group of signals. The signal obtained by hybrid beamforming is: Among them, H g is the equivalent channel matrix of the g-th group of signals, H g =[h g,1 ,...,h g,u ], P g is the transmission power of the g-th group of signals, P g =diag{p g,1 ,···,p g,u },s g is the transmission signal of the g-th group of users, s g =[s g,1 ,...,s g,u ], is the digital beamforming matrix of the g-th group of signals, is the analog beamforming matrix of the g-th group of signals, n is the noise power spectral density σ with a mean of 0 and a variance of 2 The N×1 additive complex Gaussian noise signal, i g is the interference between user groups, 5. The hybrid beamforming hybrid multiple access system transmission method according to claim 4, characterized in that: The analog beamforming matrix uses a fully connected structure, where each RF chain is connected to all antennas, and each antenna adjusts phase and amplitude independently: where the column vector 6. The hybrid beamforming hybrid multiple access system transmission method according to claim 4, characterized in that: The analog beamforming matrix uses a partially connected structure, where each RF link connects M antennas, where M = N r / N RF is an integer: where the column vector 7. A hybrid multiple access system optimization method for hybrid beamforming, characterized in that: Based on the transmission method described in any one of claims 1-6, the total power is minimized through the joint design of the following three aspects: transmission power optimization to reduce total power consumption, digital beamforming matrix design to distinguish user signals in the same group, and RIS reflection unit phase shift design to enhance user signals.

8. The method for optimizing a hybrid multiple access system with hybrid beamforming according to claim 7, characterized in that: The optimal linear receiver is used to design the digital beamforming matrix. For the g-th group of digital beamforming matrices for: in Represents the equivalent channel of the gth group of users after simulating the beamforming matrix and user grouping.

9. The method for optimizing a hybrid multiple access system with hybrid beamforming according to claim 8, characterized in that: A parallel iterative algorithm is used to optimize the transmit power of each user group. First, the transmit power within the user group is iteratively optimized, and then the next user group is iteratively optimized between user groups. This step is repeated until convergence and the optimal transmit power is obtained. When optimizing the transmit power within the user group, as the number of iterations increases, the transmit power of each user is monotonically non-increasing and eventually converges to a stable point: in, represents the transmission power of the u-th user in the g-th group for the t-th iteration, Represents the inter-group interference covariance matrix of the g-th group.

10. The method for optimizing a hybrid multiple access system with hybrid beamforming according to claim 9, characterized in that: After determining the transmit power, the system signal-to-interference-to-noise ratio ρ is improved by optimizing the phase shift of the RIS reflector unit g,u , using the sequential phase shift cycle method, the phase shift matrix of the RIS reflection unit at the tth iteration is expressed as: in, Represents the nth cyclic phase shift matrix, which satisfies the user's minimum transmission rate r g,u Under the constraint, the optimal phase shift of the nth RIS reflection unit at the tth iteration is: Among them, L is the penalty coefficient, which is a sufficiently large positive value. When β=min(ρ g,u ), the objective function obtains the optimal solution.

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