Intelligent reflecting surface assisted dual-mode relay adaptive transmission method

Abstract

The application provides a smart reflecting surface assisted dual-mode relay adaptive transmission method and relates to the technical field of wireless communication.The application comprises the following steps: a DMR is composed of multiple DMRUs, the DMRUs intelligently select an active relay mode or an IRS reflecting mode for signal forwarding or reflecting under the control of a Tx, and all the DMR working modes form a DMR working mode set;one working mode selection matrix is randomly selected from the DMR working mode set, and the working mode of the DMR is set according to the working mode selection matrix; the reflection coefficient matrix of the IRS, the beamforming matrix of the Tx and the DMR and the data rate of the Rx are calculated; the last data rate of the Rx is recorded; the DMR selects the DMR working mode corresponding to the maximum data rate of the Rx, and adjusts the beamforming matrix of the Tx and the DMR and the reflection coefficient matrix of the IRS.The application can improve the data rate without consuming extra power and comprehensively improve the communication performance.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a smart reflector-assisted dual-mode relay based adaptive transmission (DMRAT) method. Background Technology

[0002] In recent years, the rapid development of wireless communication technology has led to a dramatic increase in the number of users and traffic in communication systems. Good network coverage is crucial to ensuring users can access high-quality data anywhere, especially for users at the edge of access point coverage, where the signal-to-noise ratio is low and susceptible to interference from neighboring access points. Relay communication technology can address these issues. Relay technology uses relay nodes to receive and forward signals, extending communication range and improving signal quality; however, relay nodes require additional transmit power overhead. Intelligent Reflecting Surfaces (IRS) are passive devices composed of multiple low-cost passive reflective elements. Each element can dynamically adjust its reflection coefficient under the control of the IRS controller, thereby altering the amplitude and phase shift of the incident signal. IRS offers new design ideas for signal forwarding, but its passive nature limits its ability to enhance and forward incident signals, thus restricting its application. Relays and IRS each have their own advantages and disadvantages in terms of energy efficiency, hardware and computational complexity, and coverage. Therefore, it is of great significance to design a new relay transmission scheme that combines the advantages of both and integrates relay and intelligent reflective surface.

[0003] The first existing technology is cooperative relay technology. Although it can effectively improve communication quality and signal coverage, the hardware and power overhead of traditional relay communication increases communication costs because the relay operation relies on active components such as carrier signal generation, analog-to-digital converters, and power amplifiers. Therefore, how to achieve signal forwarding, increase coverage, and improve received signal quality in a low-cost and low-power manner is an urgent problem to be solved. The second existing technology is backscattering technology, which uses passive backscattering devices to absorb, convert, and store electromagnetic wave energy from the surrounding environment for transmission by backscattering devices. However, backscattering technology is susceptible to interference from noise and other irrelevant signal sources, and its low RF signal energy conversion efficiency limits its application. The third existing technology is IRS-assisted communication. Due to the limited signal processing capabilities and passive characteristics of IRS, it is susceptible to channel fading. In practical applications, IRS has limitations such as limited operating frequency bands and insufficient dynamic adjustment capabilities.

[0004] Based on the above analysis, the problems and shortcomings of the existing technology are as follows:

[0005] (1) Active relay technology has high hardware costs and high power consumption.

[0006] (2) Backscattering technology is susceptible to interference from noise and other irrelevant signal sources in the environment, resulting in low energy conversion efficiency of radio frequency signals.

[0007] (3) Intelligent reflective surfaces are easily affected by the communication environment and have weak dynamic control capabilities.

[0008] The challenge in addressing the above problems and shortcomings lies in considering how to design a new device that combines active repeaters and intelligent reflectors, enabling the device to simultaneously balance communication quality and system power consumption, and to dynamically employ different modes for signal relay to achieve high-quality, low-power adaptive transmission.

[0009] The significance of solving the above problems and defects is that by using a dual-mode repeater that can dynamically select the working mode, active repeater and intelligent reflector are integrated into the above dual-mode repeater. This dual-mode repeater device can select the appropriate working mode according to the communication environment, thereby improving the communication quality without increasing energy consumption. Summary of the Invention

[0010] To address the technical problems of excessive power consumption and high hardware complexity in existing relay transmission methods, this invention proposes a dual-mode relay adaptive transmission method assisted by an intelligent reflector. This method combines the relay transmission method with intelligent reflector technology and uses an alternating optimization algorithm for the combined device to maximize the data rate of the receiver.

[0011] To achieve the above objectives, the technical solution of the present invention is as follows: a smart reflector-assisted dual-mode relay adaptive transmission method, the steps of which are as follows:

[0012] S101: DMR consists of multiple DMRUs. Under the control of Tx, the DMRUs intelligently select the active relay or IRS reflection mode for signal forwarding or reflection. All DMR operating modes form the DMR operating mode set; initialize the operating mode set with the maximum Rx data rate, and set the convergence threshold and the maximum number of iterations.

[0013] S102: Select an arbitrary working mode selection matrix from the DMR working mode set, set the working mode of DMR according to the working mode selection matrix, and delete the working mode selection matrix from the DMR working mode set; initialize the number of iterations and the reflection coefficient matrix of IRS at the 0th iteration, and calculate the beamforming matrix of Tx and DMR and the data rate of Rx at the 0th iteration.

[0014] S103: Increment the iteration count by 1, and calculate the reflection coefficient matrix of IRS, the beamforming matrix of Tx and DMR, and the data rate of Rx during the iteration.

[0015] S104: Calculate the absolute value of the data rate difference of Rx obtained in adjacent iterations. If the absolute value of the data rate difference of Rx is greater than the convergence threshold and the number of iterations has not exceeded the maximum number of iterations, return to step S103. Otherwise, record the final data rate of Rx, the current DMR working mode selection matrix, the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS, and execute step S105.

[0016] S105: Determine if the DMR operating mode set is empty. If the DMR operating mode set is not empty, return to step S102. Otherwise, compare the data rates of all Rx values. DMR selects the DMR operating mode corresponding to the maximum data rate of Rx and adjusts the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS.

[0017] Preferably, the Tx is equipped with N T One transmitting antenna, Rx configured with N R Root receiving antenna, Tx with power P T Transmit signal; DMR is generated by N DM It consists of DMRUs, which can intelligently select active relay or passive reflection mode for signal / data forwarding under the control of the control unit CU under Tx. When the DMRU adopts active relay mode, it operates in full-duplex DF relay mode, and the transmit power of the DMR forwarded signal is P. DM Tx dynamically selects and configures the operating mode and parameters of the DMRU through the control unit CU. Before formal communication, Tx broadcasts pilot signals. All DMRUs of the DMR adopt the passive IRS operating mode. Rx estimates the channel state information between itself, the IRS and Tx and feeds it back to Tx.

[0018] Tx sends data information The superscript T indicates the transpose operation; Tx uses the beamforming matrix. Preprocess the data information x and map the data information x to N. T Transmit using a single transmitting antenna; and H and G represent the channel state information between Tx and DMR, and between DMR and Rx. H and G exhibit quasi-static flat fading characteristics and are independent of each other. Their elements are complex Gaussian random variables with zero mean and unit variance; and N T =N R =N DM =N I =M, where M is a positive integer.

[0019] Preferably, in step S101, the optimal data rate set Ω of Rx obtained in each operating mode of DMR is initialized. R A set of DMR operating modes that enable Rx to achieve the optimal data rate The set of Tx beamforming matrices that enables Rx to achieve the optimal data rate and DMR beamforming matrix set The set of IRS reflection matrices Ω that enables Rx to achieve the optimal data rate Φ ;initialization Represents an empty set;

[0020] Tx with power The power of the transmitted signal and the DMR relay signal is P total This represents the total transmit power of the system.

[0021] The DMR working mode set consists of all DMR working modes S n =diag(s n,1 ,…,s n,M ) represents the selection matrix for the nth DMR operating mode, and Tx is based on the DMR operating mode selection matrix S. n Controlling the DMR operating mode, element s n,m =1 indicates that the m-th DMRU uses DF relay forwarding, s n,m =0 indicates that the m-th DMRU uses IRS reflection, where m∈{1,…,M}, and M represents the number of transmit antennas of Tx, the number of receive antennas of Rx, and the number of DMRUs included in the DMR;

[0022] Initialize DMR operating mode S n Let S1 be the value of n = 1.

[0023] Preferably, the iteration number l = 0 and the reflection coefficient matrix Φ0 = I of IRS at the 0th iteration are initialized, and the beamforming matrix W of Tx at the 0th iteration is calculated using the zero-forcing beamforming algorithm. Tx,0 Beamforming matrix W of DMR DF,0 And the data rate of Rx.

[0024] Preferably, the zero-forcing beamforming algorithm is used to calculate the Tx beamforming matrix W at the 0th iteration. Tx,0 and DMR beamforming matrix W DF,0 The method is as follows:

[0025]

[0026]

[0027] in, This represents the equivalent channel matrix from Tx through all DMRUs using IRS reflection in the DMR to Rx. Φ represents the equivalent channel matrix between all DMRUs and Rx using DF relay forwarding in DMR; H represents the matrix transformation, S1 represents the current DMR operating mode selection matrix, and Φ1 represents the current IRS reflection coefficient matrix.

[0028] The data rate of Rx during the 0th iteration is:

[0029]

[0030] in, It is the equivalent channel matrix The m-th row vector, It is the equivalent channel matrix The m-th row vector, Rx represents the filter vector used to recover the m-th data stream; w DF,0,m and w Tx,0,m Representing the beamforming matrix W respectively DF,0 and W Tx,0 The m-th column vector, The variance of additive Gaussian white noise.

[0031] Preferably, in step S103, the iteration number l is incremented by 1, and the reflection coefficient matrix Φ of the IRS at the l-th iteration is calculated. l The beamforming matrix W of Tx and DMR at the l-th iteration is calculated using the zero-forcing beamforming algorithm. Tx,l and W DF,l Calculate the data rate R of Rx during the l-th iteration. DM,l .

[0032] Preferably, the calculation of the IRS reflection coefficient matrix in the l-th iteration is... Its calculation is given by the following formula:

[0033]

[0034] stβ m ∈[0,1],α m ∈[0,2π),m∈{1,…,M}

[0035] in, Let α represent the reflection coefficient matrix of the passive IRS in the l-th iteration. m and β m These represent the reflection phase coefficient and reflection amplitude coefficient when the m-th DMRU uses the IRS mode, respectively;

[0036] The beamforming matrix W of Tx at the l-th iteration is calculated using the zero-forcing beamforming algorithm. Tx,l Beamforming matrix W of DMR DF,l for:

[0037]

[0038]

[0039] in, This represents the equivalent channel matrix from Tx through all DMRUs using IRS reflection in the DMR to Rx. S represents the equivalent channel matrix between all DMRUs using DF relay forwarding and Rx in DMR; l+1 Φ represents the DMR operating mode selection matrix for the l-th iteration. l+1 Let represent the reflection coefficient matrix of the IRS in the l-th iteration;

[0040] The data rate of Rx during the l-th iteration is:

[0041]

[0042] in, It is the equivalent channel matrix The m-th row vector, It is the equivalent channel matrix The m-th row vector, Rx represents the filter vector used to recover the m-th data stream; w DF,l,m and w Tx,l,m Representing the beamforming matrix W respectively DF,l and W Tx,l The m-th column vector, The variance of additive Gaussian white noise.

[0043] Preferably, in step S104, the data rate R of Rx during the lth iteration is calculated. DM,l The data rate R of Rx in the (l-1)th iteration DM,l-1 The absolute value of the difference R dif =|R DM,l -R DM,l-1 |, if the absolute value R dif The convergence threshold ε is greater than the maximum number of iterations l. max Execute step S103; otherwise, select the DMR working mode selection matrix S. n The data rate R of the l-th iteration Rx DM,l The beamforming matrix W of Tx Tx,l Beamforming matrix W of DMR DF,lAnd the reflection coefficient matrix Φ of the IRS l Add to collection respectively set Ω R ,gather gather and set Ω Φ In, that is Ω R ←Ω R ∪{R DM,l}、 and Ω Φ ←Ω Φ ∪{Φ l}

[0044] Preferably, in step S105, the optimal data rate set Ω of Rx is compared. R The DMR selects the DMR operating mode corresponding to the element with the largest value in the Rx data rate set, based on the data rate of all elements within the set, and adjusts the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS. The implementation method is as follows:

[0045] From DMR working mode set Select the optimal data rate R DM,max DMR operating mode selection matrix S max Select matrix S according to DMR working mode max Adjust the operating mode of the DMR from the beamforming matrix set. Beamforming matrix set and the set of IRS reflection coefficient matrices Ω Φ Select the optimal data rate R respectively DM,max The beamforming matrix W of Tx Tx,max Beamforming matrix W of DMR DF,max And the reflection coefficient matrix Φ of the IRS max According to the beamforming matrix W Tx,max Beamforming matrix W DF,max The reflection coefficient matrix Φ of IRS max Adjust the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS respectively.

[0046] A wireless communication system employing the aforementioned intelligent reflective surface-assisted dual-mode relay adaptive transmission method includes a Tx, an Rx, and a DMR, wherein communication between the Tx and Rx is assisted by the DMR.

[0047] Compared with existing technologies, the beneficial effects of this invention are as follows: It proposes a dual-mode relay DMR capable of dynamically switching between active relay and passive intelligent reflector operating modes. The dual-mode relay consists of multiple dual-mode relay units (DMRUs), each capable of intelligently selecting either active relay or passive reflector operating mode based on the wireless channel state. Multiple dual-mode relay units jointly process the incident signal to complete the relay of signal or data information. Combined with the passive characteristics of the intelligent reflector, the high energy consumption problem of active relay can be overcome. Under the constraint of limited transmit power, an adaptive transmission method for dual-mode relay based on alternating optimization is designed. Alternating optimization is used to design the reflection coefficient matrix of the intelligent reflector, as well as the beamforming matrix of the transmitter and dual-mode relay, improving the data rate of the receiver. This invention uses a dual-mode relay capable of dynamically selecting operating modes, integrating active relay and intelligent reflector into a single dual-mode relay. This dual-mode relay device can select the appropriate operating mode according to the communication environment, thereby improving communication quality without increasing energy consumption. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart of the present invention.

[0050] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0051] Figure 3 This is a flowchart illustrating the implementation of the present invention.

[0052] Figure 4 This invention is based on Figure 2 The system is compared with other fixed-mode Rx data rate performance using MATLAB simulation graphs. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Example 1

[0055] like Figure 1 As shown, the intelligent reflector-assisted dual-mode relay adaptive transmission method provided by the present invention includes the following steps:

[0056] S101: DMR (Dual-Mode Relay) consists of multiple dual-mode relay units (DMRUs). Under the control of the Tx (Transmitter), the DMRU intelligently selects either active relay or intelligent reflector (IRS) mode for signal forwarding or reflection. All DMR operating modes form a DMR operating mode set. The maximum Rx (Receiver) data rate operating mode set is initialized, and the convergence threshold and maximum number of iterations are set. The maximum Rx data rate operating mode set stores the maximum data rate of the receiver in each DMR operating mode.

[0057] like Figure 2 As shown, the system utilized in this embodiment is considered to be a communication system consisting of a transmitter (Tx), a receiver (Rx), and a dual-mode relay (DMR). Tx is equipped with N... T One transmitting antenna, Rx configured with N R Root receiving antenna. Tx with power P T Transmitting signals. Assume there are obstacles or severe channel fading between Tx and Rx, resulting in no direct transmission link meeting communication quality requirements between them. Therefore, communication between Tx and Rx requires the assistance of DMR. DMR is composed of N DM It consists of two dual-mode repeater units (DMRUs). Under the control of the control unit (CU) of Tx, the DMRU can intelligently select active repeater or passive reflection mode for signal / data forwarding. When the DMRU adopts active repeater mode, it operates in full-duplex DF (active decode-and-forward) repeater mode, and the transmit power of the DMR forwarded signal is P. DM The DF relay decodes and forwards the incident signal; thanks to instantaneous relay technology, this processing delay is negligible. Therefore, signals from all (active) relayed and (passive) reflected signals in all DMRUs can arrive at Rx simultaneously. Tx dynamically selects and configures the operating mode and parameters of the DMRUs through the CU. Before formal communication, Tx broadcasts pilot signals. All DMRUs in the DMR operate in passive IRS mode, and Rx estimates the Channel State Information (CSI) between itself, the IRS, and Tx. Figure 2 The H and G values ​​are fed back to Tx, which allows Tx to obtain channel information.

[0058] Tx sends data information The superscript T indicates the transpose operation. Tx uses the beamforming matrix. Preprocess x and map x to N T Transmit using a single transmitting antenna. and Let CSI represent the relationship between Tx and DMR, and between DMR and Rx. Assume that H and G have quasi-static flat fading characteristics, are independent, and are complex Gaussian random variables with zero mean and unit variance. This embodiment assumes N... T =N R =N DM =N I =M, where M is a positive integer.

[0059] S102: Select an arbitrary working mode selection matrix from the DMR working mode set, set the working mode of DMR according to the working mode selection matrix, and delete the working mode selection matrix from the DMR working mode set; initialize the number of iterations and the reflection coefficient matrix of IRS at the 0th iteration, and calculate the beamforming matrix of Tx and DMR and the data rate of Rx at the 0th iteration.

[0060] S103: Increment the iteration number by 1, calculate the reflection coefficient matrix of IRS during iteration, calculate the beamforming matrices of Tx and DMR, and calculate the data rate of Rx;

[0061] S104: Calculate the absolute value of the data rate difference of Rx obtained in adjacent iterations. If the absolute value of the data rate difference of Rx is greater than the convergence threshold and the number of iterations has not exceeded the maximum number of iterations, return to step S103. Otherwise, record the final data rate of Rx, the current DMR working mode selection matrix, the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS, and execute step S105.

[0062] S105: Determine if the DMR operating mode set is empty. If the DMR operating mode set is not empty, proceed to step S102. Otherwise, compare the data rates of all Rx values. DMR selects the DMR operating mode corresponding to the highest data rate of Rx and adjusts the beamforming matrix of Tx and DMR, as well as the reflection coefficient matrix of IRS.

[0063] The intelligent reflector-assisted dual-mode relay adaptive transmission method provided by this invention can also be implemented using other steps by those skilled in the art. Figure 1 The intelligent reflective surface-assisted dual-mode relay adaptive transmission method provided by the present invention is merely a specific embodiment.

[0064] Example 2

[0065] The following is in conjunction with the appendix Figure 3 The technical solution of the present invention will be further described below. The intelligent reflector-assisted dual-mode relay adaptive transmission method provided by the present invention shall include the following steps:

[0066] Step 1: Consider a wireless communication system consisting of one transmitter (Tx), one receiver (Rx), and a dual-mode repeater (DMR). Tx and Rx are each configured with M transmit antennas. The DMR consists of M dual-mode repeater units (DMRUs). Under the control of Tx, the DMRUs intelligently select either decode-forward relay or intelligent reflector (IRS) mode for signal forwarding or reflection. All DMR operating modes form the DMR operating mode set Ω. S Define the set of optimal data rates Ω that Rx can achieve in each operating mode of DMR. R Define the set of DMR operating modes that enable Rx to achieve the optimal data rate. Define the set of Tx beamforming matrices that enable Rx to achieve the optimal data rate. and DMR beamforming matrix set Define the set of IRS reflection matrices Ω that enables Rx to achieve the optimal data rate. Φ Set the convergence threshold ε and the maximum number of iterations l. max .

[0067] The steps to implement step one are as follows:

[0068] Consider a communication system consisting of one transmitter (Tx), one receiver (Rx), and a dual-mode repeater (DMR). Tx and Rx are each equipped with M transmit antennas. The DMR consists of M dual-mode repeater units (DMRUs). Under the control of Tx, the DMRUs intelligently select either decode-forward relay or intelligent reflector (IRS) mode for signal forwarding or reflection. All DMR operating modes form the DMR operating mode set Ω. S ,use and This represents the channel state information between Tx and DMR, and between DMR and Rx; Tx is expressed in terms of power. The power of the transmitted signal and the DMR relay signal is P total This represents the total transmission power of the system.

[0069] Define the set of all DMR operating modes as Ω. S ={S1,…,S n ,…,S 2M}, S n =diag(s n,1 ,…,s n,M) represents the selection matrix for the nth DMR operating mode, and Tx is based on the DMR operating mode selection matrix S. n Controlling the DMR operating mode, element s n,m =1 indicates that the m-th DMRU uses DF relay forwarding, s n,m =0 indicates that the m-th DMRU uses IRS reflection, where m∈{1,…,M}, and M represents the number of transmit antennas of Tx, the number of receive antennas of Rx, and the number of DMRUs included in the DMR;

[0070] initialization Indicates an empty set; initializes the DMR working mode S. n Let S1 be the number of nodes, i.e., n = 1. Set the convergence threshold ε = 10. -5 and maximum number of iterations l max =50.

[0071] Step 2: From the DMR working mode set Ω S An arbitrary selection of the working mode selection matrix S n (S n ∈Ω S Select matrix S according to the working mode. n Set the DMR's operating mode and select the operating mode matrix S. n From the DMR working mode set Ω S Remove the following: Initialize the iteration number l = 0 and the reflection coefficient matrix Φ0 = I of IRS at the 0th iteration; use the zero-forcing beamforming algorithm to calculate the beamforming matrices W of Tx and DMR at the 1st iteration. Tx,0 and W DF,0 and the data rate Rx DM,0 .

[0072] Select matrix S based on the working mode. n Adjusting the DMR's operating mode involves selecting matrix S based on the operating mode. n The values ​​of the elements in the matrix M are used by DMRUs for DF relay forwarding or IRS reflection. The operating mode selection matrix S is used. n From the DMR working mode set Ω S Delete, i.e., Ω S =Ω S -{S n} indicates that DMR has been configured in working mode S n The beamforming matrices of Tx and DMR, as well as the reflection coefficient matrix of IRS, were optimized.

[0073] Initialize the iteration count l = 0, and set the reflection coefficient matrix Φ0 = I for the 0th iteration. Calculate the Tx beamforming matrix W for the 0th iteration using the Zero-Forcing (ZF) algorithm. Tx,0 and DMR beamforming matrix W DF,0 Its calculation is given by the following formula:

[0074]

[0075]

[0076] in, This represents the equivalent channel matrix from Tx through all DMRUs using IRS reflection in the DMR to Rx. Φ represents the equivalent channel matrix between all DMRUs and Rx using DF relay forwarding in DMR; H represents the matrix transformation; S1 represents the current DMR operating mode selection matrix; and Φ1 represents the current IRS reflection coefficient matrix.

[0077] The data rate of Rx during the 0th iteration is:

[0078]

[0079] in, It is the equivalent channel matrix The m-th row vector, It is the equivalent channel matrix The m-th row vector, Rx represents the filter vector used to recover the m-th data stream; w DF,0,m and w Tx,0,m Representing the beamforming matrix W respectively DF,0 and W Tx,0 The m-th column vector, The variance of additive Gaussian white noise.

[0080] Step 3: Increment the iteration number l by 1, i.e., l ← l+1, and calculate the reflection coefficient matrix Φ of the IRS at the l-th iteration. l The beamforming matrix W of Tx and DMR at the l-th iteration is calculated using the zero-forcing beamforming algorithm. Tx,l and W DF,l Calculate the data rate R of Rx during the l-th iteration. DM,l .

[0081] Calculate the IRS reflection coefficient matrix for the l-th iteration. Its calculation is given by the following formula:

[0082]

[0083] stβm ∈[0,1],α m ∈[0,2π),m∈{1,…,M}

[0084] in, Let α represent the reflection coefficient matrix of the passive IRS in the l-th iteration. m and β m Let represent the reflection phase coefficient and reflection amplitude coefficient of the m-th (m∈{1,…,M}) DMRU in IRS mode, respectively.

[0085] The beamforming matrix W of Tx at the l-th iteration is calculated using the zero-forcing beamforming algorithm. Tx,l Beamforming matrix W of DMR DF,l Its calculation is given by the following formula:

[0086]

[0087]

[0088] in, This represents the equivalent channel matrix from Tx through all DMRUs using IRS reflection in the DMR to Rx. S represents the equivalent channel matrix between all DMRUs using DF relay forwarding and Rx in DMR; l+1 Φ represents the DMR operating mode selection matrix for the l-th iteration. l+1 Let represent the reflection coefficient matrix of the IRS in the l-th iteration.

[0089] The data rate of Rx during the l-th iteration is:

[0090]

[0091] in, It is the equivalent channel matrix The m-th row vector, It is the equivalent channel matrix The m-th row vector, Rx represents the filter vector used to recover the m-th data stream; w DF,l,m and w Tx,l,m Representing the beamforming matrix W respectively DF,l and W Tx,l The m-th column vector, The variance of additive Gaussian white noise.

[0092] Step 4: Calculate the data rate R of Rx in the l-th iteration. DM,l The data rate R of Rx in the (l-1)th iteration DM,l-1 The absolute value of the difference R dif =|RDM,l -R DM,l-1 |, if R dif The value is greater than the convergence threshold ε, and the number of iterations l does not exceed the maximum number of iterations l. max Proceed to step three; otherwise, select the DMR working mode selection matrix S. n Rx data rate R DM,l Beamforming matrices W for Tx and DMR Tx,l and W DF,l and the reflection coefficient matrix Φ of the IRS l Add to collection respectively Ω R , and Ω Φ Then proceed to step five.

[0093] If the absolute value R dif >ε and l≤l max Proceed to step three; otherwise, select the DMR working mode selection matrix S. n The data rate R of the l-th iteration Rx DM,l The beamforming matrix W of Tx Tx,l Beamforming matrix W of DMR DF,l And the reflection coefficient matrix Φ of the IRS l Add to collection respectively Ω R , and Ω Φ In, that is Ω R ←Ω R ∪{R DM,l}、 and Ω Φ ←Ω Φ ∪{Φ l}, and proceed to step five.

[0094] Step 5: Determine the DMR operating mode set Ω S If the DMR operating mode set is not empty, proceed to step two; otherwise, compare the Rx data rate set Ω. R The algorithm calculates the data rate of all elements within the set, selects the DMR operating mode corresponding to the element with the largest value in the Rx data rate set, and adjusts the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS. The algorithm then ends.

[0095] Determine Ω S Is it an empty set? This indicates that the beamforming matrix of Tx and DMR, as well as the reflection coefficient matrix of IRS, have not yet been optimized for all DMR operating modes. Set n←n+1, switch to other DMR operating modes, and execute step two.

[0096] From DMR working mode set Select the optimal data rate R DM,max DMR operating mode selection matrix S max Select matrix S according to DMR working mode max S max Adjust the operating mode of the DMR from the beamforming matrix set. Beamforming matrix set and the set of IRS reflection coefficient matrices Ω Φ Select the optimal data rate R respectively DM,max The beamforming matrix W of Tx and DMR Tx,max and W DF,max And the reflection coefficient matrix Φ of the IRS max According to the beamforming matrix W Tx,max Beamforming matrix W DF,max The reflection coefficient matrix Φ of IRS max The beamforming matrices of Tx and DMR, as well as the IRS reflection coefficient matrix, are adjusted respectively to increase the receiver's data rate without increasing energy consumption. The algorithm then terminates.

[0097] The technical effects of the present invention will be described in detail below with reference to simulation.

[0098] 1. Simulation conditions:

[0099] Simulation parameters: In the simulation, M is set to 2, and the total system transmit power is set to P. total =P T +P DM ,make Set the convergence threshold ε = 10 -5 and maximum number of iterations l max =50. When all DMRUs included in the DMR use IRS passive reflection, the DMR does not need to consume power, and P is then... DM =0, for a fair comparison, the power of DMR is set to 0. Allocate it to Tx, that is, let P T =P total Define the signal-to-noise ratio. And set SNR∈[0,20]dB. When M=2, initialize the DMR working mode set Ω. S= {S1, S2, S3, S4}, where the elements S1, S2, S3, S4 are diag(0,0), diag(0,1), diag(1,0), and diag(1,1), respectively.

[0100] 2. Simulation content and analysis:

[0101] The invention was simulated using MATLAB. First, the DMR operating mode was set according to S1, the iteration number l = 0 and the reflection coefficient matrix Φ0 = I of the IRS at the 0th iteration were initialized, and the beamforming matrix W of Tx and DMR at the 0th iteration was calculated according to the zero-forcing beamforming algorithm. Tx,0 and W DF,0 It is important to note that when all DMRUs operate in IRS mode (diag(0,0), DMR does not require beamforming. In this case, W... DF,0 =O, where Represent the zero matrix, and then calculate the data rate R of Rx. DM,0 Increment the iteration number l by 1, i.e., l ← l+1, and calculate the reflection coefficient matrix Φ of the IRS at the l-th iteration. l and the beamforming matrices W of Tx and DMR at the l-th iteration. Tx,l and W DF,l Calculate the data rate R of Rx during the l-th iteration. DM,l Calculate the data rate R of Rx in the l-th iteration. DM,l The data rate R of Rx in the (l-1)th iteration DM,l-1 The absolute value of the difference R dif If R dif The value is greater than the convergence threshold ε, and the number of iterations l does not exceed the maximum number of iterations l. max Increment the iteration number l by 1, i.e., l ← l+1, and readjust the reflection coefficient matrix Φ of the IRS. l Calculate the beamforming matrices W of Tx and DMR at the l-th iteration. Tx,l and W DF,l And calculate R DM,l and R dif until R is satisfied dif Less than the convergence threshold ε or the number of iterations l is greater than the maximum number of iterations l max Select the DMR working mode matrix S n Rx data rate R DM,l Beamforming matrices W for Tx and DMR Tx,l and W DF,l and IRS reflection matrix Φ l Add to each Ω R , and Ω ΦFollowing the above process, simulations are performed on S2, S3, and S4.

[0102] The technical effects of this invention are described in detail below with reference to simulation. This invention uses MATLAB to simulate the average data rate of different methods, and the results are as follows: Figure 4 As shown, DMRAT-AO represents the data rate of Rx obtained by the method of the present invention, DMR-R represents the data rate of Rx when the DMR randomly selects its operating mode, DMR-IRS represents the data rate of Rx when all DMRUs of the DMR use IRS mode to reflect the signal from Tx, and DMR-DF represents the data rate of Rx when all DMRUs of the DMR use DF mode to decode and forward the signal transmitted by Tx. Figure 4 It is known that the DMRAT-AO designed in this invention has the highest data rate and can select the DMR working mode with the best data rate performance, thus significantly improving the rate performance of Rx.

[0103] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dual-mode relay adaptive transmission method assisted by a smart reflector, characterized in that, The steps are as follows: S101: DMR consists of multiple DMRUs. Under the control of Tx, the DMRUs intelligently select the active relay or IRS reflection mode to forward or reflect signals. All DMR operating modes form a DMR operating mode set. Set the convergence threshold and the maximum number of iterations; S102: Select an arbitrary working mode selection matrix from the DMR working mode set, set the working mode of DMR according to the working mode selection matrix, and delete the working mode selection matrix from the DMR working mode set; initialize the number of iterations and the reflection coefficient matrix of IRS at the 0th iteration, and calculate the beamforming matrix of Tx and DMR and the data rate of Rx at the 0th iteration. S103: Increment the iteration count by 1, and calculate the reflection coefficient matrix of IRS, the beamforming matrix of Tx and DMR, and the data rate of Rx during the iteration. S104: Calculate the absolute value of the data rate difference of Rx obtained in adjacent iterations. If the absolute value of the data rate difference of Rx is greater than the convergence threshold and the number of iterations has not exceeded the maximum number of iterations, return to step S103. Otherwise, record the final data rate of Rx, the current DMR working mode selection matrix, the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS, and execute step S105. S105: Determine if the DMR working mode set is empty. If the DMR working mode set is not empty, return to step S102. Otherwise, by comparing the data rates of all Rx values, DMR selects the DMR operating mode corresponding to the maximum data rate of Rx, and adjusts the beamforming matrix of Tx and DMR, as well as the reflection coefficient matrix of IRS.

2. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to claim 1, characterized in that, The Tx is equipped with N T One transmitting antenna, Rx configured with N R Root receiving antenna, Tx with power P T Transmit signal; DMR is generated by N DM It consists of DMRUs, which can intelligently select active relay or passive reflection mode for signal / data forwarding under the control of the control unit CU under Tx. When the DMRU adopts active relay mode, it operates in full-duplex DF relay mode, and the transmit power of the DMR forwarded signal is P. DM Tx dynamically selects and configures the operating mode and parameters of the DMRU through the control unit CU. Before formal communication, Tx broadcasts pilot signals. All DMRUs of the DMR adopt the passive IRS operating mode. Rx estimates the channel state information between itself, the IRS and Tx and feeds it back to Tx. Tx sends data information The superscript T indicates the transpose operation; Tx uses the beamforming matrix. Preprocess the data information x and map the data information x to N. T Transmit using a single transmitting antenna; and H and G represent the channel state information between Tx and DMR, and between DMR and Rx. H and G exhibit quasi-static flat fading characteristics and are independent of each other. Their elements are complex Gaussian random variables with zero mean and unit variance; and N T =N R =N DM =N I =M, where M is a positive integer.

3. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to claim 1 or 2, characterized in that, In step S101, the optimal data rate set Ω of Rx obtained in each operating mode of DMR is initialized. R A set of DMR operating modes that enable Rx to achieve the optimal data rate The set of Tx beamforming matrices that enables Rx to achieve the optimal data rate and DMR beamforming matrix set The set of IRS reflection matrices Ω that enables Rx to achieve the optimal data rate Φ ;initialization Represents an empty set; Tx with power The power of the transmitted signal and the DMR relay signal is P total This represents the total transmit power of the system. The DMR working mode set consists of all DMR working modes S n =diag(s n,1 ,…,s n,M ) represents the selection matrix for the nth DMR operating mode, and Tx is based on the DMR operating mode selection matrix S. n Controlling the DMR operating mode, element s n,m =1 indicates that the m-th DMRU uses DF relay forwarding, s n,m =0 indicates that the m-th DMRU uses IRS reflection, where m∈{1,…,M}, and M represents the number of transmit antennas of Tx, the number of receive antennas of Rx, and the number of DMRUs included in the DMR; Initialize DMR operating mode S n Let's call it S1.

4. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to claim 3, characterized in that, Initialize the iteration number l = 0 and the reflection coefficient matrix Φ0 = I of IRS at the 0th iteration, and use the zero-forcing beamforming algorithm to calculate the beamforming matrix W of Tx at the 0th iteration. Tx,0 Beamforming matrix W of DMR DF,0 And the data rate of Rx.

5. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to claim 4, characterized in that, The zero-forcing beamforming algorithm is used to calculate the Tx beamforming matrix W at the 0th iteration. Tx,0 and DMR beamforming matrix W DF,0 The method is as follows: in, This represents the equivalent channel matrix from Tx through all DMRUs using IRS reflection in the DMR to Rx. Φ represents the equivalent channel matrix between all DMRUs and Rx using DF relay forwarding in DMR; H represents the matrix transformation, S1 represents the current DMR operating mode selection matrix, and Φ1 represents the current IRS reflection coefficient matrix. The data rate of Rx during the 0th iteration is: in, It is the equivalent channel matrix The m-th row vector, It is the equivalent channel matrix The m-th row vector, Rx represents the filter vector used to recover the m-th data stream; w DF,0,m and w Tx,0,m Representing the beamforming matrix W respectively DF,0 and W Tx,0 The m-th column vector, The variance of additive Gaussian white noise.

6. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to any one of claims 2, 4, or 5, characterized in that, In step S103, the iteration number l is incremented by 1, and the reflection coefficient matrix Φ of the IRS at the l-th iteration is calculated. l The beamforming matrix W of Tx and DMR at the l-th iteration is calculated using the zero-forcing beamforming algorithm. Tx,l and W DF,l Calculate the data rate R of Rx during the l-th iteration. DM,l .

7. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to claim 6, characterized in that, The calculation of the IRS reflection coefficient matrix in the l-th iteration Its calculation is given by the following formula: stβ m ∈[0,1],a m ∈[0,2π),m∈{1,…,M} in, Let α represent the reflection coefficient matrix of the passive IRS in the l-th iteration. m and β m These represent the reflection phase coefficient and reflection amplitude coefficient when the m-th DMRU uses the IRS mode, respectively; The beamforming matrix W of Tx at the l-th iteration is calculated using the zero-forcing beamforming algorithm. Tx,l Beamforming matrix W of DMR DF,l for: in, This represents the equivalent channel matrix from Tx through all DMRUs using IRS reflection in the DMR to Rx. S represents the equivalent channel matrix between all DMRUs using DF relay forwarding and Rx in DMR; l+1 Φ represents the DMR operating mode selection matrix for the l-th iteration. l+1 Let represent the reflection coefficient matrix of the IRS in the l-th iteration; The data rate of Rx during the l-th iteration is: in, It is the equivalent channel matrix The m-th row vector, It is the equivalent channel matrix The m-th row vector, Rx represents the filter vector used to recover the m-th data stream; w DF,l,m and w Tx,l,m Representing the beamforming matrix W respectively DF,l and W Tx,l The m-th column vector, The variance of additive Gaussian white noise.

8. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to any one of claims 4, 5, or 7, characterized in that, In step S104, the data rate R of Rx during the lth iteration is calculated. DM,l The data rate R of Rx in the (l-1)th iteration DM,l-1 The absolute value of the difference R dif =|R DM,l -R DM,l-1 |, if the absolute value R dif The convergence threshold ε is greater than the maximum number of iterations l. max Execute step S103; otherwise, select the DMR working mode selection matrix S. n The data rate R of the l-th iteration Rx DM,l The beamforming matrix W of Tx Tx,l Beamforming matrix W of DMR DF,l And the reflection coefficient matrix Φ of the IRS l Add to collection respectively set Ω R ,gather gather and set Ω Φ In, that is Ω R ←Ω R ∪{R DM,l }、 and Ω Φ ←Ω Φ ∪{Φ l } 9. The intelligent reflector-assisted dual-mode relay adaptive transmission method according to claim 1, characterized in that, In step S105, the optimal data rate set Ω of Rx is compared. R The DMR selects the DMR operating mode corresponding to the element with the largest value in the Rx data rate set, based on the data rate of all elements within the set, and adjusts the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS. The implementation method is as follows: From DMR working mode set Select the optimal data rate R DM,max DMR operating mode selection matrix S max Select matrix S according to DMR working mode max Adjust the operating mode of the DMR from the beamforming matrix set. Beamforming matrix set and the set of IRS reflection coefficient matrices Ω Φ Select the optimal data rate R respectively DM,max The beamforming matrix W of Tx Tx,max Beamforming matrix W of DMR DF,max And the reflection coefficient matrix Φ of the IRS max According to the beamforming matrix W Tx,max Beamforming matrix W DF,max The reflection coefficient matrix Φ of IRS max Adjust the beamforming matrix of Tx and DMR and the reflection coefficient matrix of IRS respectively.

10. A wireless communication system using the intelligent reflective surface-assisted dual-mode relay adaptive transmission method according to any one of claims 1 to 9, comprising a Tx, an Rx, and a DMR, wherein communication between Tx and Rx is assisted by the DMR.

Images