Low-power intelligent metasurface hardware structure, precoding method and device

Abstract

The present invention provides a low-power intelligent metasurface hardware structure, precoding method and device, the hardware structure comprising: a plurality of subarrays, an amplification circuit corresponding to each subarray, and a phase shift circuit corresponding to each RIS unit; wherein each subarray comprises a plurality of RIS units, different RIS units of each subarray share an amplification circuit, and each RIS unit uses a different phase shift circuit. The hardware structure effectively solves the high power consumption problem of active RIS due to the introduction of a large number of active amplification circuits by sharing an amplification circuit by a subarray composed of a plurality of RIS units. Compared with the traditional fully connected structure, the intelligent metasurface hardware structure of the present invention can obtain significant energy efficiency improvement. Its precoding method aims to maximize the system energy efficiency, optimizes the sub-connected active RIS amplification control and phase shift control, and can effectively save the system energy consumed by a large number of amplification circuits.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a low-power intelligent metasurface hardware structure, a precoding method and a device. Background Art

[0002] Reconfigurable Intelligent Surface (RIS) is considered to be one of the key technologies for future 6G communications. Figure 1 As shown in part a of Figure 1, RIS is a large-scale array composed of a large number of passive units that can adjust the signal phase. It can intelligently adjust the incident signal so that it can be reflected in any specified direction with high gain. Since RIS has low cost and power consumption, it has application value in overcoming interruptions, increasing capacity, and saving transmission power.

[0003] like Figure 2 As shown in the figure, the introduction of RIS brings about the "multiplicative path loss effect", that is, the path loss of the transmitter-RIS-receiver link is the product of the path loss of the two sections of the signal (rather than the sum), which makes its gain much smaller than the direct link gain. This "multiplicative path loss effect" makes it difficult for RIS to show obvious advantages in scenarios with strong direct links, resulting in fatal problems. In order to overcome the "multiplicative path loss effect", a new technology called active RIS was proposed, which can improve capacity regardless of whether the direct link is strong or weak. Specifically, as Figure 1 As shown in part b of the figure, unlike the traditional passive RIS which only performs phase control on the signal, the active RIS also integrates an amplifier circuit in addition to the phase shift circuit of each unit, so that the RIS can amplify the reflected signal and further convert the multiplicative path loss into additive path loss.

[0004] However, the existing active RIS structure is a fully connected structure in which each unit integrates an independent phase shift circuit and an amplifier circuit, which greatly increases the power consumption of the active RIS as the number of units increases. For example, if each amplifier circuit consumes 10mW of static power, a 1000-unit active RIS will consume 10W of static power in the amplifier circuit alone, which is comparable to the transmission power of a typical base station and is unacceptable in actual deployment. Therefore, active RIS requires a new structure different from the fully connected structure to save power consumption. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a low-power intelligent metasurface hardware structure, a precoding method and a device.

[0006] The present invention provides a low-power intelligent metasurface hardware structure, comprising: a plurality of subarrays, an amplifying circuit corresponding to each subarray one by one, and a phase shifting circuit corresponding to each intelligent metasurface RIS unit; wherein each subarray comprises a plurality of RIS units, different RIS units of each subarray share an amplifying circuit, and each RIS unit uses a different phase shifting circuit.

[0007] The present invention also provides a precoding method based on the above-mentioned low-power intelligent metasurface hardware structure, including: precoding based on pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplifier circuit to achieve beamforming; taking the maximum power of the base station and the RIS as a constraint condition, determining the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency as the corresponding precoding scheme; wherein the system is a system composed of a user terminal, a RIS and a base station.

[0008] According to the precoding method of a low-power intelligent metasurface hardware structure of one embodiment of the present invention, the system energy efficiency is determined according to the ratio of the system spectrum efficiency to the total power consumption of the system.

[0009] According to the precoding method of a low-power intelligent metasurface hardware structure of one embodiment of the present invention, before determining the adjustment results of the phases of all phase shift circuits and coefficients of the amplification circuits that maximize the system energy efficiency, it also includes: determining the system spectrum efficiency based on the signal-to-noise ratio of the demodulated signals at all user terminals.

[0010] According to a precoding method for a low-power intelligent metasurface hardware structure of an embodiment of the present invention, before determining the system spectrum efficiency according to the signal-to-noise ratio of the demodulated signals at all user terminals, the method further includes determining the signal-to-noise ratio of the demodulated signal at each user terminal according to the following formula:

[0011]

[0012] Where K is the number of users served by the base station, and j and k represent the corresponding single users; represents the equivalent channel from the base station to user k; Ψ = diag (ΘΓa) represents the beamforming matrix of active RIS; represents the diagonal phase shift matrix, represents the amplification factor vector, N is the total number of RIS units, and L represents the number of amplification circuits; Indicates the connection relationship between the amplifier circuit and the phase shift circuit; and denote the channels between the base station and user k, the base station and the active RIS, and the active RIS and user k, respectively. M is the number of base station antennas. represents the base station beamforming vector; σ 2are the parameters of the dynamic noise introduced by active RIS and the additive white Gaussian noise at the user, respectively.

[0013] According to a precoding method for a low-power intelligent metasurface hardware structure according to an embodiment of the present invention, before determining the adjustment results of all phase shift circuits and amplification circuits that maximize the system energy efficiency, it also includes determining the total power consumption of the system according to the following formula:

[0014]

[0015] Where ξ and ζ represent the inverse of the energy conversion coefficients of the base station and active RIS, W U and W BS represents the static power consumption of user terminals and base stations, W PS and W PA represents the static power consumption of the phase shift circuit and the amplifier circuit; K is the number of users served by the base station, k represents the corresponding single user, represents the base station beamforming vector; Ψ=diag(ΘΓa) represents the beamforming matrix of active RIS; represents the diagonal phase shift matrix, represents the magnification factor vector; Indicates the connection relationship between the amplifier circuit and the phase shift circuit; represents the channel between the base station and the active RIS; N is the total number of RIS units, and L represents the number of amplification circuits; Parameters of dynamic noise introduced by active RIS.

[0016] According to a precoding method for a low-power intelligent metasurface hardware structure of an embodiment of the present invention, the adjustment results of the phases of all phase shift circuits and coefficients of the amplification circuits that maximize the energy efficiency of the system are determined as corresponding precoding schemes, including:

[0017] S1. Use the fractional optimization Dinkelbach algorithm to transform the system energy efficiency optimization problem into a rational planning problem;

[0018] S2. Use the Lagrange dual method to introduce auxiliary variables and transform the rational programming problem into a convex optimization problem;

[0019] S3. Keep other variables unchanged and optimize auxiliary variables, base station beamforming, active RIS amplification control and phase shift control variables in order;

[0020] S4. Repeat S3 until the objective function converges;

[0021] S5. Repeat S2-S4 until the objective function converges to 0. At this time, the precoding scheme obtained is an active RIS precoding scheme that maximizes the system energy efficiency.

[0022] The present invention also provides a precoding device of a low-power intelligent metasurface hardware structure, comprising: an allocation module, used to implement beamforming precoding based on pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplifier circuit; a processing module, used to determine the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency based on the maximum power of the base station and the RIS as a constraint condition, as a corresponding precoding scheme; wherein the system is a system composed of a user terminal, a RIS and a base station.

[0023] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a precoding method for a low-power intelligent metasurface hardware structure as described in any one of the above are implemented.

[0024] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a precoding method for a low-power intelligent metasurface hardware structure as described in any one of the above.

[0025] The low-power intelligent metasurface hardware structure, precoding method and device provided by the present invention effectively solve the high power consumption problem of active RIS due to the introduction of a large number of active amplifier circuits by using a sub-array composed of multiple RIS units to share an amplifier circuit. Compared with the traditional fully connected structure, the intelligent metasurface hardware structure of the present invention can achieve significant energy efficiency improvement and can be used as a high-energy-efficiency implementation method of active RIS. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 It is a schematic diagram of the structure of a passive RIS and a fully connected active RIS in the prior art;

[0028] Figure 2 It is a schematic diagram of the structure of a RIS-assisted MIMO system in the prior art;

[0029] Figure 3 It is a schematic diagram of the hardware structure of the low-power intelligent metasurface provided by the present invention;

[0030] Figure 4 It is a schematic diagram of the energy efficiency performance of the low-power intelligent metasurface hardware structure and the precoding method thereof provided by the present invention;

[0031] Figure 5 It is a structural schematic diagram of a low-power intelligent metasurface hardware structure precoding device provided by the present invention;

[0032] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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.

[0034] Combine the following Figure 1-Figure 6 The low-power intelligent metasurface hardware structure, precoding method and device of the present invention are described. Figure 3 Schematic diagram of the hardware structure of the low-power intelligent metasurface provided by the present invention. Figure 3 As shown, the present invention provides a low-power intelligent metasurface hardware structure, including: multiple sub-arrays, an amplification circuit corresponding to each sub-array, and a phase shift circuit corresponding to each intelligent metasurface RIS unit; wherein each sub-array includes multiple RIS units, different RIS units of each sub-array share an amplification circuit, and each RIS unit uses a different phase shift circuit.

[0035] The existing fully connected active RIS structures are as follows: Figure 2 As shown in part b, it is Figure 2 Based on the passive RIS of part a, each unit includes an independent amplifier circuit in addition to an independent phase shift circuit. However, when the number of RIS units is large, the fully connected structure will face high power consumption problems due to the use of a large number of active amplifier circuits.

[0036] In order to solve the high power consumption problem of the existing fully connected structure of active RIS, the present invention proposes Figure 3 In the sub-connection structure shown, multiple RIS units are divided into a sub-array. Each unit in the sub-array uses an independent phase shift circuit, but shares an amplifier circuit, that is, each unit independently controls the phase of the signal, but the entire sub-array uses the same signal amplification factor for signal amplitude control.

[0037] For the convenience of comparison, consider that each sub-array contains T RIS units, that is, one amplifier circuit serves T RIS units at the same time. At this time, the fully connected structure becomes a special case of the sub-connected structure when T=1. Under the condition of the same number of RIS units, the number of amplifier circuits of the sub-connected active RIS becomes 1 / T of that under the fully connected structure, which greatly reduces the energy consumption of the active RIS. At the same time, the degree of freedom of the sub-connected active RIS in the beamforming process is also reduced because the T RIS units share the same amplification factor. However, the present invention shows that the reduction in the beamforming freedom of the sub-connected active RIS structure has little effect, and the system can still achieve a significant improvement in energy efficiency due to the use of the sub-connected structure.

[0038] The low-power intelligent metasurface hardware structure provided by the present invention effectively solves the high power consumption problem of active RIS due to the introduction of a large number of active amplifier circuits by using a sub-array composed of multiple RIS units to share an amplifier circuit. Compared with the traditional fully connected structure, the intelligent metasurface hardware structure of the present invention can achieve significant energy efficiency improvement and can be used as a high-energy-efficiency implementation method of active RIS.

[0039] Based on the low-power intelligent metasurface hardware structure proposed in the present invention, the present invention also proposes a corresponding precoding method, including: based on pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplifier circuit to achieve beamforming precoding; taking the maximum power of the base station and the RIS as a constraint condition, determining the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency as the corresponding precoding scheme; wherein the system is a system composed of a user terminal, a RIS and a base station.

[0040] Specifically, the goal is to maximize the system energy efficiency by adjusting the amplification factor of each sub-array amplifier circuit and the phase of each phase shift circuit. Of course, in this process, the power of the base station and the active RIS does not exceed the maximum power.

[0041] The precoding method of the low-power intelligent metasurface hardware structure proposed in the present invention can effectively save system energy consumed by a large number of amplification circuits and effectively improve system energy efficiency.

[0042] In the above method embodiment, the system energy efficiency is determined according to the ratio of the system spectrum efficiency to the system total power consumption.

[0043] Specifically, the system energy efficiency can be expressed as:

[0044]

[0045] Wherein, R is the system spectrum efficiency, and P is the total power consumption of the system. In the precoding scheme, the optimization goal of the present invention is to maximize the system energy efficiency.

[0046] In the above method embodiment, before determining the adjustment results of the phases of all phase shift circuits and coefficients of the amplification circuits that maximize the system energy efficiency, it also includes: determining the system spectrum efficiency according to the signal-to-noise ratio of the demodulated signals at all user terminals.

[0047] Specifically, the system spectrum efficiency can be determined as follows:

[0048]

[0049] Where K is the number of users served by the base station; SINR k is the SINR of the demodulated signal at user k.

[0050] In the above method embodiment, before determining the system spectrum efficiency according to the signal-to-noise ratio of the demodulated signals at all user terminals, the method further includes determining the signal-to-noise ratio of the demodulated signal at each user terminal according to the following formula:

[0051]

[0052] Where K is the number of users served by the base station, and j and k represent the corresponding single users; represents the equivalent channel from the base station to user k; Ψ = diag(ψ) = diag(ΘΓa) represents the beamforming matrix of the active RIS; , N is the total number of RIS units, and L represents the number of amplifier circuits; and denote the channels between the base station and user k, the base station and the active RIS, and the active RIS and user k, respectively. M is the number of base station antennas. represents the base station beamforming vector.

[0053] Specifically, consider an N-unit active RIS-assisted MIMO system, where an M-antenna base station simultaneously serves K single-antenna users. For both full-connection and sub-connection structures, L = N / T represents the number of required amplification circuits, and the beamforming matrix of active RIS can be expressed as:

[0054] Ψ=diag(ψ)=diag(ΘΓa),

[0055] in, represents the same diagonal phase shift matrix as the conventional passive RIS, represents the magnification factor vector. is defined as a characteristic matrix, which is used to represent the connection relationship between the amplifier circuit and the phase shift circuit. Without loss of generality, let in represents the Kronecker product, Represents a vector of all 1s.

[0056] Then the signal y received by user k is k can be expressed as:

[0057]

[0058] Among them, s k represents the normalized symbol transmitted to user k, represents the corresponding base station beamforming vector, and They represent the dynamic noise introduced by active RIS and the additive white Gaussian noise at user k respectively.

[0059] In the above method embodiment, before determining the adjustment results of all phase shift circuits and amplification circuits that maximize the system energy efficiency, it also includes determining the total power consumption of the system according to the following formula:

[0060]

[0061] Where ξ and ζ represent the inverse of the energy conversion coefficients of the base station and active RIS, W U and W BS represents the static power consumption of user terminals and base stations, W PS and W PA Represents the static power consumption of the phase shift circuit and the amplifier circuit.

[0062] As for the power consumption of the system, it is composed of the transmission power of the base station and the active RIS, as well as the static power of each component of the system. The total power consumption of the system can be expressed as the above formula.

[0063] Combining the above signal model, And Θ = diag(θ), then the system energy efficiency maximization problem can be expressed as:

[0064]

[0065] stC1:

[0066] C2:

[0067] C3:

[0068] C4:

[0069] Among them, constraints C1 and C2 limit the maximum power of the base station and active RIS respectively, and constraints C3 and C4 limit the feasible sets of phase shift control θ and amplification control a respectively.

[0070] By solving the above optimization problem, the adjustment results of the phases of all phase shift circuits and the coefficients of the amplification circuits can be obtained, that is, the corresponding precoding scheme.

[0071] In one method embodiment, the adjustment results of the phases of all phase shift circuits and the coefficients of the amplification circuits that maximize the system energy efficiency are determined as the corresponding precoding scheme, including: S1. Using the fractional optimization Dinkelbach algorithm to convert the system energy efficiency optimization problem into a rational planning problem; S2. Using the Lagrange dual method to introduce auxiliary variables, converting the rational planning problem into a convex optimization problem; S3. Keeping other variables unchanged, optimizing the auxiliary variables, base station beamforming, active RIS amplification control and phase shift control variables in sequence; S4. Repeating S3 until the objective function converges; S5. Repeating S2-S4 until the objective function converges to 0, the precoding scheme obtained at this time is an active RIS precoding scheme that maximizes the system energy efficiency. The specific description is as follows:

[0072] In order to facilitate the processing of the above-mentioned fractional objective function, the embodiment of the present invention first uses the Dinkelbach algorithm in fractional programming to convert it into a rational form. Specifically, the optimal energy efficiency η opt satisfy:

[0073]

[0074] Explain the optimal energy efficiency η opt It can be obtained by iteratively solving the following problem:

[0075]

[0076] stC1,C2,C3,C4.

[0077] Since this problem still has non-convexity, the present invention introduces auxiliary variables and The problem can be rewritten as:

[0078]

[0079] stC1,C2,C3,C4.

[0080] in:

[0081]

[0082] At this time, the optimal solution of all variables in the problem can be obtained through iterative optimization. In the precoding solution proposed by the present invention, the optimization of each variable is the optimal solution obtained when other variables are fixed. The specific closed-form expression is as follows.

[0083] (1) Optimal auxiliary variables: For all k∈{1,…,K}, let and The optimal solution is 0:

[0084]

[0085]

[0086] in

[0087] (2) Optimal base station beamforming: Definition:

[0088]

[0089]

[0090] are the transmit powers of the base station and active RIS respectively. For the optimal base station beamforming, the problem can be written as:

[0091]

[0092] stC1:

[0093] C2:

[0094] in:

[0095]

[0096]

[0097]

[0098] This is a standard QCQP (quadratic constraint quadratic programming) problem, so it can be solved by existing methods such as ADMM (alternating direction method of multipliers).

[0099] (3) Optimal Active RIS Beamforming: Definition and β j =Gw j ,but can be rewritten as:

[0100]

[0101] Therefore, the active RIS beamforming problem can be written as:

[0102]

[0103] stC2:

[0104] C3,C4,

[0105] in:

[0106]

[0107]

[0108]

[0109] Again, this is a standard QCQP problem and can therefore be solved by existing methods.

[0110] Finally, considering the constraints C3 and C4, the optimal phase shift control Θ opt and the optimal magnification factor a opt They are:

[0111] Θ opt =diag(exp(jarg(ψ opt ))),

[0112] a opt =Γ -1 diag(exp(-jarg(ψ opt )))ψ opt ,

[0113] where Γ -1 represents the pseudo-inverse of the matrix Γ.

[0114] Through the above precoding method, the sub-connected active RIS structure provided by the present invention can effectively solve the high power consumption problem caused by the introduction of a large number of active amplifier circuits in active RIS. Compared with the traditional full-connected structure, the sub-connected structure can achieve a 22% improvement in energy efficiency. Figure 4 As shown, it is verified that the sub-connection structure provided by the present invention can be used as a high energy efficiency implementation method of active RIS.

[0115] The precoding device of the low-power intelligent metasurface hardware structure provided by the present invention is described below. The precoding device of the low-power intelligent metasurface hardware structure described below and the precoding method of the low-power intelligent metasurface hardware structure described above can be referenced to each other.

[0116] Figure 5 is a structural schematic diagram of a low-power intelligent metasurface hardware structure precoding device provided by the present invention, such as Figure 5As shown, the precoding device of the low-power intelligent metasurface hardware structure includes: an allocation module 501 and a processing module 502. The allocation module 501 is used to implement beamforming precoding based on pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplifier circuit; the processing module 502 is used to determine the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency with the maximum power of the base station and the RIS as the constraint condition, as the corresponding precoding scheme; wherein the system is a system composed of a user terminal, a RIS and a base station.

[0117] The device embodiments provided in the embodiments of the present invention are for implementing the above-mentioned method embodiments. For specific processes and detailed contents, please refer to the above-mentioned method embodiments, which will not be repeated here.

[0118] Figure 6 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 6 As shown, the electronic device may include: a processor (processor) 601, a communication interface (Communications Interface) 602, a memory (memory) 603 and a communication bus 604, wherein the processor 601, the communication interface 602, and the memory 603 communicate with each other through the communication bus 604. The processor 601 can call the logic instructions in the memory 603 to execute the low-power intelligent metasurface hardware structure, and the method includes: based on pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplifier circuit to achieve beamforming precoding; taking the maximum power of the base station and the RIS as the constraint condition, determining the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency as the corresponding precoding scheme; wherein the system is a system composed of a user terminal, a RIS and a base station.

[0119] In addition, the logic instructions in the above-mentioned memory 603 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0120] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the low-power intelligent metasurface hardware structure provided by the above methods, and the method includes: based on pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplifier circuit to achieve beamforming precoding; taking the maximum power of the base station and the RIS as a constraint condition, determining the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency as the corresponding precoding scheme; wherein the system is a system composed of user terminals, RIS and base stations.

[0121] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the processor executes the low-power intelligent metasurface hardware structure provided by the above-mentioned embodiments, and the method includes: based on pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplifier circuit to achieve beamforming precoding; taking the maximum power of the base station and the RIS as the constraint condition, determining the adjustment results of the phases of all phase shift circuits and the coefficients of the amplifier circuits that maximize the system energy efficiency as the corresponding precoding scheme; wherein the system is a system composed of a user terminal, a RIS and a base station.

[0122] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0123] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A precoding method based on a low-power intelligent metasurface hardware structure, characterized in that: The low-power intelligent metasurface hardware structure comprises: A plurality of sub-arrays, an amplification circuit corresponding to each sub-array, and a phase shift circuit corresponding to each smart metasurface RIS unit; Each subarray includes a plurality of RIS units, different RIS units of each subarray share an amplification circuit, each RIS unit uses a different phase shift circuit, each subarray uses the same signal amplification factor to control the signal amplitude, and each RIS unit independently controls the signal phase; The precoding method comprises: Pre-coding of beamforming is achieved based on pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit; Taking the maximum power of the base station and the RIS as the constraint condition, determining the adjustment results of the phases of all phase shift circuits and the coefficients of the amplification circuits that maximize the system energy efficiency as the corresponding precoding scheme; The system is a system composed of a user terminal, a RIS and a base station, and the system energy efficiency is determined according to the ratio of the system spectrum efficiency to the system total power consumption; The step of determining the adjustment results of the phases of all phase shift circuits and coefficients of the amplification circuits that maximize the system energy efficiency as the corresponding precoding scheme includes: S1. Use the fractional optimization Dinkelbach algorithm to transform the system energy efficiency optimization problem into a rational planning problem; S2. Use the Lagrange dual method to introduce auxiliary variables and transform the rational programming problem into a convex optimization problem; S3. Keep other variables unchanged and optimize auxiliary variables, base station beamforming, active RIS amplification control and phase shift control variables in order; S4. Repeat S3 until the objective function converges; S5. Repeat S2-S4 until the objective function converges to 0. At this time, the precoding scheme obtained is an active RIS precoding scheme that maximizes the system energy efficiency. Before determining the adjustment results of all phase shift circuits and amplification circuits that maximize the system energy efficiency, the method further includes determining the total power consumption of the system according to the following formula: Where ξ and ζ represent the inverse of the energy conversion coefficients of the base station and active RIS, W U and W BS represents the static power consumption of user terminals and base stations, W PS and W PA represents the static power consumption of the phase shift circuit and the amplifier circuit; K is the number of users served by the base station, k represents the corresponding single user, represents the base station beamforming vector, M is the number of base station antennas; Ψ = diag (ΘΓa) represents the beamforming matrix of active RIS; represents the diagonal phase shift matrix, represents the magnification factor vector; Indicates the connection relationship between the amplifier circuit and the phase shift circuit; represents the channel between the base station and the active RIS; N is the total number of RIS units, and L represents the number of amplification circuits; Parameters of dynamic noise introduced by active RIS.

2. The precoding method of the low-power intelligent metasurface hardware structure according to claim 1, characterized in that: Before determining the adjustment results of the phases of all phase shift circuits and coefficients of the amplification circuits that maximize the system energy efficiency, the method further includes: The system spectrum efficiency is determined based on the signal-to-noise ratio of the demodulated signals at all user terminals.

3. The precoding method of the low-power intelligent metasurface hardware structure according to claim 2 is characterized in that: Before determining the system spectrum efficiency according to the signal-to-noise ratio of the demodulated signals at all user terminals, the method further includes determining the signal-to-noise ratio of the demodulated signal at each user terminal according to the following formula: Where K is the number of users served by the base station, and j and k represent the corresponding single users; represents the equivalent channel from the base station to user k; Ψ = diag (ΘΓa) represents the beamforming matrix of active RIS; represents the diagonal phase shift matrix, represents the amplification factor vector, N is the total number of RIS units, and L represents the number of amplification circuits; Indicates the connection relationship between the amplifier circuit and the phase shift circuit; and denote the channels between the base station and user k, the base station and the active RIS, and the active RIS and user k respectively; represents the base station beamforming vector; 2 where σ is the parameter of the dynamic noise introduced by the active RIS and the additive white Gaussian noise at the user.

4. A precoding device based on a low-power intelligent metasurface hardware structure, applying the precoding method based on a low-power intelligent metasurface hardware structure according to any one of claims 1 to 3, characterized in that: include: An allocation module, configured to implement beamforming precoding based on pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit; A processing module, used to determine the adjustment results of the phases of all phase shift circuits and the coefficients of the amplification circuits that maximize the system energy efficiency with the maximum power of the base station and the RIS as a constraint condition, as a corresponding precoding scheme; The system is composed of a user terminal, a RIS and a base station.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the precoding method of the low-power intelligent metasurface hardware structure as described in any one of claims 1 to 3 are implemented.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the precoding method of the low-power intelligent metasurface hardware structure as described in any one of claims 1 to 3 are implemented.

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