CN114040478A - Low-power-consumption intelligent super-surface hardware structure, precoding method and device - Google Patents
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Abstract
The invention provides a low-power-consumption intelligent super-surface hardware structure, a pre-coding method and a device, wherein the hardware structure comprises the following components: the circuit comprises a plurality of sub-arrays, amplifying circuits corresponding to the sub-arrays one by one, and phase shifting circuits corresponding to RIS units; each subarray comprises a plurality of RIS units, different RIS units of each subarray share one amplifying circuit, and each RIS unit uses different phase shift circuits respectively. According to the hardware structure, the sub-arrays formed by the plurality of RIS units share one amplifying circuit, so that the problem of high power consumption caused by the introduction of a large number of active amplifying circuits in an active RIS is effectively solved, and compared with a traditional full-connection structure, the intelligent super-surface hardware structure can obtain remarkable energy efficiency improvement. The precoding method aims at maximizing the system energy efficiency, optimizes the amplification control and phase shift control of the sub-connection active RIS, and can effectively save the system energy consumed by a large number of amplification circuits.
Description
Technical Field
The invention relates to the field of wireless communication, in particular to a low-power-consumption intelligent super-surface hardware structure, a precoding method and a precoding device.
Background
Intelligent super surfaces (RIS) are considered as one of the key technologies to be selected for future 6G communication. As shown in part a of fig. 1, the RIS is a large-scale array consisting of a large number of passive elements that can regulate the phase of a signal, and can intelligently regulate an incident signal so that it can be reflected in any given direction with high gain. Because the cost and the power consumption of the RIS are both very low, the RIS has application value in scenes of overcoming interruption, improving capacity, saving transmitting power and the like.
As shown in fig. 2, the introduction of RIS introduces a "multiplicative path loss effect," i.e., the path loss of the transmitter-RIS-receiver link is the product (rather than the sum) of the path losses of the two channels, which results in a much smaller gain than the direct link gain. This "multiplicative road loss effect" in turn makes it difficult for the RIS to take significant advantage in scenarios with strong direct links, creating fatal problems. To overcome the "multiplicative road loss effect", a new technology named active RIS is proposed that can increase capacity in scenarios where the direct link is either strong or weak. Specifically, as shown in part b of fig. 1, unlike a conventional passive RIS, which only performs phase control on signals, the active RIS further integrates an amplification circuit outside the phase shift circuit of each unit, so that the RIS can amplify reflected signals, and further, multiplicative path loss is converted into additive path loss.
However, the existing active RIS structure is a fully connected structure in which an independent phase shift circuit and an amplification circuit are integrated per unit, which causes the power consumption of the active RIS to be greatly increased as the number of units increases. Taking the example that each amplifying circuit consumes 10mW of static power, a 1000-unit active RIS consumes 10W only in the static power consumption of the amplifying circuit, which is already comparable to the transmission power of a typical base station and is unacceptable in practical deployment. Therefore, the active RIS requires a new structure different from the fully connected structure to save power consumption.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an intelligent super-surface hardware structure with low power consumption, a pre-coding method and a device.
The invention provides a low-power consumption intelligent super-surface hardware structure, which comprises: the intelligent super-surface RIS unit comprises a plurality of sub-arrays, amplifying circuits corresponding to the sub-arrays one by one, and phase shifting circuits corresponding to the intelligent super-surface RIS units; each subarray comprises a plurality of RIS units, different RIS units of each subarray share one amplifying circuit, and each RIS unit uses different phase shift circuits respectively.
The invention also provides a precoding method based on the low-power-consumption intelligent super-surface hardware structure, which comprises the following steps: pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit to realize beam-forming pre-coding; determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as corresponding precoding schemes by taking the maximum powers of the base station and the RIS as constraint conditions; the system is composed of a user terminal, a RIS and a base station.
According to the precoding method of the low-power-consumption intelligent super-surface hardware structure, the system energy efficiency is determined according to the ratio of the system spectrum efficiency to the total power consumption of the system.
According to the precoding method of the intelligent super-surface hardware structure with low power consumption, before determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, the method further comprises the following steps: and determining the spectrum efficiency of the system according to the signal-to-noise ratios of the demodulated signals at all the user terminals.
According to the precoding method of the low-power-consumption intelligent super-surface hardware structure, before determining the system spectrum efficiency according to the signal-to-noise ratios of the demodulated signals at all the user terminals, the method further comprises the following steps of determining the signal-to-noise ratio of the demodulated signal at each user terminal according to the following formula:
wherein K serves the base stationThe number of users, j, k, represents the corresponding individual user;
represents the equivalent channel from the base station to user k; Ψ ═ diag (Θ Γ a) represents the beamforming matrix of the active RIS;
a diagonal phase shift matrix is represented and,
representing the vector of the amplification factor, wherein N is the total number of RIS units, and L represents the number of amplification circuits;
showing the connection relationship of the amplifying circuit and the phase shifting circuit;
and
respectively representing channels between a base station and a user k, between the base station and an active RIS, and between the active RIS and the user k, wherein M is the number of base station antennas;
representing a base station beamforming vector;
σ2parameters for dynamic noise introduced by an active RIS and additive white gaussian noise at the user, respectively.
According to the precoding method of the low-power-consumption intelligent super-surface hardware structure, before determining the adjustment results of all the phase shift circuits and the amplifying circuits which maximize the energy efficiency of the system, the method further comprises the following steps of determining the total power consumption of the system according to the following formula:
where ξ and ζ denote the reciprocal of the energy conversion coefficient of the base station and the active RIS, WUAnd WBSRepresenting the static power consumption, W, of the user terminal and the base stationPSAnd WPARepresenting the static power consumption of the phase shift circuit and the amplifying circuit; k is the number of users served by the base station, K represents the corresponding individual user,
representing a base station beamforming vector; Ψ ═ diag (Θ Γ a) represents the beamforming matrix of the active RIS;
a diagonal phase shift matrix is represented and,
representing a vector of amplification factors;
showing the connection relationship of the amplifying circuit and the phase shifting circuit;
represents a channel between the base station and the active RIS; n is the total number of RIS units, L represents the number of amplifying circuits;
parameters of dynamic noise introduced for active RIS.
According to the precoding method of the low-power-consumption intelligent super-surface hardware structure, the determining of the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as the corresponding precoding scheme includes:
s1, converting a system energy efficiency optimization problem into a rational planning problem by using a fractional optimization Butkelbach algorithm;
s2, introducing auxiliary variables by using a Lagrange dual method, and converting a rational planning problem into a convex optimization problem;
s3, keeping other variables unchanged, and sequentially optimizing auxiliary variables, base station beam forming, active RIS amplification control and phase shift control variables in sequence;
s4, repeating S3 until the target function converges;
s5, repeating S2-S4 until the objective function converges to 0, wherein the obtained precoding scheme is an active RIS precoding scheme which maximizes the energy efficiency of the system.
The invention also provides a low-power consumption intelligent pre-coding device with a super-surface hardware structure, which comprises: the distribution module is used for pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplification circuit so as to realize beam-forming precoding; the processing module is used for determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, by taking the maximum powers of the base station and the RIS as constraint conditions as corresponding precoding schemes; the system is composed of a user terminal, a RIS and a base station.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the pre-coding method of the low-power intelligent super-surface hardware structure.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method for pre-encoding a low power intelligent super surface hardware structure as described in any of the above.
According to the low-power-consumption intelligent super-surface hardware structure, the pre-coding method and the device, the sub-arrays formed by the plurality of RIS units share one amplifying circuit, so that the problem of high power consumption caused by introducing a large number of active amplifying circuits into the active RIS is effectively solved. Compared with the traditional full-connection structure, the intelligent super-surface hardware structure can obtain remarkable energy efficiency improvement and can be used as an energy-efficient implementation mode of an active RIS.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic structural view of a passive RIS and a fully connected active RIS of the prior art;
FIG. 2 is a schematic diagram of a prior art RIS assisted MIMO system architecture;
FIG. 3 is a schematic diagram of the low power consumption intelligent super-surface hardware architecture provided by the present invention;
FIG. 4 is a schematic diagram of the energy efficiency performance of the low power intelligent super-surface hardware structure and its pre-coding method provided by the present invention;
FIG. 5 is a schematic structural diagram of a low-power consumption intelligent super-surface hardware structure pre-coding device provided by the invention;
fig. 6 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The low-power intelligent super-surface hardware structure, the pre-coding method and the device of the invention are described below with reference to fig. 1 to 6. Fig. 3 is a schematic diagram of a low-power consumption intelligent super-surface hardware structure provided by the present invention, and as shown in fig. 3, the present invention provides a low-power consumption intelligent super-surface hardware structure, which includes: the intelligent super-surface RIS unit comprises a plurality of sub-arrays, amplifying circuits corresponding to the sub-arrays one by one, and phase shifting circuits corresponding to the intelligent super-surface RIS units; each subarray comprises a plurality of RIS units, different RIS units of each subarray share one amplifying circuit, and each RIS unit uses different phase shift circuits respectively.
The existing fully-connected active RIS structure is shown in part b of fig. 2, and based on the original passive RIS structure shown in part a of fig. 2, each unit includes a separate amplifying circuit outside a separate phase shifting circuit. However, when the number of RIS units is large, the fully connected structure faces a high power consumption problem because a large number of active amplification circuits are used.
In order to solve the problem of high power consumption of the existing full-connection structure of the active RIS, in the sub-connection structure shown in fig. 3, a plurality of RIS units are divided into a sub-array, each unit in the sub-array adopts an independent phase shift circuit, but shares one amplifying circuit, that is, each unit independently performs phase control on signals, but the whole sub-array adopts the same signal amplifying coefficient for amplitude control of the signals.
For the sake of contrast, consider that each subarray contains T RIS units, i.e. one amplification circuit serves T RIS units simultaneously. In this case, the full-link structure becomes a special case of the sub-link structure when T is 1. Under the condition of the same RIS unit number, the number of amplifying circuits of the sub-connection active RIS is changed into 1/T under the full connection structure, so that the energy consumption of the active RIS is greatly reduced. Meanwhile, the degree of freedom of the sub-connection active RIS in the beam forming process is reduced because the T RIS units share the same amplification factor. However, the invention shows that the reduction influence of the beam forming freedom of the sub-connection active RIS structure is small, and the system can still obtain great improvement of energy efficiency due to the use of the sub-connection structure.
According to the low-power-consumption intelligent super-surface hardware structure provided by the invention, the sub-arrays formed by a plurality of RIS units share one amplifying circuit, so that the problem of high power consumption caused by introducing a large number of active amplifying circuits into an active RIS is effectively solved. Compared with the traditional full-connection structure, the intelligent super-surface hardware structure can obtain remarkable energy efficiency improvement and can be used as an energy-efficient implementation mode of an active RIS.
Based on the low-power-consumption intelligent super-surface hardware structure provided by the invention, the invention also provides a corresponding pre-coding method, which comprises the following steps: pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit to realize beam-forming pre-coding; determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as corresponding precoding schemes by taking the maximum powers of the base station and the RIS as constraint conditions; the system is composed of a user terminal, a RIS and a base station.
Specifically, the system energy efficiency is maximized by adjusting the amplification factor of each sub-array amplification circuit and the phase of each phase shift circuit with the goal of maximizing the system energy efficiency. Of course, the power of the base station and the active RIS does not exceed the maximum power in this process.
The precoding method of the low-power-consumption intelligent super-surface hardware structure can effectively save system energy consumed by a large number of amplifying circuits and effectively improve system energy efficiency.
In the above method embodiment, the system energy efficiency is determined according to a ratio of the system spectrum efficiency to the total system power consumption.
Specifically, the system energy efficiency may be expressed as:
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 invention is to maximize the system energy efficiency.
In the above method, before determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits that maximize the energy efficiency of the system, the method further includes: and determining the spectrum efficiency of the system according to the signal-to-noise ratios of the demodulated signals at all the user terminals.
Specifically, the system spectral efficiency may be determined as follows:
wherein K is the number of users served by the base station; SINRkThe SINR of the demodulated signal at user k.
In the above method, before determining the spectrum efficiency of the system according to the snr of the demodulated signals at all the ues, the method further includes determining the snr of the demodulated signal at each ue according to the following formula:
wherein, K is the number of users served by the base station, and j and K represent corresponding single users;
represents the equivalent channel from the base station to user k; Ψ diag (ψ) diag (Θ Γ a) represents a beamforming matrix of the active RIS; n is the total number of RIS units, L represents the number of amplifying circuits;
and
respectively representing channels between a base station and a user k, between the base station and an active RIS, and between the active RIS and the user k, wherein M is the number of base station antennas;
representing base station beamforming vectors.
In particular, consider an N-element active RIS assisted MIMO system, where one M-antenna base station serves K single-antenna users simultaneously. For both full-connection and sub-connection structures, the number of required amplification circuits is represented by L ═ N/T, and then the beamforming matrix of the active RIS can be represented as:
Ψ＝diag(ψ)＝diag(ΘΓa),
wherein,
represents the same diagonal phase shift matrix as a conventional passive RIS,
representing a vector of amplification factors.
Is defined as an exemplary matrix, which is used to represent the connection relationship between the amplifying circuit and the phase shifting circuit. Without loss of generality, order
Wherein
The expression of the kronecker product,
representing a full 1 vector.
The signal y received by user kkCan be expressed as:
wherein s iskRepresenting the normalized symbol transmitted to user k,
representing the corresponding base station beamforming vector,
and
representing the dynamic noise introduced by the active RIS and the additive white gaussian noise at user k, respectively.
In the above method embodiment, before determining the adjustment results of all the phase shift circuits and the amplifying circuits that maximize the energy efficiency of the system, the method further includes determining the total power consumption of the system according to the following formula:
where ξ and ζ denote the reciprocal of the energy conversion coefficient of the base station and the active RIS, WUAnd WBSRepresenting the static power consumption, W, of the user terminal and the base stationPSAnd WPARepresenting the static power consumption of the phase shift circuit and the amplification circuit.
Regarding the power consumption of the system, which is composed of the transmission power of the base station and the active RIS, and the static power of each component of the system, the total power consumption of the system can be expressed as the above formula.
Integrating the above signal models
And Θ ═ diag (θ), the system energy efficiency maximization problem can be expressed as:
s.t.C1:
C2:
C3:
C4:
wherein constraint C1And C2Respectively limit the maximum power of the base station and the active RIS, and restrict C3And C4Respectively limit the phase shift controlThe feasible set of controls Θ and magnification a.
The optimization problem is solved, and then the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, namely the corresponding precoding schemes, can be obtained.
In one embodiment of the method, the determining the adjustment result of the phase of all the phase shift circuits and the coefficient of the amplifying circuit, which maximizes the energy efficiency of the system, as the corresponding precoding scheme includes: s1, converting a system energy efficiency optimization problem into a rational planning problem by using a fractional optimization Butkelbach algorithm; s2, introducing auxiliary variables by using a Lagrange dual method, and converting a rational planning problem into a convex optimization problem; s3, keeping other variables unchanged, and sequentially optimizing auxiliary variables, base station beam forming, active RIS amplification control and phase shift control variables in sequence; s4, repeating S3 until the target function converges; s5, repeating S2-S4 until the objective function converges to 0, wherein the obtained precoding scheme is an active RIS precoding scheme which maximizes the energy efficiency of the system. The concrete description is as follows:
to facilitate processing of the above-mentioned fractal objective function, the embodiment of the present invention first converts it into a rational form by using the t-kel bach algorithm in the fractal programming. Specifically, the optimum energy efficiency ηoptSatisfies the following conditions:
elucidation of the optimal energy efficiency ηoptThis can be obtained by iteratively solving the following problem:
s.t.C1,C2,C3,C4.
since this problem is still non-convex, the present invention introduces an auxiliary variable
And
the problem equivalence is rewritten as:
s.t.C1,C2,C3,C4.
wherein:
at this time, the optimal solution of all variables in the problem can be obtained by iterative optimization. In the precoding scheme provided by the invention, the optimization of each variable is an optimal solution obtained when other variables are fixed, and a specific closed expression is as follows.
(1) Optimal auxiliary variables: for all K e {1, …, K }, let
And
an optimal solution is obtained for 0:
wherein
(2) Optimal base station beamforming: defining:
the transmit power of the base station and the active RIS, respectively. For optimal base station beamforming, the problem can be written as:
s.t.C1:
C2:
wherein:
this is a standard QCQP (quadratic programming) problem, and thus can be solved by the existing admm (alternating direction method of multipliers) and the like.
(3) Optimal active RIS beamforming: definition of
And betaj＝GwjThen, then
Can be rewritten as:
the active RIS beamforming problem can thus be written as:
s.t.C2:
C3,C4,
wherein:
again, this is a standard QCQP problem and can therefore be solved by existing methods.
Finally considering constraint C3And C4Optimal phase shift control thetaoptAnd an optimum amplification factor aoptRespectively as follows:
Θopt＝diag(exp(jarg(ψopt))),
aopt＝Γ-1diag(exp(-jarg(ψopt)))ψopt,
wherein gamma is-1Representing the pseudo-inverse of the matrix Γ.
Through the precoding method, the sub-connection active RIS structure provided by the invention can effectively solve the problem of high power consumption of the active RIS due to the introduction of a large number of active amplifying circuits, and compared with the traditional full-connection structure, the sub-connection structure can obtain 22% energy efficiency improvement, and as shown in FIG. 4, the sub-connection structure provided by the invention can be used as a high-energy-efficiency implementation mode of the active RIS.
The pre-coding device of the low-power-consumption intelligent super-surface hardware structure provided by the invention is described below, and the pre-coding device of the low-power-consumption intelligent super-surface hardware structure described below and the pre-coding method of the low-power-consumption intelligent super-surface hardware structure described above can be referred to correspondingly.
Fig. 5 is a schematic structural diagram of a low-power consumption intelligent super-surface hardware structure precoding device provided by the present invention, and as shown in fig. 5, the low-power consumption intelligent super-surface hardware structure precoding device includes: a distribution module 501 and a processing module 502. The allocating module 501 is configured to pre-adjust the phase of each phase shifting circuit and the amplification factor of each amplifying circuit, so as to implement beamforming pre-coding; the processing module 502 is configured to determine, with the maximum powers of the base station and the RIS as constraint conditions, adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the system energy efficiency, as corresponding precoding schemes; the system is composed of a user terminal, a RIS and a base station.
The device embodiment provided in the embodiments of the present invention is for implementing the above method embodiments, and for details of the process and the details, reference is made to the above method embodiments, which are not described herein again.
Fig. 6 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 6, 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 complete communication with each other through the communication bus 604. The processor 601 may invoke logic instructions in the memory 603 to execute a low power intelligent super surface hardware structure, the method comprising: pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit to realize beam-forming pre-coding; determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as corresponding precoding schemes by taking the maximum powers of the base station and the RIS as constraint conditions; the system is composed of a user terminal, a RIS and a base station.
In addition, the logic instructions in the memory 603 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the low power intelligent meta-surface hardware architecture provided by the above methods, the method comprising: pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit to realize beam-forming pre-coding; determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as corresponding precoding schemes by taking the maximum powers of the base station and the RIS as constraint conditions; the system is composed of a user terminal, a RIS and a base station.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor is implemented to perform the low power intelligent super surface hardware structure provided by the above embodiments, the method comprising: pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit to realize beam-forming pre-coding; determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as corresponding precoding schemes by taking the maximum powers of the base station and the RIS as constraint conditions; the system is composed of a user terminal, a RIS and a base station.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A low-power intelligent super-surface hardware structure, comprising:
the intelligent super-surface RIS unit comprises a plurality of sub-arrays, amplifying circuits corresponding to the sub-arrays one by one, and phase shifting circuits corresponding to the intelligent super-surface RIS units;
each subarray comprises a plurality of RIS units, different RIS units of each subarray share one amplifying circuit, and each RIS unit uses different phase shift circuits respectively.
2. The precoding method of the intelligent low-power-consumption super-surface hardware structure, according to claim 1, comprising:
pre-adjusting the phase of each phase shift circuit and the amplification factor of each amplification circuit to realize beam-forming pre-coding;
determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, as corresponding precoding schemes by taking the maximum powers of the base station and the RIS as constraint conditions;
the system is composed of a user terminal, a RIS and a base station.
3. The method for pre-coding the low-power-consumption intelligent super-surface hardware structure according to claim 2, wherein the system energy efficiency is determined according to a ratio of system spectral efficiency to total system power consumption.
4. The method for pre-coding a low-power intelligent super-surface hardware structure according to claim 3, wherein before determining the adjustment results of the phase of all phase shift circuits and the coefficient of the amplifying circuit for maximizing the energy efficiency of the system, the method further comprises:
and determining the spectrum efficiency of the system according to the signal-to-noise ratios of the demodulated signals at all the user terminals.
5. The method of claim 4, wherein before determining the system spectral efficiency based on the SNR of the demodulated signals at all the UEs, the method further comprises determining the SNR of the demodulated signal at each UE according to the following formula:
wherein, K is the number of users served by the base station, and j and K represent corresponding single users;
represents the equivalent channel from the base station to user k; Ψ ═ diag (Θ Fa) represents the beamforming matrix of the active RIS;
a diagonal phase shift matrix is represented and,
representing the vector of the amplification factor, wherein N is the total number of RIS units, and L represents the number of amplification circuits;
showing the connection relationship of the amplifying circuit and the phase shifting circuit;
and
respectively representing base station and user k, base station and active RIS, anda channel between the active RIS and the user k, M being the number of base station antennas; w is aj、
Representing a base station beamforming vector;
σ2parameters for dynamic noise introduced by an active RIS and additive white gaussian noise at the user, respectively.
6. The method for pre-coding a low-power intelligent super-surface hardware structure according to claim 3, wherein before determining the adjustment results of all the phase shift circuits and the amplifying circuits that maximize the energy efficiency of the system, the method further comprises determining the total power consumption of the system according to the following formula:
where ξ and ζ denote the reciprocal of the energy conversion coefficient of the base station and the active RIS, WUAnd WBSRepresenting the static power consumption, W, of the user terminal and the base stationPSAnd WPARepresenting the static power consumption of the phase shift circuit and the amplifying circuit; k is the number of users served by the base station, K represents the corresponding individual user,
representing a base station beamforming vector; Ψ ═ diag (Θ Fa) represents the beamforming matrix of the active RIS;
a diagonal phase shift matrix is represented and,
representing a vector of amplification factors;
showing the connection relationship of the amplifying circuit and the phase shifting circuit;
represents a channel between the base station and the active RIS; n is the total number of RIS units, L represents the number of amplifying circuits;
parameters of dynamic noise introduced for active RIS.
7. The precoding method of the intelligent low-power-consumption super-surface hardware structure, according to claim 3, wherein the determining the adjustment results of the phase of all the phase shift circuits and the coefficient of the amplifying circuit for maximizing the energy efficiency of the system as the corresponding precoding scheme comprises:
s1, converting a system energy efficiency optimization problem into a rational planning problem by using a fractional optimization Butkelbach algorithm;
s2, introducing auxiliary variables by using a Lagrange dual method, and converting a rational planning problem into a convex optimization problem;
s3, keeping other variables unchanged, and sequentially optimizing auxiliary variables, base station beam forming, active RIS amplification control and phase shift control variables in sequence;
s4, repeating S3 until the target function converges;
s5, repeating S2-S4 until the objective function converges to 0, wherein the obtained precoding scheme is an active RIS precoding scheme which maximizes the energy efficiency of the system.
8. A pre-coding device based on the low-power intelligent super-surface hardware structure of claim 1, comprising:
the distribution module is used for pre-adjusting the phase of each phase shift circuit and the amplification coefficient of each amplification circuit so as to realize beam-forming precoding;
the processing module is used for determining the adjustment results of the phases of all the phase shift circuits and the coefficients of the amplifying circuits, which maximize the energy efficiency of the system, by taking the maximum powers of the base station and the RIS as constraint conditions as corresponding precoding schemes;
the system is composed of a user terminal, a RIS and a base station.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for pre-encoding a low power intelligent super surface hardware structure according to any of claims 2 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the method for pre-encoding a low power intelligent super surface hardware structure according to any of claims 2 to 7.
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