Primary and secondary spectrum sharing method for wireless energy-carrying communication assisted by intelligent reflective surface

Abstract

The present invention proposes a primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy-carrying communication cognition, which relates to the technical field of wireless energy-carrying communication. First, a system is composed of a secondary user transmitter, a secondary user receiver, a primary user transmitter, a primary user receiver and an IRS, and then the duration of the information transmission stage is divided. The secondary user transmitter transmits information and energy to the secondary user receiver and the primary user transmitter respectively in the first duration interval, and the primary user transmitter uses the collected energy to transmit information to the primary user receiver in the second duration interval. Then, the maximum sum of the throughputs from the secondary user transmitter to all secondary user receivers k is used as the objective function, various constraints are set, and the objective function is optimized and solved to obtain the maximum total throughput, thereby achieving sustainable energy supply and effectively improving the communication performance of primary and secondary users.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless power-carrying communication, and in particular to a primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless power-carrying communication cognition. Background Art

[0002] With the development of wireless communication technology, the amount of wireless service data has exploded, and various wireless devices require certain spectrum resources and continuous energy supply to transmit data. Cognitive radio technology is one of the effective means to improve spectrum utilization, allowing unauthorized users to access the frequency band without interfering with authorized users, thereby improving spectrum utilization. Wireless energy-carrying communication technology realizes the simultaneous transmission of information and energy, and provides a new method of energy collection for energy-constrained nodes that require continuous energy supply. In a cognitive radio system, its spectrum can be shared by two different types of users, namely primary users and secondary users.

[0003] At present, most researchers on wireless power communication technology consider combining cognitive wireless power technology with cooperative relay technology, and consider using the secondary user transmitter as a relay to transmit both the primary user data and its own data. Although the transmission performance of the primary user is improved, the communication performance of the secondary user is limited, and for the secondary user transmitter as an active relay, its power consumption is increased. Intelligent reflecting surface (IRS) is a revolutionary new technology that can improve the spectrum and energy efficiency of wireless communication. It uses a large number of low-cost passive transmitting elements, dynamically adjusts the phase shift of the reflected signal through software, and reconfigures the wireless propagation channel to enhance the required signal strength at the primary and secondary users, thereby further optimizing the user's communication performance. Combining IRS with wireless power communication technology can further improve the communication performance of primary and secondary users.

[0004] The prior art discloses a method for combining IRS with wireless energy-carrying communication. First, the method establishes a communication model in which an IRS-assisted single cognitive radio network coexists with a primary user network. The transmission power of the secondary user transmitter is minimized by jointly optimizing the beamforming vector of the secondary user transmitter and the phase shift matrix of the IRS. However, it does not take into account that when the primary user transmitter is idle, the secondary user transmitter sends energy to the primary user transmitter while sending information, and then uses the collected energy to transmit its own data when the primary user is working. That is, the energy transmitted by the secondary user transmitter cannot be supplied sustainably, affecting the communication performance of the primary and secondary users. Summary of the invention

[0005] In order to solve the problem that in the current method of combining IRS with wireless power carrying communication, the energy transmitted by the secondary user transmitter cannot be supplied sustainably, affecting the communication performance of the primary and secondary users, the present invention proposes a primary and secondary spectrum sharing method with intelligent reflective surface assisted wireless power carrying communication cognition, so as to achieve sustainable energy supply and effectively improve the communication performance of the primary and secondary users.

[0006] In order to achieve the above technical effects, the technical solution of the present invention is as follows:

[0007] A primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy-carrying communication cognition includes the following steps:

[0008] S1. Establish a multi-user wireless energy-carrying communication cognitive system consisting of a secondary user transmitter, K secondary user receivers, a primary user transmitter, a primary user receiver and an IRS;

[0009] S2. Assume that the information transmission phase in the multi-user cognitive wireless energy-carrying communication system includes a first duration gap and a second duration gap, in which the secondary user transmitter transmits information to all secondary user receivers and the primary user transmitter respectively, and the primary user transmitter collects energy from the information; in the second duration gap, the primary user transmitter transmits information to the primary user receiver based on the collected energy;

[0010] S3. For any secondary user receiver k among the secondary user receivers, based on the transmission information transmitted by the secondary user transmitter and the reflection phase shift matrix of the IRS in the first duration interval and the second duration interval, obtain the signal received by the secondary user receiver k, and determine the received signal-to-interference-noise ratio at the secondary user receiver k and the throughput from the primary user transmitter to the primary user receiver under the unit bandwidth;

[0011] S4. Based on the received signal-to-interference-noise ratio at the secondary user receiver k, calculate the throughput from the unit broadband secondary user transmitter to the secondary user receiver k;

[0012] S5. Based on the unit broadband sub-user transmitter to the sub-user receiver k throughput, calculate the sub-user transmitter to all sub-user receiver k throughput and;

[0013] S6. Taking the maximum sum of the throughputs from the secondary user transmitter to all secondary user receivers k as the objective function, and taking the transmission power of the secondary user transmitter, the signal-to-interference-noise ratio of the secondary user receiver, the throughput from the primary user transmitter to the primary user receiver, the first duration gap, the IRS reflection phase shift matrix of the first duration gap, and the IRS reflection phase shift matrix of the second duration gap as constraints, the objective function is optimized and solved to obtain the maximum total throughput from the secondary user transmitter to all secondary user receivers k.

[0014] In this technical solution, a multi-user wireless energy-carrying communication cognitive system consisting of a secondary user transmitter, a secondary user receiver, a primary user transmitter, a primary user receiver and an IRS is first established, and the IRS is combined with the wireless energy-carrying communication to improve the channel environment of the primary and secondary users, ensure the transmission of information between the primary and secondary users, and improve the total throughput from the secondary user transmitter to the secondary user receiver. Then, the duration of the information transmission phase is divided into a first duration interval and a second duration interval. The secondary user transmitter transmits information and energy to the secondary user receiver and the primary user transmitter respectively in the first duration interval, and the primary user transmitter uses the collected energy in the second duration interval. The objective function is to maximize the sum of the throughputs from the secondary user transmitter to all secondary user receivers k and maintain a sustainable supply of energy. The objective function is to use the transmission power of the secondary user transmitter, the signal to interference and noise ratio of the secondary user receiver, the throughput from the primary user transmitter to the primary user receiver, the first duration gap, the IRS reflection phase shift matrix of the first duration gap, and the IRS reflection phase shift matrix of the second duration gap as constraints. Finally, the objective function is optimized and solved to obtain the maximum total throughput from the secondary user transmitter to all secondary user receivers k, thereby achieving sustainable supply of energy and effectively improving the communication performance of the primary and secondary users.

[0015] Preferably, the secondary user transmitter is equipped with M antennas and a stable power supply, and the K secondary receivers, the primary user transmitter and the primary user receiver are all equipped with a single antenna. Assume that the IRS includes N passive reflection units, and the amplitude of each passive reflection unit is 1. The channel between the secondary user transmitter and the IRS is The channel between the secondary user transmitter and the secondary user receiver k is k={1,...,K}, the channel from the secondary user transmitter to the primary user transmitter is The channel from IRS to secondary user receiver k is The channel from IRS to the primary user transmitter is The channel from IRS to the primary user receiver is Channel from primary user transmitter to primary user receiver in, represents a set of complex-valued matrices of dimension x×y, The exponent of represents the dimension of the complex-valued matrix, and the channel state information of each channel is known.

[0016] Preferably, in step S3, assuming that the duration of the information transmission phase in the multi-user cognitive wireless energy-carrying communication system is T, the first duration gap is τ, and the second duration gap is T-τ, the reflection phase shift matrix of the IRS in the first duration gap τ is expressed as:

[0017]

[0018] Among them, φ1=[q 1,1 ,...,q N,1 ] H , n={1,...,N},β n,1 ∈[0,1] and θ n,1 ∈[0,2π) are the amplitude and phase shift of the nth reflection unit of IRS in the first duration interval τ, respectively;

[0019] The reflection phase shift matrix of IRS in the second duration interval T-τ is expressed as:

[0020]

[0021] Where φ2=[q 1,2 ,...,q N,2 ] H , n={1,...,N},β n,2 ∈[0,1] and θ n,2 ∈[0,2π) represent the amplitude and phase shift of the nth reflection unit of IRS in the second duration interval T-τ, respectively.

[0022] Preferably, during the first duration interval τ, the signal transmitted by the secondary user transmitter is expressed as:

[0023]

[0024] Among them, s k ∈C is the information transmitted from the secondary user transmitter to the secondary user receiver k, v k is the corresponding beamforming vector, s k is unit power, satisfying E[|s k | 2 ]=1, E is the mathematical expectation operation;

[0025] The signal received by the secondary user receiver k is expressed as:

[0026]

[0027] Among them, n k is the antenna noise received at the secondary user receiver k, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of

[0028] The signal received by the primary user transmitter is expressed as:

[0029]

[0030] Among them, npt is the signal processing noise received at the primary user transmitter, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of

[0031] The energy collected by the primary user transmitter is expressed as:

[0032]

[0033] Among them, η (0≤η≤1) is the energy conversion efficiency of the primary user transmitter.

[0034] Preferably, when the second duration interval is T-τ, the transmission power of the primary user transmitter transmitting information is expressed as:

[0035]

[0036] The signal received by the primary user receiver is expressed as:

[0037]

[0038] Among them, s pr is the signal sent by the primary user transmitter, which represents unit power and satisfies E[|s pr | 2 ]=1,n pr is the additive Gaussian white noise at the primary user receiver, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of .

[0039] Preferably, in step S3, the received signal-to-interference-and-noise ratio SINR at the secondary user receiver k is k The calculation expression is:

[0040]

[0041] Assume that the primary user transmitter and the primary user receiver form the primary user system, the secondary user transmitter and K secondary user receivers form the secondary user system, the throughput from the primary user transmitter to the primary user receiver is the throughput of the primary user system, and under unit bandwidth, the throughput of the primary user system is R PR The calculation expression is:

[0042]

[0043] Preferably, in step S4, the throughput R from the unit broadband secondary user transmitter to the secondary user receiver k is s,k The calculation expression is:

[0044] R s,k =τlog2(1+SINR k ).

[0045] Preferably, in step S5, the calculation expression of the sum R of the throughput from the secondary user transmitter to all secondary user receivers k is:

[0046]

[0047] Preferably, in step S6, the calculation expression of the objective function is:

[0048]

[0049] The expression with the transmission power of the secondary user transmitter as the constraint is:

[0050]

[0051] The expression with the signal-to-interference-noise ratio of the secondary user receiver as the constraint is:

[0052]

[0053] The expression with the first duration gap as the constraint is:

[0054] 0≤τ≤T

[0055] The expression with the throughput from the primary user transmitter to the primary user receiver as the constraint is:

[0056]

[0057] The expression with the IRS reflection phase shift matrix of the first duration interval τ as the constraint condition is:

[0058]

[0059] The expression with the IRS reflection phase shift matrix of the second duration interval T-τ as the constraint condition is:

[0060]

[0061] Among them, {v k} is the beamforming vector of the secondary user transmitter, P ST is the maximum transmission power of the secondary user transmitter, γ k is the minimum signal-to-interference-noise ratio requirement of secondary user receiver k, β PR The minimum throughput threshold for the primary user system.

[0062] Preferably, in step S6, the objective function is a non-convex objective function, and the method for optimizing and solving the objective function is an alternating optimization method, and the object of alternating optimization is the beamforming vector {v k}, a first duration gap τ, an IRS reflection phase shift moment of the first duration gap τ, and an IRS reflection phase shift matrix of the second duration gap T-τ.

[0063] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0064] The present invention proposes a primary-secondary spectrum sharing method for intelligent reflective surface-assisted wireless power communication cognition. First, a multi-user wireless power communication cognition system consisting of a secondary user transmitter, a secondary user receiver, a primary user transmitter, a primary user receiver and an IRS is established, and the IRS is combined with the wireless power communication to improve the channel environment of the primary and secondary users, ensure the transmission of information between the primary and secondary users, and improve the total throughput from the secondary user transmitter to the secondary user receiver. Then, the duration of the information transmission phase is divided into a first duration interval and a second duration interval. The secondary user transmitter transmits information and energy to the secondary user receiver and the primary user transmitter respectively in the first duration interval, and the primary user transmitter transmits information and energy to the secondary user receiver and the primary user transmitter in the second duration interval. The duration gap uses the collected energy to transmit information to the primary user receiver to maintain a sustainable supply of energy. Furthermore, the maximum sum of the throughputs from the secondary user transmitter to all secondary user receivers k is taken as the objective function, and the transmission power of the secondary user transmitter, the signal to interference and noise ratio of the secondary user receiver, the throughput from the primary user transmitter to the primary user receiver, the first duration gap, the IRS reflection phase shift matrix of the first duration gap, and the IRS reflection phase shift matrix of the second duration gap are taken as constraints. Finally, the objective function is optimized and solved to obtain the maximum total throughput from the secondary user transmitter to all secondary user receivers k, thereby achieving sustainable supply of energy and effectively improving the communication performance of primary and secondary users. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 A schematic diagram showing a flow chart of a primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy-carrying communication cognition proposed in an embodiment of the present invention;

[0066] Figure 2 A structural diagram showing a wireless energy-carrying communication cognitive system assisted by an intelligent reflective surface;

[0067] Figure 3 A graph showing the variation trend of the total throughput of the secondary user system as the number of IRS reflection units increases;

[0068] Figure 4 A graph showing the variation trend of the total throughput of the secondary user system as the minimum throughput threshold of the primary user system increases;

[0069] Figure 5 A graph showing the variation trend of the total throughput of the secondary user system as the maximum transmit power threshold of the secondary user transmitter increases. DETAILED DESCRIPTION

[0070] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0071] In order to better illustrate the present embodiment, some parts of the drawings may be omitted, enlarged or reduced, and do not represent actual sizes. The description of the directions of parts such as "upper" and "lower" does not limit the present patent;

[0072] It is understandable to those skilled in the art that some well-known contents may be omitted in the drawings;

[0073] The positional relationships described in the drawings are only for illustrative purposes and should not be construed as limiting the present patent.

[0074] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0075] Example 1

[0076] like Figure 1 As shown, this embodiment proposes a primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy-carrying communication cognition, including the following steps:

[0077] S1. Establish a multi-user wireless energy-carrying communication cognitive system consisting of a secondary user transmitter, K secondary user receivers, a primary user transmitter, a primary user receiver and an IRS;

[0078] In step S1, the secondary user transmitter is equipped with M antennas and a stable power supply. The K secondary receivers, the primary user transmitter and the primary user receiver are all equipped with a single antenna. Assume that the IRS includes N passive reflection units, and the amplitude of each passive reflection unit is 1. The channel between the secondary user transmitter and the IRS is The channel between the secondary user transmitter and the secondary user receiver k is k={1,...,K}, the channel from the secondary user transmitter to the primary user transmitter is The channel from IRS to secondary user receiver k is The channel from IRS to the primary user transmitter is The channel from IRS to the primary user receiver is Channel from primary user transmitter to primary user receiver in, represents a set of complex-valued matrices of dimension x×y, The exponent of represents the dimension of the complex-valued matrix, and the channel state information of each channel is known. The reflection units of IRS need to be grouped. The grouping method is: divide the adjacent IRS reflection units into subgroups, and perform phase optimization on each subgroup. Specifically, all the reflection units in each subgroup are regarded as a whole, regarded as a single reflection unit, that is, all the reflection units in each subgroup adopt a common reflection coefficient. Therefore, only the phase optimization algorithm for each subgroup needs to be considered, without optimizing the reflection coefficient of each reflection unit, which effectively reduces the complexity of solving the problem.

[0079] S2. Assume that the information transmission phase in the multi-user cognitive wireless energy-carrying communication system includes a first duration gap and a second duration gap, in which the secondary user transmitter transmits information to all secondary user receivers and the primary user transmitter respectively, and the primary user transmitter collects energy from the information; in the second duration gap, the primary user transmitter transmits information to the primary user receiver based on the collected energy;

[0080] S3. For any secondary user receiver k among the secondary user receivers, based on the transmission information transmitted by the secondary user transmitter and the reflection phase shift matrix of the IRS in the first duration interval and the second duration interval, obtain the signal received by the secondary user receiver k, and determine the received signal-to-interference-noise ratio at the secondary user receiver k and the throughput from the primary user transmitter to the primary user receiver under the unit bandwidth;

[0081] In step S3, it is assumed that the secondary user shares the spectrum with the primary user in an overlay manner, and the duration of the information transmission phase in the multi-user cognitive wireless energy communication system is T, the first duration gap is τ, and the second duration gap is T-τ. The reflection phase shift matrix of the IRS in the first duration gap τ is expressed as:

[0082]

[0083] Among them, φ1=[q 1,1 ,...,q N,1 ] H , n={1,...,N},β n,1 ∈[0,1] and θ n,1 ∈[0,2π) are the amplitude and phase shift of the nth reflection unit of IRS in the first duration interval τ, respectively;

[0084] The reflection phase shift matrix of IRS in the second duration interval T-τ is expressed as:

[0085]

[0086] Where φ2=[q 1,2,...,q N,2 ] H , n={1,...,N},β n,2 ∈[0,1] and θ n,2 ∈[0,2π) represent the amplitude and phase shift of the nth reflection unit of IRS in the second duration interval T-τ, respectively.

[0087] During the first duration interval τ, the signal transmitted by the secondary user transmitter is expressed as:

[0088]

[0089] Among them, s k ∈C is the information transmitted from the secondary user transmitter to the secondary user receiver k, v k is the corresponding beamforming vector, s k is unit power, satisfying E[|s k | 2 ]=1, E is the mathematical expectation operation;

[0090] The signal received by the secondary user receiver k is expressed as:

[0091]

[0092] Among them, n k is the antenna noise received at the secondary user receiver k, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of

[0093] The signal received by the primary user transmitter is expressed as:

[0094]

[0095] Among them, n pt is the signal processing noise received at the primary user transmitter, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of

[0096] The energy collected by the primary user transmitter is expressed as:

[0097]

[0098] Among them, η (0≤η≤1) is the energy conversion efficiency of the primary user transmitter;

[0099] When the second duration interval is T-τ, the transmission power of the primary user transmitter transmitting information is expressed as:

[0100]

[0101] The signal received by the primary user receiver is expressed as:

[0102]

[0103] Among them, s pr is the signal sent by the primary user transmitter, which represents unit power and satisfies E[|s pr | 2 ]=1,n pr is the additive Gaussian white noise at the primary user receiver, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of .

[0104] S4. Based on the received signal-to-interference-noise ratio at the secondary user receiver k, calculate the throughput from the unit broadband secondary user transmitter to the secondary user receiver k;

[0105] S5. Based on the unit broadband sub-user transmitter to the sub-user receiver k throughput, calculate the sub-user transmitter to all sub-user receiver k throughput and;

[0106] S6. Taking the maximum sum of the throughputs from the secondary user transmitter to all secondary user receivers k as the objective function, and taking the transmission power of the secondary user transmitter, the signal-to-interference-noise ratio of the secondary user receiver, the throughput from the primary user transmitter to the primary user receiver, the first duration gap, the IRS reflection phase shift matrix of the first duration gap, and the IRS reflection phase shift matrix of the second duration gap as constraints, the objective function is optimized and solved to obtain the maximum total throughput from the secondary user transmitter to all secondary user receivers k.

[0107] In this embodiment, a multi-user wireless energy-carrying communication cognitive system consisting of a secondary user transmitter, a secondary user receiver, a primary user transmitter, a primary user receiver and an IRS is first established, and the IRS is combined with the wireless energy-carrying communication to improve the channel environment of the primary and secondary users, ensure the transmission of information between the primary and secondary users, and improve the total throughput from the secondary user transmitter to the secondary user receiver. Then, the duration of the information transmission phase is divided into a first duration interval and a second duration interval. The secondary user transmitter transmits information and energy to the secondary user receiver and the primary user transmitter respectively in the first duration interval, and the primary user transmitter uses the collected energy in the second duration interval. The objective function is to maximize the sum of the throughputs from the secondary user transmitter to all secondary user receivers k and maintain a sustainable supply of energy. The objective function is to use the transmission power of the secondary user transmitter, the signal to interference and noise ratio of the secondary user receiver, the throughput from the primary user transmitter to the primary user receiver, the first duration gap, the IRS reflection phase shift matrix of the first duration gap, and the IRS reflection phase shift matrix of the second duration gap as constraints. Finally, the objective function is optimized and solved to obtain the maximum total throughput from the secondary user transmitter to all secondary user receivers k, thereby achieving sustainable supply of energy and effectively improving the communication performance of the primary and secondary users.

[0108] Example 2

[0109] See also Figure 1 and Figure 2 In step S3, the received signal-to-interference-and-noise ratio SINR at the secondary user receiver k is k The calculation expression is:

[0110]

[0111] Assume that the primary user transmitter and the primary user receiver form the primary user system, the secondary user transmitter and K secondary user receivers form the secondary user system, the throughput from the primary user transmitter to the primary user receiver is the throughput of the primary user system, and under unit bandwidth, the throughput of the primary user system is R PR The calculation expression is:

[0112]

[0113] In step S4, the throughput R from the unit broadband secondary user transmitter to the secondary user receiver k is s,k The calculation expression is:

[0114] R s,k =τlog2(1+SINR k )

[0115] In step S5, the calculation expression of the sum R of the throughput from the secondary user transmitter to all secondary user receivers k is:

[0116]

[0117] Example 3

[0118] See also Figure 1 and Figure 2 In step S6, the calculation expression of the objective function is P1:

[0119]

[0120] The expression with the transmission power of the secondary user transmitter as the constraint is:

[0121]

[0122] The expression with the signal-to-interference-noise ratio of the secondary user receiver as the constraint is:

[0123]

[0124] The expression with the first duration gap as the constraint is:

[0125] 0≤τ≤T

[0126] The expression with the throughput from the primary user transmitter to the primary user receiver as the constraint is:

[0127]

[0128] The expression with the IRS reflection phase shift matrix of the first duration interval τ as the constraint condition is:

[0129]

[0130] The expression with the IRS reflection phase shift matrix of the second duration interval T-τ as the constraint condition is:

[0131]

[0132] Among them, {v k} is the beamforming vector of the secondary user transmitter, P ST is the maximum transmission power of the secondary user transmitter, γ k is the minimum signal-to-interference-noise ratio requirement of secondary user receiver k, β PR The minimum throughput threshold for the primary user system.

[0133] Since the optimization variables in the objective function and the optimization variables τ, {v k}, Θ1 and Θ2 are highly coupled, and the left side of the IRS reflection phase shift matrix constraint expression of the first duration interval τ and the left side of the IRS reflection phase shift matrix constraint expression of the second duration interval T-τ are not linear functions, so the optimization problem belongs to a non-convex optimization problem.

[0134] The objective function is a non-convex objective function. The method for optimizing and solving the objective function is an alternating optimization method. The object of alternating optimization is the beamforming vector {v k}, a first duration gap τ, an IRS reflection phase shift moment of the first duration gap τ, and an IRS reflection phase shift matrix of the second duration gap T-τ.

[0135] In order to better obtain the optimal solution of the objective function, first, set τ, Θ1, {v k When optimizing Θ2, the objective function is simplified to a problem of optimizing Θ2, and the objective function P1 is transformed into P2:

[0136]

[0137] The Θ2 constraint is:

[0138]

[0139] The closed-form solution is obtained by using the special structure of the objective function. Specifically, the objective function in P2 satisfies the following inequality:

[0140]

[0141] Among them, if and only if When , the above equation holds true;

[0142] In the above inequality, there is always a q n,2 Satisfying the Θ2 constraint, redefine:

[0143]

[0144] Among them, q2 is expressed as:

[0145]

[0146] h is represented by:

[0147]

[0148] Convert P2 back to P3:

[0149]

[0150] The constraints are:

[0151]

[0152]

[0153] The optimal solution of P3 is expressed as:

[0154]

[0155] Therefore, in the second duration interval T-τ, the closed-form optimal solution of the nth reflection phase shift matrix of the IRS is:

[0156]

[0157] in, for The nth element of g r,p From the closed-form optimal solution above, it can be seen that by designing the nth reflection phase shift, the signal phases on the link from the primary user transmitter to the IRS and from the IRS to the primary user receiver are aligned to achieve coherent signal combination, and the optimal solution is obtained. Afterwards, the maximum channel gain from the primary user transmitter to the primary user receiver can be expressed as:

[0158]

[0159] Therefore, problem P1 is transformed into joint optimization of τ, Θ1 and {v k}Problem P4, the specific transformation of P4 is as follows:

[0160]

[0161] The transmission power constraint expression of the current secondary user transmitter is:

[0162]

[0163] The signal-to-interference-to-noise ratio constraint expression of the current secondary user receiver is:

[0164]

[0165] The current first duration gap constraint condition expression is:

[0166] 0≤τ≤T

[0167] The current throughput constraint expression from the primary user transmitter to the primary user receiver is:

[0168]

[0169] The IRS reflection phase shift matrix constraint expression of the current first duration interval τ is:

[0170]

[0171] The IRS reflection phase shift matrix constraint expression of the current second duration interval T-τ is:

[0172]

[0173] Since P4 is a non-convex problem and difficult to solve, this embodiment adopts an alternating optimization method to solve problem P4. Specifically, problem P4 is divided into three sub-problems, namely:

[0174] (1) Setting τ, Θ1 optimizes {v k};

[0175] (2) Set τ, {v k}Optimize Θ1;

[0176] (3) Set {v k}, Θ1 optimizes τ;

[0177] The above three sub-problems are solved alternately and iteratively until the objective function value converges.

[0178] Set the optimization variables τ, Θ1, and optimize {v k The subproblem of} is expressed as P5:

[0179]

[0180] The constraints are satisfied:

[0181]

[0182]

[0183]

[0184] Define respectively:

[0185]

[0186]

[0187]

[0188]

[0189] Where Tr(·) represents the trace of the matrix, then we can get the following formula:

[0190]

[0191] Similarly, we can get:

[0192]

[0193] Transform problem P5 into P6:

[0194]

[0195] The constraints are:

[0196]

[0197] Since the objective function of problem P6 is about the optimization variable V k It is a non-convex function, so it is necessary to perform a first-order Taylor expansion on the objective function of problem P6 to obtain a convex objective function. The transformation process is as follows:

[0198]

[0199] Where V represents the set In addition, F1(V) and F2(V) are expressed as:

[0200]

[0201] Since the objective problem is to maximize the function about V, it is obvious that F1(V) is a concave function about V and F2(V) is a convex function about V. Therefore, it is necessary to perform a first-order Taylor expansion on the F2(V) function to obtain its lower bound. The details are as follows:

[0202]

[0203] in V (t) represents the feasible point of the first-order Taylor expansion, and the superscript (t) represents the number of iterations of the optimization variable. To this end, the continuous convex approximation method can be used to solve the approximate solution of R through iteration, so Substituting F2(V) can transform the objective function of problem P6 into:

[0204]

[0205] because V is an affine function, so the above equation is a concave function. To facilitate the solution, Further transformed into:

[0206]

[0207] However, due to the rank-one constraint The existence of makes problem P6 still non-convex, so the semi-positive definite relaxation technique is adopted, that is, ignoring the constraint , transforming problem P6 into problem P7:

[0208]

[0209] The constraints are:

[0210]

[0211] Question P7 is about {V k The convex optimization problem of} can be solved using the interior point method. In general, the optimal solution obtained by solving problem P7 does not satisfy the rank-one constraint. Therefore, the Gaussian randomization technique is further used to obtain an approximate rank-one solution to the problem.

[0212] Set the optimization variable τ, {v k}, the subproblem of optimizing Θ1 is expressed as P8:

[0213]

[0214] The constraints are:

[0215]

[0216]

[0217] in, is equivalent to:

[0218]

[0219] Convert question P8 to question P9:

[0220]

[0221] The constraints are:

[0222]

[0223] However, since the objective function in problem P9 is a non-convex function with respect to the optimization variable Q1, it needs to be transformed as follows:

[0224]

[0225] Among them, D1(Q1) and D2(Q1) satisfy the following expressions respectively:

[0226]

[0227] Since the objective problem is to maximize the function about Q1, it is obvious that D1(Q1) is a concave function about Q1, and D2(Q1) is a convex function about Q1. Therefore, it is necessary to perform a first-order Taylor expansion on the D2(Q1) function to obtain its lower bound. The details are as follows

[0228]

[0229] in represents the feasible point of the first-order Taylor expansion, and the superscript (t) represents the number of iterations of the optimization variable.

[0230] Similarly, the continuous convex approximation method can be used to solve the approximate solution of R through iteration. Therefore, use Substituting D2(Q1) can transform the objective function of problem P9 into

[0231]

[0232] because Since Q1 is an affine function, the above equation R is a concave function. However, due to the existence of the rank-one constraint rank(Q1)=1., problem P9 is still a non-convex problem. Therefore, the semi-positive relaxation technique is used, that is, ignoring the constraint rank(Q1)=1., to transform problem P9 into problem P10:

[0233]

[0234] The constraints are satisfied:

[0235]

[0236]

[0237] Problem P10 is a convex optimization problem about Q1, which can be solved using the interior point method. Generally, the optimal solution obtained by solving problem P10 does not satisfy the rank-one constraint. Therefore, the Gaussian randomization method is further used to obtain an approximate rank-one solution to the problem.

[0238] Set the optimization variable Θ1, {v k}, the subproblem of optimizing τ is expressed as P11:

[0239]

[0240] The constraints are:

[0241]

[0242] Since the objective function is an affine function with respect to τ, and the left-hand side of the constraint condition is a convex function with respect to τ, the constraint condition is a convex constraint condition, where the constraint condition of the current first duration gap τ is:

[0243] 0≤τ≤T

[0244] Problem P11 is a convex problem and is further solved using the interior point method.

[0245] The specific solution process is:

[0246] S81. Assume that the maximum sum of the throughput of the secondary user system is the objective function, and the expression of the objective function is:

[0247] R=f({v k},τ,Θ1,Θ2)

[0248] S82. Pass Obtain the closed-form optimal solution of the nth reflection phase shift matrix of the IRS And the beamforming vector {v k}, the first duration gap τ, the IRS reflection phase shift moment of the first duration gap τ and the objective function are initialized respectively, and {v k (0)}、τ (0) , and R (0) , where R (0) The expression is:

[0249]

[0250] Let the number of iterations be i, the initial value be 0, and the convergence threshold be ε0 = 1 × 10 -2 ;

[0251] S83. Setting τ (i) and And use the initial values ​​of S82 to solve the objective function of the transformed problem P7 and obtain {V k (i+1)}; Set {V k (i+1)} and τ (i) , and use the initial values ​​of S82 to solve the objective function of the transformed problem P10, and obtain {Q1 (i+1)}; Set {V k (i+1)} and {Q1 (i+1)}, and use the initial values ​​of S82 to solve the objective function of the transformed problem P11, and obtain {τ (i+1)};

[0252] S84. The obtained {V k (i+1)}, {Q1 (i+1)} and {τ (i+1)}Substitute into the objective function to obtain f({V k (i)},τ(i) ,Q (i) )middle;

[0253] S85. Let i=i+1;

[0254] S86. Judgment If so, output the optimal Execute step S86; otherwise, return to step S82;

[0255] S87. Using Gaussian random method , Q1 * The matrices are restored to rank-one vectors {v k *}and τ * 、{v k *}、 and Substituting the objective function in S1, the optimal solution of the objective function is output as:

[0256]

[0257] The optimal solution of the objective function is expressed as the maximum value of the sum of the throughputs of the secondary user systems.

[0258] Further, this embodiment has obtained Figure 3 , that is, the total throughput of the secondary user system changes with the increase in the number of IRS reflection units, given by Figure 3 It can be seen that the algorithm proposed in the present invention is very close to the "semi-definite relaxation" scheme and is much higher than other schemes, reflecting the superiority of the algorithm proposed in the present invention. Except for the "no IRS" scheme, the total throughput of the secondary user system remains unchanged as the number of reflections increases. The total throughput of the secondary user system of the other 6 schemes increases with the increase in the number of reflection units, which shows that deploying IRS is very effective in improving system performance, and as the number of IRS reflection units increases, the system will obtain higher channel gain. In addition, it can be observed that the scheme of using a common IRS phase shift matrix for phase optimization of the IRS phase shift matrix of two transmission time slots is better than the scheme of fixing the IRS phase shift matrix of two transmission time slots, and as the number of reflection units increases, the greater the channel gain obtained, the more obvious the effect of IRS on improving system performance. Finally, it can be found that under the same number of IRS reflection units, the proposed "low complexity algorithm 1 / 2" and "low complexity algorithm 1 / 4" schemes are much higher than the "no IRS scheme", but lower than the algorithm proposed in the present invention, which effectively shows that the low complexity algorithm proposed in the present invention can effectively balance the relationship between system performance and complexity.

[0259] Figure 4The total throughput of the secondary user system changes as the minimum throughput threshold of the primary user system increases. Figure 4 It can be seen that the total throughput of the secondary user system of all schemes decreases with the increase of the minimum throughput threshold of the primary user, among which the "no IRS" scheme has the most obvious downward trend, while the downward trend of the other six schemes is not obvious. This is because as the minimum throughput threshold of the primary user increases, the secondary user transmitter needs to transmit more energy signals to the primary user transmitter, thereby reducing its own data transmission performance. In addition, the performance of the algorithm proposed in the present invention is very close to the "semi-positive definite relaxation" scheme, and is significantly better than the other five comparison schemes. The "optimized θ (θ = θ1 = θ2)" scheme, the "low complexity algorithm 1 / 2" and the "low complexity algorithm 1 / 4" schemes are better than the "fixed θ1, θ2" scheme. This is because the more IRS reflection phases are optimized in each time slot, the greater the channel spatial freedom provided, and the greater the channel gain obtained, which reflects the effectiveness of the scheme proposed in the present invention.

[0260] See also Figure 5 , that is, the total throughput of the secondary user system changes with the increase of the maximum transmission power threshold of the secondary user transmitter, from Figure 5 It can be seen that the total throughput of the secondary user system of all schemes increases with the increase of the maximum transmit power threshold of the secondary user transmitter, among which the performance of the algorithm proposed in the present invention is close to the "semi-definite relaxation" scheme, and is significantly better than the other five schemes, which shows that the algorithm proposed in the present invention has reasonably optimized the transmit beamforming, time slot time and IRS phase shift of two transmission time slots. In addition, it can be found that with the increase of the maximum transmit power threshold, the magnitude of the improvement of the total throughput of the other schemes gradually decreases compared with the "no IRS" scheme. This is because with the increase of the transmit power threshold, the active beamforming gain brought by the secondary user transmitter is sufficient to meet the constraints. Therefore, the passive gain brought by deploying IRS does not significantly improve the system performance, but it is much better than the "no IRS" scheme.

[0261] Obviously, the above embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A primary and secondary spectrum sharing method for intelligent reflective surface assisted wireless energy communication cognition, characterized in that: The following steps are involved: S1. Establish a multi-user wireless energy-carrying communication cognitive system consisting of a secondary user transmitter, K secondary user receivers, a primary user transmitter, a primary user receiver and an IRS; S2. Assume that the information transmission phase in the multi-user cognitive wireless energy-carrying communication system includes a first duration gap and a second duration gap, in which the secondary user transmitter transmits information to all secondary user receivers and the primary user transmitter respectively, and the primary user transmitter collects energy from the information; In a second duration interval, the primary user transmitter transmits information to the primary user receiver based on the collected energy; S3. For any secondary user receiver k among the secondary user receivers, based on the transmission information transmitted by the secondary user transmitter and the reflection phase shift matrix of the IRS in the first duration interval and the second duration interval, obtain the signal received by the secondary user receiver k, and determine the received signal-to-interference-noise ratio at the secondary user receiver k and the throughput from the primary user transmitter to the primary user receiver under the unit bandwidth; S4. Based on the received signal-to-interference-noise ratio at the secondary user receiver k, calculate the throughput from the unit broadband secondary user transmitter to the secondary user receiver k; S5. Based on the unit broadband next user transmitter to the secondary user receiver k throughput, calculate the secondary user transmitter to all secondary user receiver k and the throughput; S6. Taking the maximum sum of the throughputs from the secondary user transmitter to all secondary user receivers k as the objective function, and taking the transmission power of the secondary user transmitter, the signal to interference noise ratio of the secondary user receiver, the throughput from the primary user transmitter to the primary user receiver, the first duration gap, the IRS reflection phase shift matrix of the first duration gap, and the IRS reflection phase shift matrix of the second duration gap as constraints, the objective function is optimized and solved to obtain the maximum total throughput from the secondary user transmitter to all secondary user receivers k. The secondary user transmitter is equipped with M antennas and a stable power supply. The K secondary receivers, the primary user transmitter and the primary user receiver are all equipped with a single antenna. Assume that the IRS includes N passive reflection units, and the amplitude of each passive reflection unit is 1. The channel between the secondary user transmitter and the IRS is The channel between the secondary user transmitter and the secondary user receiver k is k={1,...,K}, the channel from the secondary user transmitter to the primary user transmitter is The channel from IRS to secondary user receiver k is The channel from IRS to the primary user transmitter is The channel from IRS to the primary user receiver is Channel from primary user transmitter to primary user receiver in, represents a set of complex-valued matrices of dimension x×y, The exponent of represents the dimension of the complex-valued matrix, and the channel state information of each channel is known; In step S3, assuming that the duration of the information transmission phase in the multi-user cognitive wireless energy-carrying communication system is T, the first duration interval is τ, and the second duration interval is T-τ, the reflection phase shift matrix of the IRS in the first duration interval τ is expressed as: Θ1=diag(φ1 H ) Where φ1=[q 1,1 ,...,q N,1 ] H , n={1,...,N},β n,1 ∈[0,1] and θ n,1 ∈[0,2π) are the amplitude and phase shift of the nth reflection unit of IRS in the first duration interval τ, respectively; The reflection phase shift matrix of IRS in the second duration interval T-τ is expressed as: Θ2=diag(φ2 H ) Where φ2=[q 1,2 ,...,q N,2 ] H , n={1,...,N},β n,2 ∈[0,1] and θ n,2 ∈[0,2π) represent the amplitude and phase shift of the nth reflection unit of IRS in the second duration interval T-τ, respectively; During the first duration interval τ, the signal transmitted by the secondary user transmitter is expressed as: Among them, s k ∈C is the information transmitted from the secondary user transmitter to the secondary user receiver k, v k is the corresponding beamforming vector, s k is unit power, satisfying E[|s k | 2 ]=1, E is the mathematical expectation operation; The signal received by the secondary user receiver k is expressed as: Among them, n k is the antenna noise received at the secondary user receiver k, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of The signal received by the primary user transmitter is expressed as: Among them, n pt is the signal processing noise received at the primary user transmitter, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of The energy collected by the primary user transmitter is expressed as: Among them, η (0≤η≤1) is the energy conversion efficiency of the primary user transmitter; When the second duration interval is T-τ, the transmission power of the primary user transmitter transmitting information is expressed as: The signal received by the primary user receiver is expressed as: Among them, s pr is the signal sent by the primary user transmitter, which represents unit power and satisfies E[|s pr | 2 ]=1,n pr is the additive Gaussian white noise at the primary user receiver, which has a mean of 0 and a variance of The cyclically symmetric complex Gaussian distribution of .

2. The primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy communication cognition according to claim 1 is characterized in that: In step S3, the received signal-to-interference-and-noise ratio SINR at the secondary user receiver k is k The calculation expression is: Assume that the primary user transmitter and the primary user receiver form the primary user system, the secondary user transmitter and K secondary user receivers form the secondary user system, the throughput from the primary user transmitter to the primary user receiver is the throughput of the primary user system, and under unit bandwidth, the throughput of the primary user system is R PR The calculation expression is:

3. The primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy communication cognition according to claim 2 is characterized in that: In step S4, the throughput R from the unit broadband secondary user transmitter to the secondary user receiver k is s,k The calculation expression is: R s,k =τlog2(1+SINR k )。 4. The primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy communication cognition according to claim 3 is characterized in that: In step S5, the calculation expression of the sum R of the throughput from the secondary user transmitter to all secondary user receivers k is:

5. The primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy communication cognition according to claim 4 is characterized in that: In step S6, the calculation expression of the objective function is: The expression with the transmission power of the secondary user transmitter as the constraint is: The expression with the signal-to-interference-noise ratio of the secondary user receiver as the constraint is: The expression with the first duration gap as the constraint is: 0≤τ≤T The expression with the throughput from the primary user transmitter to the primary user receiver as the constraint is: The expression with the IRS reflection phase shift matrix of the first duration interval τ as the constraint condition is: The expression with the IRS reflection phase shift matrix of the second duration interval T-τ as the constraint condition is: Among them, {v k } is the beamforming vector of the secondary user transmitter, P ST is the maximum transmission power of the secondary user transmitter, γ k is the minimum signal-to-interference-noise ratio requirement of secondary user receiver k, β PR Minimum throughput threshold for the primary user system.

6. The primary and secondary spectrum sharing method for intelligent reflective surface-assisted wireless energy communication cognition according to claim 5 is characterized in that: In step S6, the objective function is a non-convex objective function, and the method for optimizing and solving the objective function is an alternating optimization method, and the object of alternating optimization is the beamforming vector {v k }, a first duration gap τ, an IRS reflection phase shift moment of the first duration gap τ, and an IRS reflection phase shift matrix of the second duration gap T-τ.

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