Wireless information and energy simultaneous transmission method based on mobile antenna

Abstract

The invention discloses a wireless information and energy simultaneous transmission method based on a mobile antenna, which comprises the following steps of: firstly, obtaining energy collection and communication performance indexes in a wireless information and energy simultaneous transmission system; secondly, constructing an optimization problem of maximizing the communication rate of the information receiver under the constraint that the energy collected by the energy receiver is greater than a preset threshold value; then, an alternative optimization method is used for solving the optimization problem about the transmitting beam of the information transmitter and the position of the mobile antenna; thirdly, stopping iteration when the communication rate obtained by the current and later iterations meets the iteration condition, and taking the currently obtained communication rate of the information receiver as an optimal value; the method has the advantages that the communication rate of the information receiver can be greatly improved by adjusting the position of the mobile antenna of the information transmitter under the condition of ensuring that the energy collected by the energy receiver is greater than the preset threshold value.

Description

Technical Field

[0001] The invention relates to a wireless information and energy simultaneous transmission technology, and in particular to a wireless information and energy simultaneous transmission method based on a mobile antenna. Background Art

[0002] With the continuous development of the Internet of Things and the increasing number of sensors, the demand for large-scale connections in Internet of Things scenarios such as environmental monitoring, smart agriculture, and industrial automation is increasing. In large-scale Internet of Things scenarios, the energy consumption of sensors has always been a concern. Since sensors are generally small in size, the battery devices they carry are also small, which greatly limits the working time of sensors. Sensors can effectively solve the problem of insufficient energy by converting wireless signals into energy and collecting them through wireless energy harvesting technology. In addition, when the sensor has sufficient energy, it can effectively decode the information to obtain the information transmitted by the transmitter. A network with simultaneous information transmission and information decoding can be called a wireless information and energy simultaneous transmission network, which is particularly suitable for future high-energy consumption Internet of Things systems. In order to improve the performance of wireless information and energy simultaneous transmission networks, equipping the transmitter with multiple antennas is considered to be a very effective method. Multi-antenna technology can significantly improve the transmission rate of the network through the diversity gain brought by multiple antennas, and can also increase the energy collected by sensors. It is one of the core technologies in 5G networks and future 6G networks.

[0003] However, in the traditional multi-antenna wireless information and energy simultaneous transmission system, the multi-antennas are deployed in fixed positions, and they cannot fully utilize the spatial variation of the wireless channel. This situation is more obvious when the number of antennas is limited. In order to further improve the spatial freedom of the multi-antennas to improve the transmission rate of the wireless information and energy simultaneous transmission system and the energy collected by the sensor, the multi-antenna wireless information and energy simultaneous transmission system based on mobile antennas is considered to be an effective method. In the multi-antenna wireless information and energy simultaneous transmission system based on mobile antennas, the mobile antenna is connected to the RF link through a flexible cable, and the position of the mobile antenna can be adjusted in real time by a controller such as a stepper motor or a servo motor. Unlike the traditional multi-antenna wireless information and energy simultaneous transmission system with a fixed position, the multi-antenna wireless information and energy simultaneous transmission system based on mobile antennas can flexibly change the position of the mobile antenna, thereby reshaping the channel between them to achieve a higher transmission rate and collect energy. Therefore, it is very important to effectively adjust the position of the mobile antenna and the beamforming of the transmitter to improve the transmission rate of the multi-antenna wireless information and energy simultaneous transmission system based on mobile antennas while increasing the collected energy. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for simultaneous transmission of wireless information and energy based on a mobile antenna, which can simultaneously improve the energy collected by an energy receiver and the communication rate of the information receiver by adjusting the mobile antenna position and the transmission beam of the information transmitter.

[0005] The technical solution adopted by the present invention to solve the above technical problems is: a method for simultaneous transmission of wireless information and energy based on a mobile antenna, characterized by comprising the following steps:

[0006] Step 1: In the wireless information and energy simultaneous transmission system, assume that there is an information transmitter equipped with N mobile antennas, an information receiver equipped with 1 fixed antenna, and an energy receiver equipped with 1 fixed antenna. The N mobile antennas equipped by the information transmitter are distributed in the area Ω of A×A, and the interval D between the mobile antennas is greater than or equal to 0.5λ. The fixed antennas equipped by the information receiver and the fixed antennas equipped by the energy receiver are located at the center of the area Ω of A×A. The information sent by the information transmitter is denoted as s, and the information received by the information receiver is denoted as The information received by the energy receiver is recorded as

[0007] Wherein, N>1, A=4λ, λ represents the signal wavelength, the coordinates of the center position of the area Ω are set to (0, 0), the x-axis coordinates of the area Ω are from -A / 2 to A / 2, and the y-axis coordinates are also from -A / 2 to A / 2, t represents the vector formed by the coordinates of the N mobile antennas equipped by the information transmitter in sequence, t n represents the coordinates of the nth mobile antenna equipped by the information transmitter, n=1,···,N,t n ∈Ω, represents the x-axis coordinate of the nth mobile antenna equipped by the information transmitter, represents the y-axis coordinate of the nth mobile antenna equipped by the information transmitter, [] T represents the matrix transpose operation, The channel coefficient representing the channel from the information transmitter to the information receiver, (·) H represents the conjugate transpose operation, The receiving response matrix representing the link from the information transmitter to the information receiver, The dimension is K I A column vector of all 1s, K I represents the number of receiving paths from the information transmitter to the information receiver, Σ I The path response matrix represents the link from the information transmitter to the information receiver, The transmission response matrix representing the link from the information transmitter to the information receiver, represents the transmission response vector of the link from the nth mobile antenna equipped by the information transmitter to the information receiver, n=1,···,N, e is a natural constant, j is an imaginary unit, L I represents the number of transmission paths from the information transmitter to the information receiver, The lth transmission path of the link from the information transmitter to the information receiver is at t n The path difference between the location and the center of the region Ω, represents the elevation angle of the lth transmission path of the link from the information transmitter to the information receiver, represents the azimuth of the lth transmission path of the link from the information transmitter to the information receiver, v represents the transmission beam of the information transmitter, and n I represents the noise of the information receiver, n I The variance of represents the channel coefficient of the channel from the information transmitter to the energy receiver, represents the receiving response matrix of the link from the information transmitter to the energy receiver, The dimension is K E A column vector of all 1s, K E represents the number of receiving paths from the information transmitter to the energy receiver, Σ E represents the path response matrix of the link from the information transmitter to the energy receiver, represents the transmission response matrix of the link from the information transmitter to the energy receiver, g E (t n ) represents the transmission response vector of the link from the nth mobile antenna equipped by the information transmitter to the energy receiver, n=1,···,N,L E represents the number of transmission paths of the link from the information transmitter to the energy receiver, The lth transmission path of the link from the information transmitter to the energy receiver is at t n The path difference between the location and the center of the region Ω, represents the elevation angle of the lth transmission path of the link from the information transmitter to the energy receiver, represents the azimuth of the lth transmission path of the link from the information transmitter to the energy receiver, n E represents the noise of the energy receiver;

[0008] Step 2: Measure the communication rate R of the information receiver with the channel capacity. The performance of the energy receiver is measured by the amount of energy collected, expressed as in, τ represents the efficiency of energy collection, Tr(·) represents the trace of the matrix;

[0009] Step 3: Based on step 2, construct an optimization problem to maximize the communication rate R of the information receiver under the constraint that the energy collected by the energy receiver is greater than the preset threshold, which is described as:

[0010]

[0011] Among them, t u represents the coordinates of the u-th mobile antenna equipped by the information transmitter, P max Indicates the maximum transmission power of the information transmitter, represents the preset threshold of energy collected by the energy receiver, rank(·) represents the rank operation of the matrix;

[0012] Step 4: Given t, transform the optimization problem constructed in step 3 into a new optimization problem P1, which is described as:

[0013]

[0014] Then the constraints in the new optimization problem P1 are Remove it and transform the new optimization problem P1 into a convex optimization problem P2, which can be described as:

[0015] Step 5: In the given and the coordinates of the nth mobile antenna t n The coordinates of all other mobile antennas except u ,u∈{1,···,N},n≠u, the optimization problem constructed in step 3 is converted into a new optimization problem P3, which is described as:

[0016]

[0017] Among them, f I (t n ) and f E (t n ) are all introduced intermediate quantities,

[0018] Then, for the new optimization problem P3, q (t n ),q∈{I,E}at a feasible initial point Perform a first-order Taylor expansion at , and we get: in, represents f q (t n ),q∈{I,E}at a feasible initial point The first-order Taylor expansion at is the intermediate quantity introduced, To calculate the real part, g q (t n ) is g I (t n ) or g E (t n ), n=1,···,N,ηq is the introduced intermediate quantity, v(n) represents the nth element in v, v(u) represents the uth element in v, Will Substitution n=1,···,N v(i) represents the i-th element in v, v(a) represents the a-th element in v, and are all feasible initial points. Substitution n=1,···,N Will Substitution n=1,···,N

[0019] Again At a feasible starting point Perform a second-order Taylor expansion at , and we get: in, express At a feasible starting point The second-order Taylor expansion at Substitution Get express The gradient of || is the modulus operator, η q (l) represents η q The lth element in , ∠η q (l) represents η q (l) angle, for or Will Substitution Get

[0020] Then, the constraint ||t in the new optimization problem P3 is n -t u ||2≤||t in D n -t u||2 At a feasible initial point Perform a first-order Taylor expansion at , and we get:

[0021] Finally, the new optimization problem P3 is transformed into a convex optimization problem P4, which is described as:

[0022]

[0023] Step 6: Use external iteration to solve the convex optimization problem P2 obtained in step 4, and obtain The optimal solution of t in each external iteration is obtained; in each external iteration, the convex optimization problem P4 obtained in step 5 is solved by internal iteration for the coordinates of each mobile antenna, and the solution of the coordinates in each internal iteration for the coordinates of each mobile antenna is obtained. When the solution of the coordinates in the internal iteration satisfies the internal iteration conditions, the optimal solution of t in each external iteration is obtained; in the external iteration The optimal solution and The optimal value of R is obtained when the optimal solution meets the external iteration conditions.

[0024] In step 1, Σ I is a diagonal matrix, the first element on the diagonal is a random variable with mean 0 and variance 0.5, and the remaining elements on the diagonal except the first element are random variables with mean 0 and variance A random variable Σ E is a diagonal matrix, the first element on the diagonal is a random variable with mean 0 and variance 0.5, and the remaining elements on the diagonal except the first element are random variables with mean 0 and variance A random variable.

[0025] The specific process of step 6 is as follows:

[0026] Step 6.1: Order represents the number of external iterations, The initial value of is 1;

[0027] Step 6.2: In During the external iteration, Substitute into the convex optimization problem P2 obtained in step 4 and solve it using the interior point method to obtain External iterations Solution if Then As The optimal solution if Then execute the following process: 1) Perform eigenvalue decomposition and get Among them, each column vector of U is is an eigenvector of , Λ is a diagonal matrix, and its diagonal elements are eigenvalues; 2) randomly generate P eigenvalues ​​with mean 0 and variance I N The pth complex Gaussian vector is denoted by w p , then let Further order in, represents the square root of the matrix Λ, I N represents the N-order identity matrix, p=1,···,P,v p and are all intermediate quantities introduced; 3) Substitute them into the convex optimization problem P2 as candidate values, and take the candidate values ​​that both satisfy the constraints in the convex optimization problem P2 and maximize the objective function as the first External iterations The optimal solution in, hour For initialization solution hour Indicates The solution of t at the outer iteration;

[0028] Step 6.3: Traverse the coordinates of each mobile antenna equipped by the information transmitter;

[0029] Step 6.4: Assume that the coordinate t of the nth mobile antenna is currently being traversed n ; Let m represent the number of internal iterations of step 5, and the initial value of m is 1;

[0030] Step 6.5: During the mth internal iteration, after obtaining the External iterations The optimal solution Under the premise of Substitute u∈{1,···,N},n≠u into the convex optimization problem P4 obtained in step 5 and solve it using the interior point method to obtain the mth internal iteration time t n Solution in, for The u-th element in, when m=1 for When m≠1 represents the solution of t at the m-1th internal iteration;

[0031] Step 6.6: and Substitute In the corresponding and Then judge the internal iteration condition Is it true? If so, then As the External iteration time t n Solution For t n The internal iteration is over, and the coordinates of the next mobile antenna are traversed, and then the step 6.4 is returned to continue the execution. After the coordinates of all mobile antennas are traversed, the first External iterations The optimal solution Then execute step 6.7; if it is not true, set m=m+1, and then return to step 6.5 to continue iterating; where, for The nth element in , abs(·) is the absolute value function, ε1 represents the preset internal iteration judgment threshold, and the "=" in m=m+1 is the assignment symbol;

[0032] Step 6.7: and Substitute In the corresponding and Then judge the external iteration condition Is it true? If so, then As the The optimal value of R at the external iteration final , the external iteration ends; if it does not hold, then let Then return to step 6.2 to continue iteration; where, hour For initialization solution hour Indicates External iterations The solution, ε2 represents the preset external iteration judgment threshold, The “=” in is the assignment symbol.

[0033] In step 6.2, The generation steps are as follows: the initialization value of the coordinates of the first mobile antenna equipped by the information transmitter Among them, rand(1,2) represents a row vector containing two random numbers between 0 and 1; the initial value of the coordinates of the second mobile antenna equipped by the information transmitter is And meet By analogy, the initialization value of the coordinates of the nth mobile antenna equipped by the information transmitter is And meet u'∈{1,···,n-1}, where represents the initialization value of the coordinates of the u'th mobile antenna equipped by the information transmitter; the initialization value of the coordinates of the Nth mobile antenna equipped by the information transmitter And meet u'∈{1,···,N-1}; in step 6.7, Equivalent to Substitute into the convex optimization problem P2 obtained in step 4 and solve the obtained The solution.

[0034] Compared with the prior art, the advantages of the present invention are:

[0035] 1) The method of the present invention can greatly improve the communication rate of the information receiver while ensuring that the energy collected by the energy receiver is greater than a preset threshold, thereby effectively achieving sufficient energy collection while effectively ensuring the communication rate.

[0036] 2) The method of the present invention equips the information transmitter with a mobile antenna, and further improves the spatial freedom by moving the position of the antenna, thereby effectively improving energy collection and communication rate.

[0037] 3) The method of the present invention adopts an alternating optimization method to optimize the transmission beam of the information transmitter and the position of the mobile antenna in the wireless information and energy simultaneous transmission system, thereby effectively improving the collection energy and communication rate of the wireless information and energy simultaneous transmission system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flowchart of the method of the present invention;

[0039] Figure 2 The performance curves of the information receiver's rate versus maximum transmission signal-to-noise ratio obtained by using the method of the present invention and the existing fixed antenna method are compared. DETAILED DESCRIPTION

[0040] The present invention is further described in detail below with reference to the accompanying drawings.

[0041] The present invention proposes a method for simultaneous wireless information and energy transmission based on a mobile antenna, and its flow chart is as follows: Figure 1 As shown, it is applicable to a wireless information and energy simultaneous transmission system in which the information transmitter is equipped with a mobile antenna, and it includes the following steps:

[0042] Step 1: In the wireless information and energy simultaneous transmission system, assume that there is an information transmitter equipped with N mobile antennas, an information receiver equipped with 1 fixed antenna, and an energy receiver equipped with 1 fixed antenna. The N mobile antennas equipped by the information transmitter are distributed in the area Ω of A×A, and the interval D between the mobile antennas needs to be greater than or equal to 0.5λ. The fixed antennas equipped by the information receiver and the fixed antennas equipped by the energy receiver are located at the center of the area Ω of A×A. The information sent by the information transmitter is recorded as s, and the information received by the information receiver is recorded as The information received by the energy receiver is recorded as

[0043] Wherein, N>1, in this embodiment, N=4, A=4λ, λ represents the signal wavelength, in this embodiment, λ=1.5 meters, the coordinates of the center position of the area Ω are set to (0, 0), the x-axis coordinate of the area Ω is from -A / 2 to A / 2, and the y-axis coordinate is also from -A / 2 to A / 2, in this embodiment, D=0.5λ, t represents the vector formed by the coordinates of the N mobile antennas equipped by the information transmitter in sequence, t n represents the coordinates of the nth mobile antenna equipped by the information transmitter, n=1,···,N,t n ∈Ω, represents the x-axis coordinate of the nth mobile antenna equipped by the information transmitter, represents the y-axis coordinate of the nth mobile antenna equipped by the information transmitter, [] T represents the matrix transpose operation, t1 represents the coordinates of the first mobile antenna equipped by the information transmitter, t N represents the coordinates of the Nth mobile antenna equipped by the information transmitter, The channel coefficient representing the channel from the information transmitter to the information receiver, (·) H represents the conjugate transpose operation, The receiving response matrix representing the link from the information transmitter to the information receiver, The dimension is K I A column vector of all 1s, K I represents the number of receiving paths from the information transmitter to the information receiver. In this embodiment, K I =3,Σ I The path response matrix represents the link from the information transmitter to the information receiver, The transmission response matrix representing the link from the information transmitter to the information receiver, g I (t n) represents the transmission response vector of the link from the nth mobile antenna equipped by the information transmitter to the information receiver, n=1,···,N, e is a natural constant, e=2.71…, j is an imaginary unit, L I represents the number of transmission paths of the link from the information transmitter to the information receiver. In this embodiment, L I =3, The lth transmission path of the link from the information transmitter to the information receiver is at t n The path difference between the location and the center of the region Ω, represents the elevation angle of the lth transmission path of the link from the information transmitter to the information receiver. In this embodiment, is a random number between 0 and 2π, The azimuth of the lth transmission path of the link from the information transmitter to the information receiver is represented by is a random number between 0 and 2π, v represents the transmission beam of the information transmitter, n I represents the noise of the information receiver, n I The variance of In this example, represents the channel coefficient of the channel from the information transmitter to the energy receiver, represents the receiving response matrix of the link from the information transmitter to the energy receiver, The dimension is K E A column vector of all 1s, K E represents the number of receiving paths from the information transmitter to the energy receiver. In this embodiment, K E =3,Σ E represents the path response matrix of the link from the information transmitter to the energy receiver, represents the transmission response matrix of the link from the information transmitter to the energy receiver, g E (t n ) represents the transmission response vector of the link from the nth mobile antenna equipped by the information transmitter to the energy receiver, n=1,···,N,L E represents the number of transmission paths of the link from the information transmitter to the energy receiver. In this embodiment, L E =3, The lth transmission path of the link from the information transmitter to the energy receiver is at t n The path difference between the location and the center of the region Ω, represents the elevation angle of the lth transmission path of the link from the information transmitter to the energy receiver. In this embodiment, is a random number between 0 and 2π, The azimuth of the lth transmission path of the link from the information transmitter to the energy receiver is represented by is a random number between 0 and 2π, n E Represents the noise of the energy receiver.

[0044] In this specific embodiment, Σ I is a diagonal matrix, the first element on the diagonal is a random variable with mean 0 and variance 0.5, and the remaining elements on the diagonal except the first element are random variables with mean 0 and variance A random variable Σ E is a diagonal matrix, the first element on the diagonal is a random variable with mean 0 and variance 0.5, and the remaining elements on the diagonal except the first element are random variables with mean 0 and variance A random variable.

[0045] Step 2: Measure the communication rate R of the information receiver with the channel capacity. As a communication performance indicator; the performance of the energy receiver is measured by the amount of collected energy, expressed as As an energy harvesting indicator; among them, τ represents the efficiency of energy collection, and in this example, τ=0.5, and Tr(·) represents the trace of the matrix.

[0046] Step 3: Based on step 2, construct an optimization problem to maximize the communication rate R of the information receiver under the constraint that the energy collected by the energy receiver is greater than the preset threshold, which is described as:

[0047]

[0048] Among them, max is the maximization function, st means "subject to...", || ||2 means the binary norm operation, and t u represents the coordinates of the u-th mobile antenna equipped by the information transmitter, represents the x-axis coordinate of the u-th mobile antenna equipped by the information transmitter, represents the y-axis coordinate of the u-th mobile antenna equipped by the information transmitter, P max Indicates the maximum transmission power of the information transmitter. In this embodiment, P max =10dBm, Q represents the preset threshold of energy collected by the energy receiver, which is taken in this embodiment rank(·) represents the rank operation of a matrix.

[0049] Step 4: Given In the case of , the optimization problem constructed in step 3 is converted into a new optimization problem P1, which is described as:

[0050]

[0051] Then the constraints in the new optimization problem P1 are Remove it and transform the new optimization problem P1 into a convex optimization problem P2, which can be described as:

[0052]

[0053] Step 5: In the given and the coordinates of the nth mobile antenna t n The coordinates of all other mobile antennas except u ,u∈{1,···,N},n≠u, the optimization problem constructed in step 3 is converted into a new optimization problem P3, which is a non-convex optimization problem and is described as:

[0054]

[0055] Among them, f I (t n ) and f E (t n ) are all introduced intermediate quantities,

[0056] Then, because f in the new optimization problem P3 I (t n ) and f E (t n ), so they are processed in the same way. Specifically, for the new optimization problem P3, q (t n ),q∈{I,E}at a feasible initial point Perform a first-order Taylor expansion at , and we get: in, represents f q (t n ),q∈{I,E}at a feasible initial point The first-order Taylor expansion at f q (t n ) is the introduced intermediate quantity, To calculate the real part, g q (t n ) is g I (t n ) or g E (t n ), n=1,···,N,η q is the intermediate quantity introduced, v(n) represents the nth element in v, v(u) represents the uth element in v, Will Substitution n=1,···,N v(i) represents the i-th element in v, v(a) represents the a-th element in v, and are all feasible initial points. Substitution n=1,···,N Will Substitution n=1,···,N

[0057] Again At a feasible starting point Perform a second-order Taylor expansion at , and we get: in, express At a feasible starting point The second-order Taylor expansion at Substitution Get express The gradient of | | is the modulus operator, η q (l) represents η q The lth element in , ∠η q (l) represents η q (l) angle, for or Will Substitution Get

[0058] Then, the constraint ||t in the new optimization problem P3 is n -t u ||2≤||t in D n -t u ||2 At a feasible initial point Perform a first-order Taylor expansion at , and we get:

[0059] Finally, the new optimization problem P3 is transformed into a convex optimization problem P4, which is described as:

[0060] This convex optimization problem P4 can be directly solved by the interior point method to obtain t n The solution.

[0061] Step 6: Use external iteration to solve the convex optimization problem P2 obtained in step 4, and obtain The optimal solution; in each external iteration process, for the coordinates of each mobile antenna, the convex optimization problem P4 obtained in step 5 is solved by internal iteration to obtain the solution of the coordinates of each mobile antenna at each internal iteration. When the solution of the coordinates at the internal iteration satisfies the internal iteration condition, the solution of the coordinates at each external iteration is obtained. The optimal solution of The optimal value of R is obtained when the optimal solution of and the optimal solution of t meet the external iteration conditions.

[0062] In this specific embodiment, the specific process of step 6 is:

[0063] Step 6.1: Order represents the number of external iterations, The initial value of is 1.

[0064] Step 6.2: In During the external iteration, Substituting into the convex optimization problem P2 obtained in step 4, we get And use the interior point method to solve it, and get External iterations Solution if Then As The optimal solution if Then execute the following process: 1) Perform eigenvalue decomposition and get Among them, each column vector of U is is an eigenvector of , Λ is a diagonal matrix, and its diagonal elements are eigenvalues; 2) randomly generate P eigenvalues ​​with mean 0 and variance I N The pth complex Gaussian vector is denoted by w p , then let Further order in, represents the square root of the matrix Λ. In this embodiment, P=500, I N represents the N-order identity matrix, p=1,···,P,v p and are all intermediate quantities introduced; 3) Substitute them into the convex optimization problem P2 as candidate values, and take the candidate values ​​that both satisfy the constraints in the convex optimization problem P2 and maximize the objective function as the first External iterations The optimal solution in, hour For initialization solution hour Indicates The solution for t at the outer iteration.

[0065] Here, The generation steps are as follows: the initialization value of the coordinates of the first mobile antenna equipped by the information transmitter Among them, rand(1,2) represents a row vector containing two random numbers between 0 and 1; the initial value of the coordinates of the second mobile antenna equipped by the information transmitter is And meet By analogy, the initialization value of the coordinates of the nth mobile antenna equipped by the information transmitter is And meet u'∈{1,···,n-1}, where represents the initialization value of the coordinates of the u'th mobile antenna equipped by the information transmitter; the initialization value of the coordinates of the Nth mobile antenna equipped by the information transmitter And meet u′∈{1,···,N-1}.

[0066] Step 6.3: Traverse the coordinates of each mobile antenna equipped by the information transmitter.

[0067] Step 6.4: Assume that the coordinate t of the nth mobile antenna is currently being traversed n ; Let m represent the number of internal iterations of step 5, and the initial value of m is 1.

[0068] Step 6.5: During the mth internal iteration, after obtaining the External iterations The optimal solution Under the premise of Substitute u∈{1,···,N},n≠u into the convex optimization problem P4 obtained in step 5 and we get n,u∈{1,···,N},n≠u, and use the interior point method to solve and get the mth internal iteration time t n Solution in, for The u-th element in, when m=1 for When m≠1 Indicates the m-1th internal iteration The solution.

[0069] Step 6.6: and Substitute In the corresponding and Then judge the internal iteration condition Is it true? If so, then As the External iteration time t n Solution For t n The internal iteration is over, and the coordinates of the next mobile antenna are traversed, and then the step 6.4 is returned to continue the execution. After the coordinates of all mobile antennas are traversed, the first External iterations The optimal solution Then execute step 6.7; if it is not true, set m=m+1, and then return to step 6.5 to continue iterating; where, for The nth element in , abs(·) is the absolute value function, ε1 represents the preset internal iteration judgment threshold, and in this embodiment, ε1=10 -5 , the “=” in m=m+1 is an assignment symbol.

[0070] Step 6.7: and Substitute In the corresponding and Then judge the external iteration condition Is it true? If so, then As the The optimal value of R at the external iteration final , the external iteration ends; if it does not hold, then let Then return to step 6.2 to continue iteration; where, hour For initialization solution hour Indicates External iterations ε2 represents the preset external iteration judgment threshold. In this embodiment, ε2=10 -5 , The "=" in is the assignment symbol. Here, Equivalent to Substitute into the convex optimization problem P2 obtained in step 4 and solve the obtained The solution.

[0071] The feasibility and effectiveness of the method of the present invention are further illustrated by the following simulation. Figure 2A performance curve comparison of the communication rate R of the information receiver obtained by the method of the present invention and the existing fixed antenna method as a function of the maximum transmission signal-to-noise ratio is given. From small to large, it varies from -5dB to 15dB. Figure 2 It can be seen that the communication rate R of both methods will increase with the maximum transmission signal-to-noise ratio This is because the larger the The easier it is to meet the constraint that the energy collected by the energy receiver is greater than the preset threshold, so that the transmission beam of the information transmitter is used more to improve the rate; at the same time, it can be seen that the communication rate R of the method of the present invention is always greater than that of the existing fixed antenna method, because the change of the position of the mobile antenna can bring higher degrees of freedom, thereby improving the rate. Therefore, the calculation performance of the method of the present invention is better than that of the existing fixed antenna method.

Claims

1. A method for simultaneous transmission of wireless information and energy based on a mobile antenna, characterized in that The following steps are involved: Step 1: In the wireless information and energy simultaneous transmission system, assume that there is an information transmitter equipped with N mobile antennas, an information receiver equipped with 1 fixed antenna, and an energy receiver equipped with 1 fixed antenna. The N mobile antennas equipped by the information transmitter are distributed in the area Ω of A×A, and the interval D between the mobile antennas is greater than or equal to 0.5λ. The fixed antennas equipped by the information receiver and the fixed antennas equipped by the energy receiver are located at the center of the area Ω of A×A. The information sent by the information transmitter is denoted as s, and the information received by the information receiver is denoted as The information received by the energy receiver is recorded as Wherein, N>1, A=4λ, λ represents the signal wavelength, the coordinates of the center position of the region Ω are set to (0, 0), the x-axis coordinate of the region Ω is from -A / 2 to A / 2, and the y-axis coordinate is also from -A / 2 to A / 2, Represents a vector consisting of the coordinates of the N mobile antennas equipped by the information transmitter in sequence, t n represents the coordinates of the nth mobile antenna equipped by the information transmitter, n=1,···,N,t n ∈Ω, represents the x-axis coordinate of the nth mobile antenna equipped by the information transmitter, represents the y-axis coordinate of the nth mobile antenna equipped by the information transmitter, [] T represents the matrix transpose operation, The channel coefficient representing the channel from the information transmitter to the information receiver, (·) H represents the conjugate transpose operation, The receiving response matrix representing the link from the information transmitter to the information receiver, The dimension is K I A column vector of all 1s, K I represents the number of receiving paths from the information transmitter to the information receiver, Σ I The path response matrix represents the link from the information transmitter to the information receiver, The transmission response matrix representing the link from the information transmitter to the information receiver, g I (t n ) represents the transmission response vector of the link from the nth mobile antenna equipped by the information transmitter to the information receiver, n=1,···,N, e is a natural constant, j is an imaginary unit, L I represents the number of transmission paths from the information transmitter to the information receiver, The first link from the information transmitter to the information receiver The transmission path is at t n The path difference between the location and the center of the region Ω, The first link from the information transmitter to the information receiver The elevation angle of the transmission path, The first link from the information transmitter to the information receiver The azimuth of the transmission path, v represents the transmission beam of the information transmitter, n I represents the noise of the information receiver, n I The variance of represents the channel coefficient of the channel from the information transmitter to the energy receiver, represents the receiving response matrix of the link from the information transmitter to the energy receiver, The dimension is K E A column vector of all 1s, K E represents the number of receiving paths from the information transmitter to the energy receiver, Σ E represents the path response matrix of the link from the information transmitter to the energy receiver, represents the transmission response matrix of the link from the information transmitter to the energy receiver, g E (t n ) represents the transmission response vector of the link from the nth mobile antenna equipped by the information transmitter to the energy receiver, n=1,···,N,L E represents the number of transmission paths of the link from the information transmitter to the energy receiver, The first link from the information transmitter to the energy receiver The transmission path is at t n The path difference between the location and the center of the region Ω, The first link from the information transmitter to the energy receiver The elevation angle of the transmission path, The first link from the information transmitter to the energy receiver The azimuth of the transmission path, n E represents the noise of the energy receiver; Step 2: Measure the communication rate R of the information receiver with the channel capacity. The performance of the energy receiver is measured by the amount of energy collected, expressed as ;in, τ represents the efficiency of energy collection, Tr(·) represents the trace of the matrix; Step 3: Based on step 2, construct an optimization problem to maximize the communication rate R of the information receiver under the constraint that the energy collected by the energy receiver is greater than the preset threshold, which is described as: Among them, t u represents the coordinates of the u-th mobile antenna equipped by the information transmitter, P max Indicates the maximum transmission power of the information transmitter, represents the preset threshold of energy collected by the energy receiver, rank(·) represents the rank operation of the matrix; Step 4: Given In the case of , the optimization problem constructed in step 3 is converted into a new optimization problem P1, which is described as: Then the constraints in the new optimization problem P1 are Remove it and transform the new optimization problem P1 into a convex optimization problem P2, which can be described as: Step 5: In the given and the coordinates of the nth mobile antenna t n The coordinates of all other mobile antennas except u ,u∈{1,···,N},n≠u, the optimization problem constructed in step 3 is converted into a new optimization problem P3, which is described as: Among them, f I (t n ) and f E (t n ) are all introduced intermediate quantities, Then, for the new optimization problem P3, q (t n ),q∈{I,E}at a feasible initial point Perform a first-order Taylor expansion at , and we get: in, represents f q (t n ),q∈{I,E}at a feasible initial point The first-order Taylor expansion at is the intermediate quantity introduced, To calculate the real part, g q (t n ) is g I (t n ) or g E (t n ), n=1,···,N,ηq is the introduced intermediate quantity, v(n) represents the nth element in v, v(u) represents the uth element in v, Will Substitution n=1,···,N, we get v(i) represents the i-th element in v, v(a) represents the a-th element in v, and are all feasible initial points. Substitution n=1,···,N, we get Will Substitution n=1,···,N, we get Again At a feasible starting point Perform a second-order Taylor expansion at , and we get: in, express At a feasible starting point The second-order Taylor expansion at Substitution Get express The gradient of | | is the modulus operator. Represents η q The elements, express Angle, for or Will Substitution Get Then, the constraint ||t in the new optimization problem P3 is n -t u ||2≤||t in D n -t u ||2 At a feasible initial point Perform a first-order Taylor expansion at , and we get: Finally, the new optimization problem P3 is transformed into a convex optimization problem P4, which is described as: Step 6: Use external iteration to solve the convex optimization problem P2 obtained in step 4, and obtain The optimal solution; in each external iteration process, for the coordinates of each mobile antenna, the convex optimization problem P4 obtained in step 5 is solved by internal iteration to obtain the solution of the coordinates of each mobile antenna at each internal iteration. When the solution of the coordinates at the internal iteration satisfies the internal iteration condition, the solution of the coordinates at each external iteration is obtained. The optimal solution of The optimal solution and The optimal value of R is obtained when the optimal solution meets the external iteration conditions.

2. A method for simultaneous wireless information and energy transmission based on a mobile antenna according to claim 1, characterized in that In step 1, Σ I is a diagonal matrix, the first element on the diagonal is a random variable with mean 0 and variance 0.5, and the remaining elements on the diagonal except the first element are random variables with mean 0 and variance A random variable Σ E is a diagonal matrix, the first element on the diagonal is a random variable with mean 0 and variance 0.5, and the remaining elements on the diagonal except the first element are random variables with mean 0 and variance A random variable.

3. A method for simultaneous wireless information and energy transmission based on a mobile antenna according to claim 1 or 2, characterized in that The specific process of step 6 is as follows: Step 6.1: Order represents the number of external iterations, The initial value of is 1; Step 6.2: In During the external iteration, Substitute into the convex optimization problem P2 obtained in step 4 and solve it using the interior point method to obtain External iterations Solution if Then As The optimal solution if Then execute the following process: 1) Perform eigenvalue decomposition and get Among them, each column vector of U is is an eigenvector of , Λ is a diagonal matrix, and its diagonal elements are eigenvalues; 2) randomly generate P eigenvalues ​​with mean 0 and variance I N The pth complex Gaussian vector is denoted by w p , then let Further order in, represents the square root of the matrix Λ, I N represents the N-order identity matrix, p=1,···,P,v p and are all intermediate quantities introduced; 3) Substitute them into the convex optimization problem P2 as candidate values, and take the candidate values ​​that both satisfy the constraints in the convex optimization problem P2 and maximize the objective function as the first External iterations The optimal solution in, hour For initialization solution hour Indicates External iterations The solution; Step 6.3: Traverse the coordinates of each mobile antenna equipped by the information transmitter; Step 6.4: Assume that the coordinate t of the nth mobile antenna is currently being traversed n ; Let m represent the number of internal iterations of step 5, and the initial value of m is 1; Step 6.5: During the mth internal iteration, after obtaining the External iterations The optimal solution Under the premise of Substitute u∈{1,···,N},n≠u into the convex optimization problem P4 obtained in step 5 and solve it using the interior point method to obtain the mth internal iteration time t n Solution in, for The u-th element in, when m=1 for When m≠1 Indicates the m-1th internal iteration The solution; Step 6.6: and Substitute In the corresponding and Then judge the internal iteration condition Is it true? If so, then As the External iteration time t n Solution For t n The internal iteration is over, and the coordinates of the next mobile antenna are traversed, and then the step 6.4 is returned to continue the execution. After the coordinates of all mobile antennas are traversed, the first External iterations The optimal solution Then execute step 6.7; if it is not true, set m=m+1, and then return to step 6.5 to continue iterating; where, for The nth element in , abs(·) is the absolute value function, ε1 represents the preset internal iteration judgment threshold, and "=" in m=m+1 is the assignment symbol; Step 6.7: and Substitute In the corresponding and Then judge the external iteration condition Is it true? If so, then As the The optimal value of R at the external iteration final , the external iteration ends; if it does not hold, then let Then return to step 6.2 to continue iteration; where, hour For initialization solution hour Indicates External iterations The solution, ε2 represents the preset external iteration judgment threshold, The "=" in is the assignment symbol.

4. A method for simultaneous wireless information and energy transmission based on a mobile antenna according to claim 3, characterized in that In step 6.2, The generation steps are as follows: the initialization value of the coordinates of the first mobile antenna equipped by the information transmitter Among them, rand(1,2) represents a row vector containing two random numbers between 0 and 1; the initial value of the coordinates of the second mobile antenna equipped by the information transmitter is And meet By analogy, the initialization value of the coordinates of the nth mobile antenna equipped by the information transmitter is And meet u'∈{1,···,n-1}, where represents the initialization value of the coordinates of the u'th mobile antenna equipped by the information transmitter; the initialization value of the coordinates of the Nth mobile antenna equipped by the information transmitter And meet u'∈{1,···,N-1}; in step 6.7, Equivalent to Substitute into the convex optimization problem P2 obtained in step 4 and solve the obtained The solution.

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