Communication method, communication device and computer readable storage medium

Abstract

The invention provides a communication method, a communication device and a computer readable storage medium. Determining a target position of the MA on the two communication devices, wherein the target position of the MA enables a first communication index between the two communication devices to meet a preset condition; and performing co-frequency co-time full duplex communication according to the target position of the MA. According to the scheme, the proper position is determined for the MA on the two pieces of communication equipment, so that the first communication index between the two pieces of communication equipment meets the preset condition, and the communication performance between the two pieces of communication equipment is improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a communication method, a communication device, and a computer-readable storage medium. Background Technology

[0002] In co-frequency co-time full-duplex (CCFD) communication systems, movable antennas (MAs) can be introduced to eliminate self-interference and improve the utilization of spatial degrees of freedom. How to improve the performance of the CCFD communication system after introducing MAs is a technical problem that needs to be solved. Summary of the Invention

[0003] This application provides a communication method, a communication device, and a computer-readable storage medium to improve the performance of a CCFD communication system after the introduction of MA.

[0004] In a first aspect, a communication method is provided, comprising: determining the target position of a MA on two communication devices, wherein the target position of the MA causes a first communication indicator between the two communication devices to meet a preset condition; and performing CCFD communication based on the target position of the MA.

[0005] As one possible implementation, determining the target location of the MA on two communication devices includes: determining second mapping relationship information based on first mapping relationship information, wherein the first mapping relationship information is used to indicate the mapping relationship between the channel coefficient and the location of the MA, and the second mapping relationship information is used to indicate the mapping relationship between the first communication index and the location of the MA; and determining the target location of the MA using an optimization algorithm based on the second mapping relationship information, with the first communication index satisfying a preset condition as the optimization objective.

[0006] As one possible implementation, the first communication indicator is related to the achievable rate of the two communication devices. The second mapping relationship information is determined based on the first mapping relationship information, including: determining the third mapping relationship information based on the first mapping relationship information, the third mapping relationship information being used to indicate the mapping relationship between the signal-to-interference-plus-noise ratio (SINR) and the position of the MA; and determining the second mapping relationship information based on the third mapping relationship information.

[0007] As one possible implementation, the third mapping information is used to indicate: Where q and p represent the first and second communication devices, respectively, and γ q h represents the SINR corresponding to the first communication device.pq (t p ,r q ) represents the channel coefficient between two terminal devices, h qq (t q ,r q ) represents the channel coefficient between the transmitting MA and the receiving MA of the first communication device, t q and r q P represents the positions of the transmitting MA and the receiving MA, respectively. t Indicates the transmission power of the second communication device. This represents the power of additive white Gaussian noise (AWGN).

[0008] As one possible implementation, the second mapping information is used to indicate: R q =log2(1+γ) q ); where R q This indicates the achievable speed of the first communication device.

[0009] As one possible implementation, the optimization algorithm is particle swarm optimization (PSO).

[0010] As one possible implementation, the positions of particles in the PSO algorithm satisfy: Where n represents the nth particle in the PSO algorithm, k represents the kth iteration of the PSO algorithm, and A and B represent two communication devices. This represents the position of the nth particle corresponding to the kth iteration. and This indicates the position of the transmitting MA of the two communication devices. and This indicates the position of the receiving MA of the two communication devices.

[0011] As one possible implementation, the velocity of particles in the PSO algorithm satisfies: Where n represents the nth particle in the PSO algorithm, and k represents the kth iteration of the PSO algorithm. This represents the velocity of the nth particle corresponding to the kth iteration. This represents the velocity of the nth particle corresponding to the (k-1)th iteration. Let represent the position of the nth particle corresponding to the (k-1)th iteration, ω represent the inertia weight, c1 and c2 represent the learning factors, and e1 and e2 represent random vectors. Let u represent the local optimal position of the nth particle. ＊This represents the global optimal position of the nth particle.

[0012] As one possible implementation, the channel coefficients satisfy: h pq (t p ,r q )=f(r q ) H Σ pq g(t p ); where q and p represent the first and second communication devices, respectively, and h pq (t p ,r q ) represents the channel coefficient, t p and r q ∑ represents the positions of the transmitting MA of the second communication device and the receiving MA of the first communication device, respectively. pq f(r) represents the channel response between the origin of the mobile area transmitting the MA and the origin of the mobile area receiving the MA. q ) represents r q The corresponding field response vector, g(t) p ) represents t p The corresponding field response vector.

[0013] As one possible implementation, f(r) q )satisfy: and / or g(t) p )satisfy: Where λ represents the wavelength of the signal. This indicates the number of receive paths within the receive area of ​​the receiving MA. to Indicates that the received MA is in The difference in propagation distance between each receiving path, This indicates the number of launch paths within the launch area of ​​the MA. to Indicates the launch of MA in The difference in propagation distance between the two transmission paths.

[0014] As one possible implementation, the constraints of the optimization algorithm include that the position of MA does not exceed the movement range defined by the movement area of ​​MA.

[0015] As one possible implementation, the first communication metric is the minimum achievable rate (MAR) between the two terminal devices, with preset conditions including maximizing the MAR.

[0016] In a second aspect, a communication device is provided, comprising: a determining module for determining the target position of a movable antenna MA on two communication devices, wherein the target position of the MA causes a first communication indicator between the two communication devices to meet a preset condition; and a communication module for performing CCFD communication based on the target position of the MA.

[0017] Thirdly, a communication device is provided, comprising: a memory for storing a program; and a processor for executing the program stored in the memory to perform the method described in the first aspect or any implementation thereof.

[0018] Fourthly, a computer-readable storage medium is provided, on which program code is stored for performing the method as described in the first aspect or any implementation thereof.

[0019] Fifthly, a computer program product is provided, comprising program code for performing the method as described in the first aspect or any implementation thereof.

[0020] In this embodiment, the target position of the MA on two communication devices is determined, and the target position of the MA causes the first communication indicator between the two communication devices to meet preset conditions; CCFD communication is performed based on the target position of the MA. This embodiment improves the communication performance between the two communication devices by determining a suitable position for the MA on the two communication devices, thereby ensuring that the first communication indicator between the two communication devices meets preset conditions. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the protection scope of this application.

[0022] Figure 1 This is a structural example diagram of a wireless communication system that can be applied to the embodiments of this application.

[0023] Figure 2 This is a structural example diagram of the CCFD system provided in the embodiments of this application.

[0024] Figure 3 This is a structural example diagram of a CCFD system incorporating MA, provided in an embodiment of this application.

[0025] Figure 4 This is a schematic flowchart of a communication method provided in one embodiment of this application.

[0026] Figure 5This is a schematic flowchart of a communication method provided in another embodiment of this application.

[0027] Figure 6 This is a schematic flowchart of a communication method provided in another embodiment of this application.

[0028] Figure 7 This is an example diagram of the transmission path and reception path provided in the embodiments of this application.

[0029] Figure 8 This is a schematic flowchart of a communication method provided in another embodiment of this application.

[0030] Figure 9 This is a schematic diagram of the simulation results of MAR provided in the embodiments of this application.

[0031] Figure 10 This is a schematic diagram of the structure of a communication device provided in one embodiment of this application.

[0032] Figure 11 This is a schematic diagram of the structure of a communication device provided in another embodiment of this application. Detailed Implementation

[0033] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained based on the embodiments of this application are within the scope of protection of this application.

[0034] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0035] It should be understood that the specific embodiments described below are merely illustrative of this application and are not intended to limit this application.

[0036] Figure 1This is a system architecture example diagram of a wireless communication system 10 applicable to embodiments of this application. The wireless communication system 10 may include a network device 101 and a terminal device 102. The network device 101 may be a device that communicates with the terminal device 102. The network device 101 can provide network coverage for a specific geographical area and can communicate with the terminal device 102 located within that coverage area. The terminal device 102 can access a network (such as a wireless network) through the network device 101. Optionally, the wireless communication system 101 may also include other network entities such as a network controller and a mobility management entity; this embodiment of the application does not limit this.

[0037] The aforementioned wireless communication system 10 can operate in time division duplex (TDD) mode, frequency division duplex (FDD) mode, CCFD mode, etc. When the wireless communication system 10 operates in CCFD mode, it can also be referred to as a CCFD communication system (or CCFD system). In a CCFD communication system, communication devices are allowed to use the same frequency resources (e.g., the same frequency point) to transmit and receive signals simultaneously (e.g., in the same time slot). CCFD mode breaks through the limitations of traditional TDD and FDD modes, and can greatly improve spectrum utilization efficiency.

[0038] The following is combined with Figure 2 An introduction to the CCFD system.

[0039] CCFD systems can have features such as Figure 2 The structure shown. Figure 2 The CCFD system shown includes two communication devices, namely communication device A and communication device B. One of communication device A and communication device B is... Figure 1 The network device shown is another one. Figure 1 The terminal device shown. Alternatively, both communication device A and communication device B can be... Figure 1 The terminal devices shown are communication devices A and B, each including at least one transmitting antenna and one receiving antenna.

[0040] Because CCFD systems allow simultaneous signal transmission and reception on the same frequency, self-interference (SI) occurs. For example, for communication device A, since it can transmit and receive signals simultaneously on the same frequency, a portion of the signal transmitted by its transmitting antenna will be received by its receiving antenna. This portion of the signal can be called the SI signal leaked from the transmitting antenna. Similarly, the receiving antenna of communication device B may also receive the SI signal leaked from its transmitting antenna. High-power SI signals leaked from the transmitting antenna can be eliminated in the antenna domain, analog domain, and digital domain. Antenna domain SI elimination involves taking measures at the physical level (antenna) to reduce the impact of the transmitted signal on the received signal. For example, SI can be reduced by designing special antenna structures or using physical isolation to reduce the coupling between the transmitting and receiving antennas of the same communication device (i.e., using antenna isolation). Analog domain SI elimination involves weakening or eliminating SI through analog circuits. Digital domain SI elimination involves eliminating or reducing SI through algorithms during the digital signal processing stage. For example, in the analog and digital domains, channel estimation can be performed and the SI signal can be reconstructed, thereby eliminating the SI signal in the received signal.

[0041] Traditional antenna domain SI cancellation typically relies on fixed-position antennas (FPAs). However, when environmental factors alter channel characteristics (spatial channel variations), FPAs cannot adapt to these variations by changing their spatial location, thus limiting the extensive utilization of spatial degrees of freedom (DoFs). To overcome this limitation, related technologies propose introducing MAs into CCFD systems. The position of the MA is changeable; it can be flexibly moved from one location to another in various ways to improve or worsen channel conditions.

[0042] This application does not limit the specific form of the antenna (MA). For example, the MA can be a microstrip antenna, a foldable antenna, a flexible antenna, a magnetic antenna, etc. The MA can be connected to the RF link via a flexible cable and mounted on a mechanical slide rail. The movement of the MA can be controlled in various ways. For example, the MA can be moved freely using a stepper motor. Alternatively, the movement of the MA can be controlled using a microelectromechanical system (MEMS). Microelectromechanical systems offer more precise control and are particularly suitable for controlling the movement of small MAs.

[0043] The following is combined with Figure 3 This section provides a detailed introduction to the CCFD system introduced by MA. Figure 3 The CCFD system with MA introduced shown can also be called an MA-assisted CCFD system.

[0044] Figure 3 The CCFD system shown includes two communication devices, namely terminal A and terminal B. Terminal A is equipped with a transmitting MA and a receiving MA. Terminal B is also equipped with a transmitting MA and a receiving MA. Figure 3 The four moving areas (MAs) shown can all move within their respective movement areas. The movement areas of the four MAs can be the same or different; this embodiment does not impose any limitation on this. For each MA, its movement area can be a two-dimensional region or a three-dimensional region. When the movement area is a two-dimensional region, the specific positions of the four MAs can be represented using Cartesian coordinates. The position of the transmitting MA of terminal A can be represented as... in, and Let x and y represent the x and y coordinates of the transmission MA of terminal A, respectively. This represents the movement area of ​​the transmitting MA of terminal A (i.e., the transmission area corresponding to terminal A). The position of the receiving MA of terminal A can be represented as... in, and These represent the x and y coordinates of the receiving MA of terminal A, respectively. This represents the moving area of ​​the receiving MA of terminal A (i.e., the receiving area corresponding to terminal A). Similarly, the position of the transmitting MA of terminal B can be represented as... in, This represents the movement area of ​​the transmitting MA of terminal B (i.e., the transmission area corresponding to terminal B). The position of the receiving MA of terminal B can be represented as... in, This represents the moving area of ​​the receiving MA of terminal B (i.e., the receiving area corresponding to terminal B). When terminal A acts as the transmitter, terminal B acts as the receiver. When terminal B acts as the receiver, terminal A acts as the transmitter. We can use p to represent the transmitter in terminal A and terminal B, and q to represent the receiver in terminal A and terminal B. That is, p and q belong to the set {A, B}, and p and q can be called the labels of the terminals. Based on the above understanding, to simplify the subsequent description, the position coordinates of the four MAs can be simplified as follows: and Among them, t p Indicates the position where MA is emitted, r q Indicates the location of the receiving MA. and These represent the x and y coordinates of the transmitted MA, respectively. and These represent the x and y coordinates of the received MA, respectively. This indicates the transmission area corresponding to terminal p. This indicates the receiving area corresponding to terminal q.

[0045] According to the above... Figure 2 As described above, the signal received by terminal q includes signals received from the transmitting antenna of terminal p, signals received from the transmitting antenna of terminal q itself, and spatial noise. Assuming that the channel state information (CSI) can be perfectly acquired by the receiving terminal q, terminal q can use this information for optimal signal processing to improve the quality of signal transmission. Under this assumption, the transmit power of terminal p can be expressed as P. t Then the signal received by terminal q can be represented as Among them, h pq (t p ,r q ) represents the channel coefficient between the transmit MA of terminal p and the receive MA of terminal q, s p H represents the signal transmitted by terminal p. qq (t q ,r q ) represents the channel coefficient between the transmitting MA of terminal q and the receiving MA of terminal q, n q Indicates power as Additive white Gaussian noise (AWGN). q It follows a mean of 0 and a variance of . The complex Gaussian distribution, i.e.

[0046] like Figure 3 As shown, terminal p can transmit signals through multiple transmission paths, and terminal q can receive signals through multiple reception paths. The number of transmission multipaths and the number of reception multipaths can be expressed as follows: and Can One of the launch paths is represented as: And One of the receiving paths is represented as:

[0047] exist Figure 3 In, ∑ AB This represents the channel response from the origin of the transmitting area of ​​terminal A to the origin of the receiving area of ​​terminal B, ∑ AA This represents the channel response from the origin of the transmitting area of ​​terminal A to the origin of the receiving area of ​​terminal A. Σ BA This represents the channel response from the origin of the transmitting area of ​​terminal B to the origin of the receiving area of ​​terminal A, ∑ BBThis represents the channel response from the origin of the transmitting area of ​​terminal B to the origin of the receiving area of ​​terminal B. The channel response can be used to describe the changes a signal undergoes as it travels through the physical channel in a wireless communication system. The channel response can include one or more of the following: amplitude response, phase response, frequency response, etc. The channel response can be characterized by channel coefficients.

[0048] Figure 3 The CCFD system shown includes a transmitting MA and a receiving MA in each terminal, but the embodiments of this application are not limited to this. The CCFD system with MA introduced in the embodiments of this application can also be a multiple-input multiple-output (MIMO) system. Figure 3 Terminal A and / or terminal B shown may further include multiple transmit MAs and / or multiple receive MAs. For example, in the CCFD system of this application embodiment, each terminal may further include M transmit MAs and N receive MAs, where M and N are both integers greater than 1. For a MIMO system including M transmit MAs and N receive MAs, the coordinates of the m-th transmit MA can be represented as t. m (1≤m≤M), the coordinates of the nth receiver MA are represented as r. n (1≤n≤N). The channel coefficients of a MIMI system are in matrix form, and therefore can be called the channel matrix. This channel matrix can be represented as: in Here Represents the set of complex numbers with N rows and M columns. Represents a set of real numbers in rows of M columns.

[0049] As mentioned above, in order to eliminate SI in CCFD systems and overcome the limitations of traditional FPA-based CCFD systems on the utilization of space DoFs, MA has been introduced into CCFD systems. However, how to further improve the performance of CCFD communication after introducing MA into the CCFD system is a technical problem that needs to be solved.

[0050] To address the aforementioned technical problems, this application proposes a communication method, which includes: determining the target position of a communication mode (MA) on two communication devices, wherein the target position of the MA causes a first communication indicator between the two communication devices to satisfy a preset condition (see...). Figure 4 Step S410 in the text); perform CCFD communication based on the target location of the MA (see...). Figure 4 (Step S420 in the process). Using this method, a suitable position can be determined for the MA on the communication device based on the first communication index, thereby improving the performance of CCFD communication between communication devices.

[0051] The following is combined with Figure 4 and Figure 7 The communication method provided in the embodiments of this application will be described in detail.

[0052] In step S410, the target position of MA on the two communication devices is determined, and the target position of MA makes the first communication index between the two communication devices meet the preset condition.

[0053] This application does not specifically limit the types of the two communication devices. Both communication devices can be the terminal devices mentioned above. Alternatively, one of the two communication devices can be a network device and the other a terminal device.

[0054] This application does not specifically limit the type of MA. For example, the MA can be the microstrip antenna, foldable antenna, flexible antenna, magnetic antenna, etc. mentioned above.

[0055] The aforementioned first communication indicator can be a parameter used to characterize the communication performance between two communication devices. The communication performance between the two communication devices changes with the position of the aforementioned MA. Therefore, when the position of the aforementioned MA changes, the value of the first communication indicator between the two communication devices also changes accordingly. When the MA is at the target position, the first communication indicator between the two communication devices meets a preset condition. This application does not specifically limit the first communication indicator. For example, the first communication indicator can be the throughput between the two communication devices. Another example is that the first communication indicator can be the MAR of the two communication devices. MAR typically refers to the minimum data transmission rate that can be guaranteed in a specific communication system or network environment. The preset condition can be: the first communication indicator reaches its maximum value, or the first communication indicator is greater than a certain value. Different first communication indicators have different preset conditions. For example, when the first communication indicator is MAR, the first preset condition can be that MAR reaches its maximum value, i.e., MAR is maximized.

[0056] In step S420, CCFD communication is performed based on the target location of MA.

[0057] For a detailed introduction to CCFD communication, please refer to the relevant sections above; it will not be repeated here. After determining the target position of the MAs, the MAs can be moved to their corresponding target positions, and CCFD communication can be performed at those positions. Since the target positions are determined based on the first communication index between the two communication devices, moving the MAs to their corresponding target positions for CCFD communication can improve the communication performance between the two devices.

[0058] There are multiple ways to determine the target position of MA on the two communication devices in step S410. Two possible implementation methods are described in detail below.

[0059] In some implementations, multiple first communication indicators corresponding to each candidate position (or candidate position set) in multiple candidate positions (or candidate position sets) of MA can be calculated by traversal. A first communication indicator that meets a first preset condition is selected from the multiple first communication indicators, and the candidate position (or candidate position set) corresponding to the selected first communication indicator is determined as the target candidate position.

[0060] In other implementations, optimization algorithms can be used to determine the target position of the aforementioned MA. The following section combines... Figure 5 A detailed introduction will be provided.

[0061] See Figure 5 Step S410, which determines the target location of the MA on the two communication devices, may include the following steps S510 and S520.

[0062] In step S510, the second mapping relationship information is determined based on the first mapping relationship information.

[0063] The first mapping information mentioned here is used to indicate the mapping relationship between the channel coefficients and the position of the MA. Considering that when the position of the MA changes, it will directly cause changes in the channel characteristics, and thus cause changes in the channel coefficients, the first mapping information can be established first. This first mapping information can be a function of the channel coefficients relative to the position of the MA.

[0064] The second mapping information mentioned here is used to indicate the mapping relationship between the first communication indicator and the position of the MA. This second mapping information can be a function of the position of the first communication indicator relative to the MA.

[0065] For example, two communication devices are each equipped with a transmitting MA and a receiving MA. The channel coefficient can be characterized as a function of the position coordinates of the transmitting MA and the receiving MA, i.e., h pq (t p ,r q ), where p represents the second communication device (transmitter) and q represents the first communication device (receiver). This function h pq (t p ,r q This refers to the mapping relationship between the channel coefficients and the position of MA. Determine h. pq (t p ,r q After that, you can determine the h pq (t p ,r q Determine the mapping relationship between the first communication indicator and the position of MA.

[0066] In step S520, based on the second mapping relationship information and with the first communication index meeting the preset conditions as the optimization objective, the target position of MA is determined using an optimization algorithm.

[0067] The optimization algorithms mentioned here could be, for example, particle swarm optimization (PSO), alternating position optimization (APO), or other optimization algorithms. The PSO algorithm could be, for example, the standard PSO algorithm. The optimization objective can be determined based on a first communication metric and preset conditions. For example, when the first communication metric is the maximum range (MAR) of two communication devices, the optimization objective could be to maximize the MAR. As a more concrete example, suppose the first communication device is equipped with one transmitting MA and one receiving MA, and the second communication device is equipped with one transmitting MA and one receiving MA. The first communication metric is the MAR, and the preset condition is to maximize the MAR. Then, based on the mapping relationship between the positions (set of positions) of the four MAs and the MAR, with maximizing the MAR as the optimization objective, the target positions of the four MAs can be determined using the standard PSO algorithm.

[0068] There are multiple ways to implement step S510. The following will combine... Figure 6 An example will be given to illustrate how step S510 is implemented.

[0069] See Figure 6 When the first communication indicator is related to the achievable rate of the two communication devices, determining the second mapping relationship information based on the first mapping relationship information may include the following steps S610 and S620.

[0070] In step S610, based on the first mapping relationship information, the third mapping relationship information is determined. The third mapping relationship information is used to indicate the mapping relationship between the positions of SINR and MA.

[0071] When the first communication metric is related to the achievable rates of two communication devices, a mapping relationship between the channel coefficient and the achievable rate can be established based on the mapping relationship between this intermediate parameter and the channel coefficient, as well as the mapping relationship between this intermediate parameter and the achievable rate. Considering that SINR is an important indicator for evaluating communication performance, SINR can be used as the aforementioned intermediate parameter. First, based on the mapping relationship between the location of the MA and the channel coefficient (indicated by the first mapping relationship information), the mapping relationship between SINR and the location of the MA (indicated by the third mapping relationship information) is determined.

[0072] In step S620, the second mapping relationship information is determined based on the third mapping relationship information.

[0073] After obtaining the mapping relationship between SINR and MA location in step S610 (indicated by the third mapping relationship information), the second mapping relationship between the achievable rate of the two communication devices and MA location can be determined based on the third mapping relationship information (indicated by the second mapping relationship information).

[0074] Since the third mapping relationship information (used to indicate the mapping relationship between SINR and MA positions) in step S610 is obtained based on the first mapping relationship information (used to indicate the mapping relationship between MA positions and channel coefficients), the third mapping relationship information is used to indicate the relationship between SINR and channel coefficients, that is:

[0075]

[0076] Where q and p represent the first communication device and the second communication device, respectively, γ q h represents the SINR corresponding to the first communication device. pq (t p ,r q ) represents the channel coefficient between two communication devices, h qq (t q ,r q ) represents the channel coefficient between the transmitting MA and the receiving MA of the first communication device, t q And represents r q P represents the positions of the transmitting MA and the receiving MA, respectively. t Indicates the transmission power of the second communication device. This indicates the power of the AWGN. Regarding P... t and For a detailed introduction, please refer to the relevant descriptions in the previous section, which will not be repeated here.

[0077] As mentioned in step S610, the second mapping relationship information is used to indicate the relationship between the reachable rates of the two communication devices and the location of MA. Since the reachable rate is generally relative to the receiving device q, the reachable rate here can be expressed as R. q Furthermore, since the second mapping relationship information in step S620 is determined based on the third mapping relationship information, and the third mapping relationship information is used to indicate the mapping relationship between the positions of SINR and MA, the mapping relationship indicated by the second mapping relationship information can be expressed as the relationship between the achievable rate and SINR, that is:

[0078] R q =log2(1+γ) q (2)

[0079] Among them, R q γ represents the achievable rate of the first communication device. qSINR can be calculated using the above formula (1).

[0080] Step S520 mentions that the position of MA can be determined using the PSO algorithm or other optimization algorithms. The PSO algorithm mentioned here is a heuristic global optimization method that simulates the foraging behavior of a flock of birds, searching for optimal solutions by having a group of simple particles move through the search space. Each particle represents a potential solution and has its own position and velocity. The particles explore the solution space by updating their positions and are guided in the search direction by tracking individual optimal solutions and the global optimal solution. In the PSO algorithm, the number of particles is assumed to be N, and the number of iterations is K. At the k-th iteration, the positions of the n particles can be represented as a matrix, i.e. Each element in the matrix This represents the position of the nth particle out of N particles. When a particle moves in two-dimensional space, the position of each instance can be represented by two elements: the horizontal coordinate and the vertical coordinate. Therefore, the position matrix above is an 8-row, N-column set of real numbers. In the k-th iteration, the velocities of the N particles can also be represented as a matrix, i.e. Each element in the matrix This represents the velocity of the nth particle out of N particles. Similarly, when a particle moves in two-dimensional space, the above velocity matrix is ​​also an 8-row, N-column set of real numbers, i.e. In the above description, 1≤n≤N and 1≤k≤K.

[0081] Taking the example that both the first and second communication devices are equipped with one transmitting MA and one receiving MA, when the standard PSO algorithm is used to determine the positions of the four MAs, the position of the particle in the standard PSO algorithm represents the set of positions of the two transmitting MAs and the two receiving MAs. That is, the position of the nth particle in the standard PSO algorithm can be represented as a vector:

[0082]

[0083] Where n represents the nth particle in the PSO algorithm, k represents the kth iteration of the PSO algorithm, and A and B represent two communication devices. This represents the position of the nth particle corresponding to the kth iteration. and This indicates the position of the transmitting MA of the two communication devices. and This indicates the position of the receiving MA of the two communication devices.

[0084] When the position of MA is determined using the PSO algorithm, the velocities of the particles in the PSO algorithm satisfy:

[0085]

[0086] Where n represents the nth particle in the PSO algorithm, and k represents the kth iteration of the PSO algorithm. This represents the velocity of the nth particle corresponding to the kth iteration. This represents the velocity of the nth particle corresponding to the (k-1)th iteration. Let represent the position of the nth particle corresponding to the (k-1)th iteration, ω represent the inertia weight, c1 and c2 represent the learning factors, and e1 and e2 represent random vectors. Let u represent the local optimal position of the nth particle. ＊ This represents the global optimal position of the nth particle.

[0087] The aforementioned inertial weight ω adjusts the previous velocity For subsequent speed The value of ω plays a crucial role in determining the tendency of particles to maintain their original direction of motion. ω can be a fixed value throughout the PSO search process. Alternatively, the value of ω can vary dynamically throughout the PSO search process. To achieve a balance between the speed and accuracy of the PSO search, ω can be set to gradually decrease as the number of iterations k increases. For example, ω can be set as a linearly decreasing function of the number of iterations k, with a value ranging from [ω...]. min ω max The calculation formula is:

[0088] Learning factors c1 and c2 serve as step sizes, guiding each particle toward its local optimal position vector. and the global optimal position vector u ＊ The different values ​​of learning factors c1 and c2 lead to different search behaviors, thus affecting the convergence speed and quality of the algorithm. Therefore, the convergence speed of the PSO search process can be adjusted by changing the values ​​of c1 and c2.

[0089] In random vectors e1 and e2, each element is a random number, used to increase the randomness of the search process and reduce the risk of obtaining an unwanted local optimum. The random numbers can vary within the range [0, 1]. That is, in each iteration, the value of each element in random vectors e1 and e2 is randomly generated.

[0090] In each iteration of the PSO algorithm, the fitness function helps determine the local and global optimal position vectors. That is, in each iteration of the PSO algorithm, the optimal solution is tracked by continuously updating the individual best position and the group's best position for each particle. It is assumed that the optimal position vector corresponds to the maximum fitness value. For example, when determining the target positions of the four MAs for terminals A and B with the optimization objective of maximizing MAR, the fitness function of each particle can be defined as... in, and The positions of MA are respectively represented by The achievable rates of terminals A and B are specified. Typically, after k iterations, the approximate optimal positions u of the four MAs can be obtained. ＊ .

[0091] Step S510 mentions that the first mapping relationship information is used to indicate the channel coefficient h. pq (t p r q The mapping relationship between the position of the signal and the position of the channel coefficient. Here, the channel coefficient can be a complex number, representing the amplitude attenuation and phase change of the signal after passing through the channel. In multipath propagation, each path has its corresponding channel coefficient.

[0092] A field response channel model is a mathematical model used to describe the characteristics of a wireless channel. A field response channel model typically includes multiple paths, each corresponding to a channel coefficient. In single-path propagation, there is only one obvious propagation path, and the channel coefficient directly describes the characteristics of that path. In multipath propagation, the signal reaches the receiving antenna through multiple paths, each with its own channel coefficient. The field response channel model needs to consider the channel coefficients of all paths and combine them to form the overall effect.

[0093] To calculate the channel coefficients, a suitable field response channel model can be selected, and the channel coefficients for each path can be calculated based on the selected model. Then, the channel coefficients of all paths are summed to obtain the total field response (channel coefficients). The total field response (channel coefficients) can be obtained by calculating the channel coefficients of each path and combining them with the phase difference.

[0094] Therefore, the channel coefficients can be expressed as:

[0095] h pq (t p ,r q )=f(r q ) H ∑ pq g(t p (5)

[0096] Where q and p represent the first communication device and the second communication device, respectively, and h pq (t p ,r q ) represents the channel coefficient, t p and r q Σ represents the positions of the transmitting MA and receiving MA of the first communication device, respectively. pq f(r) represents the channel response between the origin of the mobile area transmitting the MA and the origin of the mobile area receiving the MA. q ) represents r q The corresponding field response vector, g(t) p ) represents t p The corresponding field response vector.

[0097] In equation (5) above, Σ pq belong OK The set of complex numbers in a column, i.e. in This indicates the number of receive paths within the receive area of ​​the receiving MA. This represents the number of transmission paths within the transmission area of ​​the transmitting MA. When p = q, the channel coefficient h... pq This can be interpreted as an SI channel. When p≠q, the channel coefficient h pq This can be interpreted as a useful signal channel.

[0098] From equation (5) above, it can be seen that the channel coefficient h pq With r q The corresponding field response vector f(r) q ) and t p The corresponding field response vector g(t) p (See below for details.) Therefore, in order to determine the channel coefficient h... pq We can first determine f(r) q ) and g(t p Then according to f(r) q ) and g(t p Determine the channel coefficient h pq .

[0099] In multipath propagation, different characteristics of the propagation environment, such as near-field or far-field conditions, significantly affect the field response vector. To simplify calculations, we can assume that the far-field condition is met, i.e., the distance between the transmitting MA and the receiving MA is sufficiently large. Under the far-field condition, for a given position t of the transmitting MA... p and the position r of receiving MA q The field response vector is mainly determined by the propagation path length.

[0100] Therefore, in equation (5) under far-field conditions, r qThe corresponding field response vector f(r) q This can be represented as:

[0101]

[0102] In equation (5), t p The corresponding field response vector g(t) p This can be represented as:

[0103]

[0104] Where λ represents the wavelength of the signal. This indicates the number of receive paths within the receive area of ​​the receiving MA. to Indicates that the received MA is in The difference in propagation distance between each receiving path, This indicates the number of launch paths within the launch area of ​​the MA. to Indicates the launch of MA in The difference in propagation distance between the two transmission paths.

[0105] As can be seen from equations (6) and (7) above, r q The corresponding field response vector f(r) q ) and received MA in Difference in propagation distance between each receiving path to Related to, t p The corresponding field response vector g(t) p ) and the launch MA in The difference in propagation distance between each launch path to This is relevant. Therefore, the propagation distance difference of each receiving path and the propagation distance difference of each transmitting path can be calculated, and then the aforementioned r can be determined based on the calculated propagation distance difference. q The corresponding field response vector f(r) q ) and t p The corresponding field response vector g(t) p ).

[0106] Can emit MA One of the launch paths is represented as l t ,in Similarly, the receiving MA can be One of the receiving paths is represented as l r ,in To simplify the calculation of each launch path l t Difference in propagation distance And each receiving path l r Difference in propagation distance This can be calculated using a quasi-static block fading channel. In a quasi-static block fading channel, for a specific fading block (i.e., a time interval in the signal transmission process), the multipath channel components at any location within the transmission area (e.g., transmission path l) are calculated. t All are fixed, and the multipath channel components (e.g., the receiving path l) at any location within the receiving area are also fixed. r It is also fixed. Below, we will combine... Figure 3 Detailed introduction to the difference in propagation distance and The calculation.

[0107] exist Figure 3 middle, Indicates the launch path l t The pitch angles of the departure angles (AoDs). This represents the polarization angle of the AoDs. Compared to the origin coordinates, the l-th polarization angle of the emitted MA is... t The propagation distance difference of each transmission path can be expressed as

[0108] Similarly, Indicates receiving path l r The pitch angles of arrival (AoAs) This represents the polarization angle of AoAs. Compared to the origin coordinates, the l-th polarization angle of the receiving MA is... r The propagation distance difference of each receiving path can be expressed as:

[0109] Step S520 mentions that the target position of MA can be determined using an optimization algorithm.

[0110] When using optimization algorithms to determine the target position of the moving average (MA), constraints can be set for the MA's position, or no constraints can be set. If constraints are set, they can be based on the MA's movement area. For example, the constraint of the optimization algorithm can be set to ensure that the MA's position does not exceed the movement range defined by the MA's movement area. For example, with the optimization objective of maximizing the MAR of terminals A and B, and the movement area of ​​the MA as the constraint, when using optimization algorithms to solve for the positions of the four MAs of terminals A and B, the optimization problem can be formulated as follows: The constraints are The moving area of ​​the transmitting MA and the moving area of ​​the receiving MA can be the same or different. The moving area can be a three-dimensional area or a two-dimensional area. As a concrete example, the moving area of ​​the transmitting MA can be... Both the moving area of ​​the receiving MA and the moving area of ​​the receiving MA are set as squares of size D×D centered at the origin. Then, when using the PSO algorithm to determine the target position of the MA, the position coordinates of the transmitting MA are... and the location coordinates of the receiving MA All are confined within the given square region. The position of the nth particle corresponding to the kth iteration. It can be updated to in, This represents the position of the nth particle corresponding to the (k-1)th iteration. This represents the velocity of the nth particle corresponding to the kth iteration. {a} is a function that projects each component of vector a to its corresponding maximum or minimum value. Therefore, the above formula It can be transformed into This formula shows that, based on the position of the nth particle corresponding to k-1 iterations... And the velocity of the nth particle corresponding to the kth iteration. The position of the nth particle corresponding to the kth iteration is obtained. When, if the position of the nth particle corresponding to the kth iteration... When located within a square region of size D×D, the calculated value will be... As like When located outside a square region of size D×D, the edge position of the square region is taken as...

[0111] The embodiments of this application are described in more detail below with reference to more specific examples. In the examples below, both the first communication device and the second communication device are terminal devices (also referred to as communication terminals or terminals), each terminal device is equipped with a transmitting MA and a receiving MA, and both the transmitting MA and the receiving MA are microstrip antennas. The first communication metric is the achievable rate of the two terminal devices, with the preset condition being the maximization of the MAR (Maximum Averaging Range). It should be noted that this example is only to help those skilled in the art understand the embodiments of this application, and is not intended to limit the embodiments of this application to the specific values ​​or specific scenarios in the example. Those skilled in the art can obviously make various equivalent modifications or changes based on the examples given below, and such modifications or changes also fall within the scope of the embodiments of this application.

[0112] like Figure 8 The diagram illustrates a flowchart of a communication method according to an embodiment of this application. In the following example, the communication method includes steps S810 to S890.

[0113] In step S810, a CCFD communication model is established.

[0114] In step S810, establish as follows Figure 3 The CCFD communication model shown is illustrated. This model includes terminal A and terminal B, each equipped with a transmitting MA and a receiving MA. All four MAs shown can move within a square area of ​​size D×D. The positions of the four MAs are represented using Cartesian coordinates. That is, the position of the transmitting MA is represented as... The location of the received MA is represented as in It is the transmission area corresponding to terminal p. This refers to the receiving area corresponding to terminal q. p and q belong to the set {A, B}, and p and q serve as labels for the terminal, which will be used in subsequent steps.

[0115] In step S820, the propagation distance difference is calculated.

[0116] In step S820, the transmit path is calculated by analyzing a specific fading block in the quasi-static block fading channel model. The difference in propagation distance and the receiving path The difference in propagation distance.

[0117] like Figure 7 As shown, the launch path l t The difference in propagation distance can be expressed as in Indicates the pitch angle of AoDs. Indicates the polarization angle of AoDs. Receiver path l r The difference in propagation distance can be expressed as in, This represents the pitch angle of AoAs. This represents the polarization angle of AoAs.

[0118] In step S830, the field response vector is calculated.

[0119] After obtaining the propagation distance difference in step S820, the position t of the transmitting MA can be calculated based on the propagation distance difference. p The field response vector at position r and the received MA at position r qThe field response vector at point A. To simplify the calculation, it is assumed that the distance between terminal A and terminal B is large enough to satisfy the far-field condition. Under the far-field condition, the variations in AoDs, AoAs, and amplitude of multiple channel paths can be ignored, and only the phase variation (phase difference) is considered. The phase difference can be expressed as... Where ρ represents the propagation distance difference, and λ is the wavelength. The transmitter MA is at position t. p The field response vector at point can be expressed as Receive MA at position r q The field response vector at point can be expressed as

[0120] In step S840, the channel coefficients are calculated.

[0121] In step S830, the emission MA is obtained at position t. p The field response vector at position r and the received MA at position r q After obtaining the field response vector, the channel coefficients between the transmitting MA and the receiving MA can be calculated based on the field response vector. The channel coefficients between the transmitting MA and the receiving MA can be expressed as: h pq (t p ,r q )=f(r q ) H ∑ pq g(t p ),in This is the channel response from the origin of the transmitting region to the origin of the receiving region. When q = q, the channel coefficient h pq This can be interpreted as the channel coefficient of the SI channel. When p≠q, the channel coefficient h pq It can be interpreted as the channel coefficient of the useful signal.

[0122] In step S850, SINR is calculated.

[0123] In step S840, the channel coefficient h between the transmitting MA and the receiving MA is calculated. pq Then, based on the channel coefficient h pq The SINR for terminal q is calculated. The SINR for terminal q can be expressed as:

[0124] Step S860: Calculate the achievable rate.

[0125] After calculating the SINR of terminal q in step S850, the reachable rate of terminal q can be calculated based on the SINR. The reachable rate of terminal q can be expressed as: R q =log2(1+γ) q ).

[0126] In step S870, an optimization problem is established to maximize the terminal MAR.

[0127] In step S860, the achievable rate R of terminal q is calculated. q Then, it can be based on the achievable rate R of terminal q. q Establish an optimization problem. To ensure fairness among terminals, the terminal's MAR is maximized by jointly optimizing the positions of the four MAs. Therefore, the optimization problem is described as follows: Due to the position t of the MA launch p Confined to the launch area The position r of receiving MA q Limited to receiving area Therefore, the constraints of this optimization problem are: The constraints indicate that the range of movement of the transmitting MA is limited to a specific transmitting area, and the range of movement of the receiving MA is limited to a specific receiving area.

[0128] In step S880, the optimal positions of the four MAs are determined based on the standard PSO algorithm.

[0129] After establishing the optimization problem in step S870, the standard PSO algorithm is used to solve it, that is, to find the optimal positions of the four MAs. When using the standard PSO algorithm, the number of particles is represented by N, and the number of iterations is represented by K.

[0130] In the standard PSO algorithm, at the k-th (1≤k≤K) iteration, the particle position is represented as a matrix. The position of the nth particle (1≤n≤N) is represented by a vector. in and Let these represent the coordinates of the transmitting MA and the receiving MA, respectively. Due to the existence of constraints, and It is confined to a given area. This is because the model established in step S810 already includes the emission area. and receiving All were set to square regions of size D×D. Therefore, the vector Updated to in It is a function that projects each component of vector a to its corresponding maximum or minimum value, i.e.

[0131] In the standard PSO algorithm, the formula for calculating the velocity vector of the nth particle in the kth iteration is: Here, the inertial weight ω adjusts the previous velocity. For subsequent speed The learning factors c1 and c2, acting as step sizes, play a crucial role in influencing the movement of each particle towards its local optimal position vector. and the global optimal position vector u ＊ Closer. Furthermore, random vectors. Each element is a uniformly random number in the range [0,1], used to increase the randomness of the search process and reduce the risk of obtaining unwanted local optima. To achieve a balance between the speed and accuracy of the PSO search, ω is described as a linearly decreasing function of the number of iterations k, ranging from [ω...]. min ω max The calculation formula is:

[0132] In each iteration, the fitness function is used to determine the optimal position vector locally and globally. It is assumed that the optimal position vector corresponds to the maximum fitness value. To maximize the terminal MAR, the fitness function for each particle is defined as follows: in It is at the MA position by The achievable rate of the terminal is specified. Typically, after k iterations, the approximate optimal position u of the four moving averages can be obtained. ＊ .

[0133] In step S890, the optimal position obtained based on the PSO algorithm is verified using Matlab numerical calculation software.

[0134] In step S880, after solving for the approximate optimal positions of the four MAs using the standard PSO algorithm, the solved approximate optimal positions are verified using Matlab numerical calculation software. The following section combines... Figure 9 Please provide a detailed explanation.

[0135] like Figure 9 As shown, the scheme proposed in this application embodiment is called MA-CCFD-PSO, which represents a MA-assisted CCFD scheme using the PSO method. The naming rules for other schemes are similar. Figure 9 The performance of three schemes—MA, FPA, and antenna selection (AS)—was compared, and the performance of the same scheme in CCFD mode and HD mode was also compared. In the AS scheme, the antenna array... The antennas are deployed at intervals, and the optimal antenna is selected using the APO algorithm. As shown in the figure, in HD mode, the achievable rate is penalized due to the halved communication time (i.e., the actual achievable rate is less than the theoretical achievable rate). The expression for the achievable rate in HD mode is: Where p≠q. Furthermore, the performance of the proposed PSO method compared to the traditional APO method was evaluated. In the APO method, the moving region is divided into multiple regions of size... The grid allows for alternating searches of each MA's location while other MA positions remain fixed. In the above scheme, the antenna's movement range cannot exceed a D×D square area.

[0136] Figure 9 The diagram illustrates how MAR varies with the size D of the mobile area. The results show that for the MA-assisted scheme, MAR increases continuously as the mobile area expands. Conversely, in the AS-assisted scheme, the improvement in MAR is only significant when the number of deployed antennas increases. See also... Figure 9 The curve of AS-CCFD, when D is An integer multiple of this indicates an increase in antenna size. This is because MA (Multi-Auxiliary) can more fully utilize the spatial variations of the wireless channel in continuous areas. Compared to FPA-assisted schemes, MA-assisted and AS-assisted schemes exhibit higher performance. Furthermore, Figure 9 The paper also compares the advantages and disadvantages of the PSO and APO methods under MA-assisted schemes. By comparing the curves of MA-CCFD-PSO and MA-CCFD-APO, as well as the curves of MA-HD-PSO and MA-HD-APO, it can be seen that the PSO method is superior to the APO method, especially in CCFD mode when D is less than λ.

[0137] The above text combined Figures 4 to 9 This application describes in detail embodiments of the communication method provided. The apparatus embodiments of this application are described in detail below. It should be understood that the descriptions of the apparatus embodiments correspond to the descriptions of the method embodiments. Therefore, any parts not described in detail can be referred to the foregoing descriptions of the method embodiments.

[0138] This application embodiment also provides a communication device 100, which is used to perform the communication method mentioned above. Figure 10 A schematic diagram of the structure of the communication device 100 provided in an embodiment of this application is shown. Figure 10 As shown, the communication device 100 includes a determination module 1010 and a communication module 1020.

[0139] The determination module 1010 is used to determine the target position of the movable antenna MA on the two communication devices, and the target position of the MA makes the first communication index between the two communication devices meet the preset conditions.

[0140] The communication module 1020 is used for CCFD communication based on the target position of the MA.

[0141] This application embodiment also provides a communication device 110, which is used to perform the communication method mentioned above. Figure 11 A schematic diagram of the structure of the communication device 110 provided in an embodiment of this application is shown. Figure 11 As shown, the communication device 110 includes a memory 1110 and a processor 1120.

[0142] The memory 1110 is used to execute the program stored in the memory.

[0143] Processor 1120 is configured to execute a program stored in the memory to perform the communication method in any of the preceding embodiments.

[0144] This application also provides a computer-readable storage medium. The computer-readable storage medium stores program code that can be used to execute the communication methods in any of the preceding embodiments.

[0145] This application also provides a computer program product. This computer program product includes program code for performing the communication methods described in any of the preceding embodiments.

[0146] It should be understood that, in the embodiments of this application, determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0147] It should be understood that in the embodiments of this application, "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0148] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0149] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0151] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0152] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0153] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can read or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs, DVDs) or semiconductor media (e.g., solid-state disks, SSDs) etc.

[0154] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A communication method characterized by comprising: The method comprises: determining a target position of a movable antenna MA on two communication devices, the target position of the MA being such that a first communication index between the two communication devices meets a preset condition; performing a same-frequency simultaneous full-duplex CCFD communication according to the target position of the MA.

2. The method of claim 1, wherein, The determining of the target position of the MA on the two communication devices comprises: determining second mapping relationship information according to first mapping relationship information, wherein the first mapping relationship information is used to indicate a mapping relationship between a channel coefficient and a position of the MA, and the second mapping relationship information is used to indicate a mapping relationship between the first communication index and the position of the MA; determining the target position of the MA by using an optimization algorithm with the first communication index meeting the preset condition as an optimization target according to the second mapping relationship information.

3. The method of claim 2, wherein, The first communication index is related to an achievable rate of the two communication devices, and the determining of the second mapping relationship information according to the first mapping relationship information comprises: determining third mapping relationship information according to the first mapping relationship information, wherein the third mapping relationship information is used to indicate a mapping relationship between a signal-to-interference-plus-noise ratio and the position of the MA; determining the second mapping relationship information according to the third mapping relationship information.

4. The method of claim 3, wherein, The third mapping relationship information is used to indicate that: wherein q and p represent a first communication device and a second communication device in the two communication devices respectively, γ q represents a signal-to-interference-and-noise ratio SINR corresponding to the first communication device, h pq (t p , r q ) represents a channel coefficient between the two terminal devices, h qq (t q , r q ) represents a channel coefficient between a transmit MA and a receive MA of the first communication device, t q and r q represent positions of the transmit MA and the receive MA respectively, P t represents a transmit power of the second communication device, represents a power of an additive white Gaussian noise AWGN.

5. The method of claim 4, wherein, The second mapping relationship information is used to indicate that R q = log2(1+ γ q ), wherein R q represents the reachable rate of the first communication device.

6. The method of claim 2, wherein, The optimization algorithm is a particle swarm optimization PSO algorithm.

7. The method of claim 6, wherein, A position of a particle in the PSO algorithm meets that: wherein n denotes the n-th particle of the PSO algorithm, k denotes the k-th iteration of the PSO algorithm, A and B denote the two communication devices, denotes the position of the n-th particle of the k-th iteration, and denotes the position of the transmitting MA of the two communication devices, and denotes the position of the receiving MA of the two communication devices.

8. The method according to claim 6 or 7, characterized in that, A speed of the particle in the PSO algorithm meets that: wherein n represents the nth particle in the PSO algorithm, k represents the kth iteration of the PSO algorithm, represents the velocity of the nth particle corresponding to the kth iteration, represents the velocity of the nth particle corresponding to the k-1th iteration, represents the position of the nth particle corresponding to the k-1th iteration, ω represents an inertia weight, c1 and c2 represent learning factors, and e1 and e2 represent random vectors, represents the local optimal position of the nth particle, u ＊ represents the global optimal position of the nth particle.

9. The method of claim 2, wherein, The channel coefficient meets that: h pq (t p ,r q )=f(r q ) H ∑ pq g(t p ); where q and p represent a first communication device and a second communication device in the two communication devices respectively, h pq (t p , r q ) represents the channel coefficient, t p and r q represent positions of a transmitting MA of the second communication device and a receiving MA of the first communication device respectively, ∑ pq represents a channel response between an origin of a moving area of the transmitting MA and an origin of a moving area of the receiving MA, f(r q ) represents a corresponding field response vector of r q , and g(t p ) represents a corresponding field response vector of t p .

10. The method of claim 9, wherein: f(rq) satisfies: and / or g(t p ) satisfies: Where λ represents the wavelength of the signal. This indicates the number of receiving paths within the receiving area of ​​the receiving MA. to Indicates that the received MA is in The difference in propagation distance between each receiving path, This indicates the number of transmission paths within the transmission area of ​​the transmitting MA. to Indicates that the transmitting MA is in The difference in propagation distance between the two transmission paths.

11. The method of claim 2, wherein, a constraint condition of the optimization algorithm comprises that the position of the MA does not exceed a movement range defined by a movement area of the MA.

12. The method of claim 1, wherein, The first communication index is a minimum achievable rate MAR of the two terminal devices, and the preset condition comprises that the MAR is maximized.

13. A communications device, characterized by The method comprises: a determining module configured to determine a target position of a movable antenna MA on two communication devices, the target position of the MA being such that a first communication index between the two communication devices meets a preset condition; a communication module configured to perform a same-frequency simultaneous full-duplex CCFD communication according to the target position of the MA.

14. A communications device, characterized by The method comprises: a memory configured to store a program; a processor configured to execute the program stored in the memory to perform the method of any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that, The computer readable storage medium has program code stored thereon for performing the method of any one of claims 1 to 12.

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