Cross-type movable antenna array, communication system, communication parameter optimization method and related equipment

Abstract

The embodiment of the invention provides a cross-type movable antenna array, a communication system, a communication parameter optimization method and related equipment. The cross-type movable antenna array comprises a plurality of mutually parallel first sliding rails, a plurality of mutually parallel second sliding rails, at least one antenna unit and driving control equipment, the first sliding track and the second sliding track intersect to form a two-dimensional plane grid structure, and an antenna unit is arranged on the intersection point of the first sliding track and the second sliding track; when the driving control device receives the driving request of the target position, the driving control device is used for controlling the first sliding track and / or the second sliding track to slide and driving the plurality of antenna units to move to the target position, so that the hardware cost, the energy consumption and the maintenance difficulty of the movable antenna array are greatly reduced.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a cross-type movable antenna array, a communication system, a communication parameter optimization method and related equipment. Background Art

[0002] With the rapid development of wireless communication technology, users have an increasing demand for communication quality, data transmission rate and network capacity. Traditional fixed-position antenna systems cannot flexibly adapt to dynamically changing wireless channel environments due to their fixed antenna positions, resulting in limited communication performance. Especially in multi-user communication scenarios, the layout of fixed antennas is difficult to effectively deal with problems such as user position changes, channel fading and interference.

[0003] Among related technologies, movable antenna technology has the potential to improve wireless communication performance. By allowing the antenna to move in three-dimensional space, movable antenna technology can dynamically adjust the antenna position to optimize the signal transmission channel, thereby significantly improving communication performance. However, movable antenna systems usually require each antenna unit in the antenna unit array to be equipped with an independent driving component so that each antenna unit can move independently, resulting in a significant increase in the use cost, including hardware cost, energy consumption and maintenance difficulty, as the number of antennas increases. Summary of the invention

[0004] The embodiments of the present application provide a cross-type movable antenna array, a communication system, a communication parameter optimization method and related equipment, which can reduce the use cost of the movable antenna array.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a cross-type movable antenna array, comprising: A plurality of mutually parallel first sliding tracks, a plurality of mutually parallel second sliding tracks, at least one antenna unit and a drive control device; The first sliding track and the second sliding track form a two-dimensional plane grid structure after crossing, and the antenna unit is arranged at the intersection of the first sliding track and the second sliding track; When the drive control device receives a drive request for a target position, the drive control device is used to control the first sliding track and / or the second sliding track to slide, so as to drive the plurality of antenna units to move to the target position.

[0006] In some embodiments, the drive control device includes a first drive motor and a second drive motor, the first drive motor is connected to the first sliding track, and the second drive motor is connected to the second sliding track; There are multiple antenna units, and when the drive control device receives a drive request for a target position of a target antenna unit, the drive control device is used to determine a target antenna unit from the multiple antenna units, and the intersection where the antenna unit is located is the target intersection, and the target intersection includes a first direction position corresponding to the moving direction of the first sliding track and a second direction position corresponding to the moving direction of the second sliding track; The first driving motor is used to control the first sliding track to move to the first direction position, and the second driving motor is used to control the second sliding track to move to the second direction position.

[0007] To achieve the above object, a second aspect of an embodiment of the present application proposes a communication system, including: A base station, the base station being provided with at least one cross-type movable antenna array as described in the first aspect; At least one terminal, the base station communicates with the terminal based on the cross-type movable antenna array.

[0008] To achieve the above-mentioned purpose, a third aspect of an embodiment of the present application proposes a communication parameter optimization method for a communication system, wherein the communication system is as shown in the second aspect, and the communication parameter optimization method is applied to a base station, and the method includes: Based on the cross-type movable antenna array, an instantaneous channel vector between the base station and the terminal is acquired, and based on the instantaneous channel vector, a signal-to-interference-and-noise ratio model corresponding to an uplink signal received by the base station from the terminal is generated; Generate a communication parameter optimization model based on the signal to interference and noise ratio model and the transmit power parameter of the terminal; Solving the communication parameter optimization model to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmitting power; adjusting at least one of the cross-type movable antenna arrays based on the optimized antenna position vector, and adjusting the receiving parameters of the base station based on the optimized base station receiving combining matrix; The optimized terminal transmit power is sent to the terminal, so that the terminal sends transmission information to the base station according to the optimized terminal transmit power.

[0009] In some embodiments, acquiring the instantaneous channel vector between the base station and the terminal based on the cross movable antenna array includes: generating a first direction field response matrix between the terminal and the base station based on a first movement parameter of a first sliding track, a pitch arrival angle and an azimuth arrival angle between the terminal and the base station; generating a second directional field response matrix between the terminal and the base station based on a second movement parameter of a second sliding track, a pitch arrival angle and an azimuth arrival angle between the terminal and the base station; The instantaneous channel vector is obtained based on the Catelli-Rao product of the first directional field response matrix and the second directional field response matrix.

[0010] In some embodiments, there are multiple terminals, and generating a communication parameter optimization model based on the signal to interference and noise ratio model and the transmit power parameter of the terminal includes: Generating an optimization objective function based on minimizing the transmit power parameters of all the terminals; Generate an optimization variable parameter based on an antenna position vector parameter of the base station, a base station receiving combining matrix parameter of the base station, and the transmit power parameter; Generate a transmission rate constraint based on the signal to interference and noise ratio model, and generate an optimization constraint condition based on the transmission rate constraint, the variable optional domain of the optimization variable parameter, and the position distance constraint of the antenna position vector parameter; The communication parameter optimization model is generated based on the optimization objective function, the optimization variable parameters and the optimization constraint conditions.

[0011] In some embodiments, solving the communication parameter optimization model to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmitting power includes: generating a single parameter optimization condition based on the number of terminals of the terminal and the number of tracks of the sliding track; Based on the single transmission path condition and the single parameter optimization condition, the communication parameter optimization model is directly solved to obtain the optimized antenna position vector, the optimized base station receiving combining matrix and the optimized terminal transmitting power.

[0012] In some embodiments, when there are multiple transmission paths between the terminal and the base station, solving the communication parameter optimization model to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmit power includes: Discretize the antenna position vector parameters to obtain discrete antenna position parameters, and construct an initial antenna position matrix based on the discrete antenna position parameters; Iteratively eliminating the initial antenna position matrix to obtain a screening antenna position matrix; Iteratively optimize the screening antenna position matrix based on the optimization objective function to obtain the optimized antenna position vector; Based on the optimized antenna position vector and the instantaneous channel matrix model, the optimized base station receiving combining matrix is ​​obtained, wherein the instantaneous channel matrix model is generated based on the instantaneous channel vectors of all terminals; The optimized terminal transmit power is generated based on the instantaneous channel matrix model and the receiving noise power of the base station.

[0013] In some embodiments, the iterative elimination of the initial antenna position matrix to obtain a screening antenna position matrix includes: Using each initial antenna position in the initial antenna position matrix as a test antenna position one by one; Calculating a first minimum total transmit power corresponding to the inspection antenna position; Deleting the corresponding row vector and / or column vector in the initial antenna position matrix where the inspection antenna position is located, adjusting the inspection antenna position to obtain an adjusted inspection antenna position, and calculating the second minimum total transmit power corresponding to the adjusted inspection antenna position; When the second lowest total transmit power is less than the first lowest total transmit power, the verification antenna positions in the initial antenna position matrix are updated based on the adjusted verification antenna positions.

[0014] In some embodiments, the iteratively optimizing the screening antenna position matrix based on the optimization objective function to obtain the optimized antenna position vector includes: Based on the optimization objective function, a third minimum total transmit power corresponding to the screening antenna position matrix is ​​calculated; Based on the unit matrix, replace the row vectors in the screening antenna position matrix one by one to obtain a first replacement screening antenna position, and calculate the fourth minimum total transmit power corresponding to the first replacement screening antenna position; when the fourth minimum total transmit power is less than the third minimum total transmit power and the first replacement screening antenna position satisfies the position distance constraint, update the screening antenna position matrix based on the first replacement screening antenna position, and use the fourth minimum total transmit power as the new third minimum total transmit power; Based on the updated screening antenna position matrix, the optimized antenna position vector is obtained.

[0015] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the communication parameter optimization method of the communication system as described in the third aspect.

[0016] To achieve the above-mentioned purpose, the fifth aspect of an embodiment of the present application proposes a storage medium, which is a computer-readable storage medium, and the storage medium stores a computer program. When the computer program is executed by a processor, it implements the communication parameter optimization method of the communication system as described in the third aspect.

[0017] The embodiments of the present application propose a cross-type movable antenna array, a communication system, a communication parameter optimization method and related equipment. The cross-type movable antenna array includes: a plurality of mutually parallel first sliding rails, a plurality of mutually parallel second sliding rails, at least one antenna unit and a drive control device; the first sliding rails and the second sliding rails form a two-dimensional plane grid structure after crossing, and the antenna unit is arranged at the intersection of the first sliding rail and the second sliding rail; when the drive control device receives a drive request for a target position, the drive control device is used to control the first sliding rail and / or the second sliding rail to slide, so as to drive the plurality of antenna units to move to the target position. The embodiment of the present application utilizes mutually intersecting first sliding rails and second sliding rails to form a two-dimensional plane grid structure, and sets the antenna unit at the intersection of the two-dimensional plane grid structure, and realizes the coordinated movement of the antenna unit by controlling the sliding of the first sliding rail and the second sliding rail. This design significantly reduces the number of required drive control devices, greatly reduces hardware costs, energy consumption and maintenance difficulties, makes the deployment and application of large-scale movable antenna arrays more economical and feasible, and thus greatly reduces the cost of using movable antenna arrays; at the same time, the scheme can still flexibly adjust the antenna position, adapt to the dynamically changing wireless channel environment, and effectively deal with problems such as terminal position changes, channel fading and interference, thereby improving the communication quality, data transmission rate and network capacity in multi-terminal communication scenarios, etc.

[0018] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a structural schematic diagram of a cross-type movable antenna array provided in one embodiment of the present application.

[0020] Figure 2 It is a structural schematic diagram of a communication system equipped with a cross-type movable antenna array provided by another embodiment of the present application.

[0021] Figure 3 This is a channel space angle schematic diagram provided by another embodiment of the present application.

[0022] Figure 4This is a flowchart of a communication parameter optimization method for a communication system provided by another embodiment of the present application.

[0023] Figure 5 yes Figure 4 Flow chart of step 401 in FIG.

[0024] Figure 6 yes Figure 4 Flow chart of step 402 in FIG.

[0025] Figure 7 yes Figure 4 Flow chart of step 403 in FIG.

[0026] Figure 8 yes Figure 4 Another flow chart of step 403 in FIG.

[0027] Fig. 9 yes Figure 8 Flowchart of step 802 in FIG.

[0028] Fig.10 yes Figure 8 Flow chart of step 803 in FIG.

[0029] Fig.11 It is a simulation schematic diagram of a first communication system equipped with a cross-type movable antenna array provided by another embodiment of the present application.

[0030] Fig.12 It is a simulation schematic diagram of a second communication system equipped with a cross-type movable antenna array provided by another embodiment of the present application.

[0031] Fig.13 This is a schematic diagram of the hardware structure of an electronic device provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0033] It should be noted that although the functional modules are divided in the device schematic and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0035] First, explain the symbols that appear below: , , as well as denote conjugate, inverse, conjugate transpose, and transpose operations respectively; It means to find the expectation of a random variable; express The identity matrix of Represents the dot product of vector a and vector b; , as well as They represent the Euclidean norm, Frobenius norm and infinite norm of a complex vector respectively; Representation vector The j-th element of .

[0036] With the rapid development of wireless communication technology, users have an increasing demand for communication quality, data transmission rate and network capacity. Traditional fixed-position antenna systems cannot flexibly adapt to dynamically changing wireless channel environments due to their fixed antenna positions, resulting in limited communication performance. Especially in multi-user communication scenarios, the layout of fixed antennas is difficult to effectively deal with problems such as user position changes, channel fading and interference.

[0037] Among related technologies, movable antenna technology has the potential to improve wireless communication performance. By allowing the antenna to move in three-dimensional space, movable antenna technology can dynamically adjust the antenna position to optimize the signal transmission channel, thereby significantly improving communication performance. However, movable antenna systems usually require each antenna unit in the antenna unit array to be equipped with an independent driving component so that each antenna unit can move independently, resulting in a significant increase in the use cost, including hardware cost, energy consumption and maintenance difficulty, as the number of antennas increases.

[0038] In order to reduce the use cost of the movable antenna array, the embodiment of the present application utilizes a first sliding track and a second sliding track that intersect each other to form a two-dimensional plane grid structure, and sets the antenna unit at the intersection of the two-dimensional plane grid structure, and realizes the coordinated movement of the antenna unit by controlling the sliding of the first sliding track and the second sliding track. This design significantly reduces the number of required drive control devices, greatly reduces hardware costs, energy consumption and maintenance difficulties, makes the deployment and application of large-scale movable antenna arrays more economical and feasible, and thus greatly reduces the use cost of the movable antenna array; at the same time, the scheme can still flexibly adjust the antenna position, adapt to the dynamically changing wireless channel environment, and effectively deal with problems such as terminal position changes, channel fading and interference, thereby improving the communication quality, data transmission rate and network capacity in multi-terminal communication scenarios, etc.

[0039] The following will further describe the cross-type movable antenna array, communication system, communication parameter optimization method and related equipment proposed in the embodiments of the present application. First, a cross-type movable antenna array is described, referring to Figure 1 , is a schematic diagram of the structure of a cross-type movable antenna array provided in an embodiment of the present application. Figure 1 As shown, the cross-type movable antenna array proposed in the embodiment of the present application includes a sliding track, an antenna unit and a drive control device. Among them, the sliding track includes M first sliding tracks in the vertical direction and N second sliding tracks in the horizontal direction, which together form a two-dimensional plane grid structure. Each antenna unit is installed at the intersection of the first sliding track and the second sliding track, and is connected to the radio frequency chain through a flexible cable to realize the movement of the antenna. Each first sliding track and the second sliding track are driven by an independent drive control device respectively, which is used to control the movement of the antenna in the horizontal and vertical directions.

[0040] The drive control device may be: Figure 1 The driving motor shown in the figure is arranged at one end of each sliding track, wherein the driving control device corresponding to the vertical first driving track is the first driving motor, and the driving control device corresponding to the horizontal second driving track is the second driving motor. When the driving control device receives the driving request of the target position, the first driving motor controls the vertical first sliding track to move horizontally, thereby changing the horizontal position of each column of antenna units to the first direction position; the second driving motor controls the horizontal second sliding track to move vertically, thereby changing the vertical position of each row of antenna units to the second direction position, and completing the coordinated movement of the target antenna unit at the target intersection corresponding to the target position to the target position. Unlike the traditional movable antenna system, the cross-type movable antenna array significantly reduces the hardware complexity and motion overhead through the coordinated movement mechanism. In addition, the cross-type movable antenna array realizes the coordinated movement of multiple antenna units through horizontal and vertical sliding tracks. Compared with the traditional movable antenna system, the cross-type movable antenna array significantly reduces the number of driving components, reduces the hardware complexity and cost.

[0041] It is understandable that the first sliding track and the second sliding track can be not only in the vertical and horizontal directions, but also in the upward and downward directions, and do not have to be perpendicular to each other, but only need to intersect on a plane to form a two-dimensional plane grid structure.

[0042] By utilizing mutually intersecting first sliding rails and second sliding rails to form a two-dimensional plane grid structure, and arranging the antenna units at the intersections in the two-dimensional plane grid structure, the coordinated movement of the antenna units is achieved by controlling the sliding of the first sliding rail and the second sliding rail. This design significantly reduces the number of required drive control devices, greatly reduces hardware costs, energy consumption and maintenance difficulties, and makes the deployment and application of large-scale movable antenna arrays more economical and feasible, thereby greatly reducing the cost of using movable antenna arrays; at the same time, the solution can still flexibly adjust the antenna position, adapt to the dynamically changing wireless channel environment, and effectively deal with problems such as terminal position changes, channel fading and interference, thereby improving the communication quality, data transmission rate and network capacity in multi-terminal communication scenarios.

[0043] Reference Figure 2 , is a schematic diagram of the structure of a communication system equipped with a cross-type movable antenna array provided by an embodiment of the present application. Figure 2 As shown in , the communication system includes a base station equipped with a cross-type movable antenna array and K terminals, and then the base station communicates with the terminals based on the loaded cross-type movable antenna array.

[0044] In this embodiment, a field response channel model is used to describe the change of the channel with the antenna position. It is assumed that the channel between the base station and the terminal meets the far field condition because the size of the moving area of ​​the antenna unit (usually several wavelengths) is much smaller than the signal propagation distance. , assuming the base station receives channel paths. Figure 3 , is a schematic diagram of a channel space angle provided in an embodiment of the present application. Figure 3 As shown in the terminal No. The physical pitch arrival angle and azimuth arrival angle of each path are expressed as and .

[0045] Based on the above description of the cross-type movable antenna array and the communication system, the following further describes a communication parameter optimization method of a communication system provided in an embodiment of the present application. The communication parameter optimization method of the communication system provided in the embodiment of the present application can be applied to a base station in the communication system or a processor connected to the base station, etc. Figure 4 , which is an optional flow chart of the communication parameter optimization method of the communication system provided in the embodiment of the present application, Figure 4 The method in the embodiment may include but is not limited to steps 401 to 405. Figure 4 The order of step 401 to step 405 is not specifically limited, and the order of steps can be adjusted or some steps can be reduced or added according to actual needs.

[0046] Step 401: Based on a cross-type movable antenna array, an instantaneous channel vector between a base station and a terminal is obtained, and a signal-to-interference-and-noise ratio model corresponding to an uplink signal received by the base station from the terminal is generated based on the instantaneous channel vector.

[0047] The following is a detailed description of step 401.

[0048] In some embodiments, in order to improve the communication efficiency and reduce the communication cost of the terminals between a base station equipped with a cross-type movable antenna array and multiple terminals, it is first necessary to perform data modeling on the instantaneous channel vector between the base station and the terminal in the communication system based on the cross-type movable antenna array, so as to facilitate the subsequent use of the instantaneous channel vector to generate a signal-to-noise ratio model corresponding to the uplink signal received by the base station at the terminal.

[0049] The following further describes how to model the instantaneous channel vector between the base station and the terminal based on the cross-type movable antenna array.

[0050] Reference Figure 5 , based on a cross-type movable antenna array, obtaining an instantaneous channel vector between a base station and a terminal, including the following steps 501 to 503.

[0051] Step 501: Generate a first directional field response matrix between a terminal and a base station based on a first movement parameter of a first sliding track, an elevation arrival angle and an azimuth arrival angle between a terminal and a base station.

[0052] Step 502: Generate a second directional field response matrix between the terminal and the base station based on a second movement parameter of the second sliding track, an elevation arrival angle and an azimuth arrival angle between the terminal and the base station.

[0053] Step 503: Obtain an instantaneous channel vector based on the Catelli-Rao product of the first directional field response matrix and the second directional field response matrix.

[0054] Steps 501 to 503 are described in detail below.

[0055] Based on Figure 3 The channel space angle diagram shown is based on the first movement parameter of the first sliding track. , No. The elevation arrival angle of the ℓth path between the terminal and the base station and azimuth angle of arrival , generating The first direction field response vector in the horizontal direction between the terminal and the base station As shown in the following formula (1).

[0056] (1) Similarly, based on the second movement parameter of the second sliding track, the The first Pitch arrival angle of each path and azimuth angle of arrival , generating The second direction field response vector in the vertical direction between the terminal and the base station As shown in the following formula (2).

[0057] (2) in and denote the virtual arrival angles of the ℓth path to the terminal k and the base station, respectively. Therefore, the first direction field response matrices corresponding to the horizontal and vertical directions are and the second direction field response matrix They are shown in the following formulas (3) and (4) respectively.

[0058] (3) (4) Then, based on the first directional field response matrix and the second direction field response matrix The Khatri-Rao product (⊙) of the terminal k and the base station is obtained to obtain the instantaneous channel vector As shown in the following formula (5).

[0059] (5) Through the above steps 501 to 503, the channel changes caused by the movement of the terminal can be captured more accurately, especially considering the spatial characteristics of the antenna unit at different positions (the position movement of the antenna unit represented by the first / second sliding track). Compared with only using AoA and AoD to construct the directional field response matrix, introducing the mobile parameter and using the Catelli-Rao product can more finely characterize the spatial correlation of the channel, thereby improving the accuracy of the instantaneous channel vector estimation between the terminal and the base station, and ultimately helping to improve the performance of the communication system.

[0060] Based on the instantaneous channel vector between each terminal and the base station , the instantaneous channel matrix between the base station and all terminals It can be shown as the following formula (6).

[0061] (6) Next, based on the instantaneous channel vector between terminal k and the base station , base station and terminal The instantaneous channel vector between Expressed as a function of the antenna position vector, based on the space division multiple access technology, the base station receives the terminal The transmitted uplink signal is determined by the receive combining matrix, channel matrix and user transmit power. Representative terminal The transmission power is defined as Represents the base station receiving merging matrix. Definition represents the additive Gaussian noise power when the base station receives the signal. Based on this, we can further obtain the terminal signal received by the base station The signal to interference noise ratio (SINR) model corresponding to the transmitted uplink signal is shown in the following formula (7).

[0062] (7) Step 402: Generate a communication parameter optimization model based on the signal to interference and noise ratio model and the terminal's transmit power parameter.

[0063] Step 402 is described in detail below.

[0064] In modeling get terminal After the signal-to-interference-to-noise ratio model (7) between the base station and the base station, in order to further optimize the energy consumption cost of the terminal when the base station and multiple terminals communicate, the signal-to-interference-to-noise ratio model (7) and the transmission power of each terminal are further optimized. Generate a transmission power for each terminal while meeting the communication requirements of each terminal and the base station The following will further describe how to construct the communication transmission optimization model.

[0065] Reference Figure 6 , generating a communication parameter optimization model based on the signal to interference and noise ratio model and the terminal's transmit power parameter, including the following steps 601 to 604.

[0066] Step 601: Generate an optimization objective function based on minimizing the transmit power parameters of all terminals.

[0067] Step 602: Generate optimization variable parameters based on the antenna position vector parameters of the base station, the base station receiving combining matrix parameters of the base station, and the transmission power parameters.

[0068] Step 603: Generate a transmission rate constraint based on the signal to interference and noise ratio model, and generate an optimization constraint condition based on the transmission rate constraint, the variable optional domain of the optimization variable parameter, and the position distance constraint of the antenna position vector parameter.

[0069] Step 604: Generate a communication parameter optimization model based on the optimization objective function, optimization variable parameters, and optimization constraints.

[0070] Steps 601 to 604 are described in detail below.

[0071] In some embodiments, the optimization objective function is first generated based on minimizing the transmission power parameters of all terminals in the communication system. .

[0072] Next, based on the antenna position vector parameters of the base station , the base station receiving merging matrix parameters of the base station And the transmission power parameters Generate optimization variable parameters .

[0073] Afterwards, the transmission rate constraint is generated based on the signal-to-interference-noise ratio model , based on transmission rate constraints, variable optional domains for optimizing variable parameters (including , and ), position distance constraints of antenna position vector parameters (including and ), generate optimization constraints.

[0074] Finally, based on the optimization objective function, optimization variable parameters and optimization constraints, a communication parameter optimization model is generated as shown in the following formula (8).

[0075] (8) Among them, constraint (a) ensures that each terminal meets the minimum rate requirement. , constraint (b) ensures that the transmit power of each terminal is non-negative, and constraints (c) and (d) limit the antenna units in the area The constraints (d) and (f) respectively constrain the antenna spacing in the horizontal and vertical directions to be no less than the minimum threshold. and .

[0076] Through the above steps 601 to 604, by taking minimizing the transmit power of all terminals as the optimization goal, and comprehensively considering the base station antenna position, receiving combining matrix and transmit power as optimization variables, and introducing the transmission rate constraint based on the signal to interference and noise ratio (SINR) and the antenna position distance constraint, a complete communication parameter optimization model is finally formed. This model can minimize the total transmit power of all terminals and optimize the position of the base station antenna and the receiving combining matrix while ensuring that each terminal reaches the target transmission rate. This optimization method can improve spectrum efficiency, reduce energy consumption, reduce interference, and improve overall network performance.

[0077] Step 403: Solve the communication parameter optimization model to obtain the optimized antenna position vector, the optimized base station receiving combining matrix, and the optimized terminal transmitting power.

[0078] The following is a detailed description of step 403.

[0079] Next, the communication parameter optimization model (8) is further solved to obtain the optimized communication parameters, which include optimizing the antenna position vector , optimize base station receiving merging matrix And optimize the terminal transmission power , so that these optimized communication parameters can be used to adjust the base stations and terminals in the communication system in the future, so that the communication performance of the adjusted base stations and terminals during communication is better.

[0080] In this embodiment, the optimal solution and theoretical optimal performance bound of the communication parameter optimization model (8) are first determined when there is only a single communication channel path between the terminal and the base station, and then a practical algorithm is designed to obtain the suboptimal solution of the communication parameter optimization model (8) under a multipath channel.

[0081] The following first describes the solution for a single communication channel path.

[0082] Reference Figure 7 , solving the communication parameter optimization model, obtaining the optimized antenna position vector, the optimized base station receiving combining matrix and the optimized terminal transmitting power, including the following steps 701 to 702.

[0083] Step 701: Generate a single parameter optimization condition based on the number of terminals of the terminal and the number of tracks of the sliding track.

[0084] Step 702: Based on a single transmission path condition and a single parameter optimization condition, the communication parameter optimization model is directly solved to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmitting power.

[0085] Steps 701 to 702 are described in detail below.

[0086] For the case where there is only one communication transmission path between the terminal and the base station (i.e., the single transmission path condition), firstly, a single parameter optimization condition is generated based on the number of terminals K of the terminal and the number of sliding tracks (including the first sliding track number M of the first sliding track and the second sliding track number N of the second sliding track): ; Then, based on the single parameter optimization condition and the single transmission path condition, the optimized antenna position vector in the best case is shown in the following formula (9).

[0087] (9) (10) (11) Among them, and and indicates arrival at the terminal For a multi-terminal communication system with randomly distributed terminals and scatterers, the probability that two terminals have exactly the same arrival angle is zero. Therefore, it is assumed that the arrival angles of paths of different terminals are different. The matrix and Represent the factor decomposition coefficient matrix respectively. Among them, the vector It can be obtained by decomposing the prime factor of the first sliding track number M. For any integer M, the prime factor decomposition is expressed as .in, is the ith prime factor (in non-decreasing order), is the total number of prime factors. Definition . For any positive integer m, , we can factorize the coefficient vector The only certainty, satisfaction ,and .vector is the integer quotient obtained by dividing the number (m-1) by each element in m (from the back to the front). It can be obtained by decomposing the integer N into prime factors. and Represents any two disjoint sets of terminal pairs, the union of which is all pairs of terminals, and the number of elements in each set does not exceed and .definition Representative Set The i-th element of Similarly, define Representative Set The i-th element of .

[0088] Under the condition that the channel transmission path between each terminal and the base station is a single path (i.e., a single transmission path condition), when When , the minimum value of the transmission power of each terminal in the communication parameter optimization model (8) is as shown in the following formula (12).

[0089] (12) in, and Respectively represent the total number of prime factors of the first sliding track number M and the second sliding track number N. For any channel, the lower bound of the transmission power represented by the objective function of the communication parameter optimization model (8) is shown in the following formula (13).

[0090] (13) Through the above steps 701 to 702, a single parameter optimization condition is generated by introducing the number of terminals, the number of sliding tracks and a single transmission path condition, thereby simplifying the originally complex multivariable optimization problem, thereby being able to directly solve the communication parameter optimization model.

[0091] Next, an embodiment of the present application provides a design method for a cross-type movable antenna in a multipath channel to obtain a suboptimal solution to problem (P1).

[0092] At any given antenna location parameter In this application, a zero-forcing receiving and combining method is proposed to minimize the total transmit power while meeting the terminal communication requirements. The specific steps include receiving and combining matrix design, minimum transmit power and antenna position optimization.

[0093] Design of optimized receiving combining matrix: For a given channel matrix , the zero-forcing receiving combining matrix is ​​adopted as shown in the following formula (14).

[0094] (14) For minimum transmit power: To meet the terminal The rate requirement, the minimum transmit power (i.e. the optimized terminal transmit power) is calculated by the following formula (15).

[0095] (15) Based on this, the total transmit power of all terminals can be expressed as follows:

[0096] (16) in, From the above steps of optimizing the design of the receiving merging matrix and the minimum transmitting power, it can be seen that the terminal transmitting power and the base station receiving merging matrix are functions related to the antenna position vector. The embodiment of the present application optimizes the antenna position vector according to the method described in the following antenna position optimization, and then determines the corresponding optimized terminal transmitting power and optimized base station receiving merging matrix.

[0097] The relevant steps for optimizing the antenna position will be further described below.

[0098] Reference Figure 8When there are multiple transmission paths between the terminal and the base station, the communication parameter optimization model is solved to obtain the optimized antenna position vector, the optimized base station receiving combining matrix and the optimized terminal transmitting power, including the following steps 801 to 805.

[0099] Step 801: discretize antenna position vector parameters to obtain discrete antenna position parameters, and construct an initial antenna position matrix based on the discrete antenna position parameters.

[0100] Step 802: iteratively eliminate the initial antenna position matrix to obtain a screening antenna position matrix.

[0101] Steps 801 to 802 are described in detail below.

[0102] For antenna position optimization, first, discretize the antenna movement area, that is, the horizontal movement area of ​​the antenna position vector parameter Vertical moving area Discretize into and The candidate positions, i.e., discrete antenna position parameters, are respectively shown in the following formula (17).

[0103] (17) in, and .

[0104] Then, the channel matrix and the binary selection matrix are constructed, that is, based on the discretized discrete antenna position parameters, the channel vectors from the candidate positions corresponding to all discrete antenna position parameters to the terminal k are constructed. . Combine the channel vectors of all terminals into a channel matrix .

[0105] Construct two binary matrices as the initial antenna position matrix, namely and , respectively representing the antenna position selection in the horizontal and vertical directions. Among them, each row of each binary selection matrix has only one element of 1, indicating the antenna position of the row or column.

[0106] Initialize the binary selection matrix to the identity matrix, denoted as and .

[0107] Next, the initial antenna position selection matrix is ​​iteratively eliminated, that is, rows are gradually eliminated from the initial antenna position selection matrix corresponding to the initial binary matrix until and There are only M and N rows left respectively, as described below.

[0108] Reference Fig. 9 , iteratively eliminate the initial antenna position matrix to obtain a screening antenna position matrix, including the following steps 901 to 904.

[0109] Step 901: Each initial antenna position in the initial antenna position matrix is ​​used as a test antenna position one by one.

[0110] Step 902: Calculate the first minimum total transmit power corresponding to the inspection antenna position.

[0111] Step 903: Delete the corresponding row vector and / or column vector in the initial antenna position matrix where the test antenna position is located, adjust the test antenna position to obtain an adjusted test antenna position, and calculate the second minimum total transmission power corresponding to the adjusted test antenna position.

[0112] Step 904: When the second lowest total transmit power is less than the first lowest total transmit power, update the verification antenna position in the initial antenna position matrix based on the adjusted verification antenna position.

[0113] Steps 901 to 904 are described in detail below.

[0114] In some embodiments, the iteration parameter i is first set to 0, and the iteration parameter i is substituted into the initial antenna position matrix to use each initial antenna position in the initial antenna position matrix as a test antenna position one by one, and then determine whether i satisfies If satisfied , then calculate the current test antenna position and The total transmission power under the condition of As shown in the following formula (18).

[0115] (18) Then, the iteration parameter i corresponds to Assigned to . Set another iteration parameter j=1 and perform the following operations in a loop.

[0116] For the corresponding row vector in the initial antenna position matrix where the test antenna is located, delete The jth row of the matrix is ​​assigned to . Calculate the current adjustment to verify the antenna position and The total transmission power under is the second lowest total transmission power As shown in the following formula (19).

[0117] (19) If the second total transmission power at the current adjustment test antenna position Less than the first lowest total transmit power , then based on the adjustment of the test antenna position, the test antenna position in the initial antenna position matrix is ​​updated, that is, Assign to , and Updated to the total transmit power at the current antenna position .

[0118] Each time through the loop, increase the value of j by 1 until until.

[0119] On the contrary, if you are not satisfied , then enter the next loop to determine whether the iteration parameter i satisfies If satisfied, calculate the current test antenna position and The total transmission power under the condition of , that is, the first minimum total transmission power, is recorded as As shown in the following formula (20).

[0120] (20) Then, the iteration parameter i corresponding to Assigned to . Set j=1 and execute the following operations in a loop.

[0121] For the corresponding column vector in the initial antenna position matrix where the test antenna is located, delete The jth row of the matrix is ​​assigned to . Calculate the current adjustment to check the antenna position and The total transmission power under is the second lowest total transmission power As shown in the following formula (21).

[0122] (twenty one) If the second total transmission power at the current adjustment test antenna position Less than the first lowest total transmit power , then based on the adjustment of the test antenna position, the test antenna position in the initial antenna position matrix is ​​updated, that is, Assign to , and Updated to the total transmit power at the current antenna position .

[0123] Each time through the loop, increase the value of j by 1 until until.

[0124] After the above cycle ends, if it is not satisfied , increase the value of the iteration parameter i by 1 to determine whether If satisfied, repeat the above cycle. Otherwise, exit the cycle to complete the iterative elimination of the initial antenna position selection matrix.

[0125] Step 803: iteratively optimize the screening antenna position matrix based on the optimization objective function to obtain an optimized antenna position vector.

[0126] Step 803 is described in detail below.

[0127] Next, the antenna position matrix is ​​screened based on the optimization objective function. and Iterative optimization is performed to further reduce the total transmit power while satisfying the minimum spacing constraint between antennas, thereby obtaining an optimized antenna position vector, as described below.

[0128] Reference Fig.10 , based on the optimization objective function, the screening antenna position matrix is ​​iteratively optimized to obtain the optimized antenna position vector, including the following steps 1001 to 1003.

[0129] Step 1001: Based on the optimization objective function, calculate and obtain the third minimum total transmit power corresponding to the screening antenna position matrix.

[0130] Step 1002: Based on the unit matrix, replace the row vectors in the screening antenna position matrix one by one to obtain the first replacement screening antenna position, and calculate the fourth minimum total transmit power corresponding to the first replacement screening antenna position. When the fourth minimum total transmit power is less than the third minimum total transmit power and the first replacement screening antenna position satisfies the position distance constraint, update the screening antenna position matrix based on the first replacement screening antenna position, and use the fourth minimum total transmit power as the new third minimum total transmit power.

[0131] Step 1003: Based on the updated screening antenna position matrix, an optimized antenna position vector is obtained.

[0132] Steps 1001 to 1003 are described in detail below.

[0133] First, initialize the parameters and iterate to optimize the parameters is positive infinity, and then the front antenna position selection matrix, that is, the screening antenna position matrix and The total transmission power under Assign to . Set i=1.

[0134] Afterwards, determine whether If satisfied , then execute the setting is positive infinity, Assigned to Set j = 1 and repeat the following row replacement process. In each row replacement process, replace the matrix The i-th row of is replaced by the identity matrix The j-th row vector of , get the first replacement screening antenna position. Calculate the new antenna position selection matrix and (i.e., the total transmit power under the first replacement screening antenna position), i.e., the fourth lowest total transmit power If the position selection matrix corresponding to the first replacement screening antenna position satisfies the position distance constraint, that is, , and the fourth lowest total transmit power Less than , then based on the first replacement screening antenna position update screening antenna position matrix, that is Updated to At the same time, the fourth lowest total transmission power is used as the new third lowest total transmission power, that is, Updated to At the end of each row replacement loop, j is incremented by 1 until Ends the line replacement process.

[0135] On the contrary, if you are not satisfied , determine whether If satisfied ,set up is positive infinity, Assigned to Set j = 1 and repeat the following row replacement process. In each row replacement process, replace the matrix The i-th row of is replaced by the identity matrix The jth row of , and assign the replaced new matrix to the matrix , get the first replacement screening antenna position. Calculate the new antenna position selection matrix and The total transmit power of the first replacement screening antenna position, that is, the fourth lowest total transmit power If the position selection matrix corresponding to the first replacement screening antenna position satisfies the position distance constraint, that is, , and the fourth lowest total transmit power Less than , then based on the first replacement screening antenna position update screening antenna position matrix, that is Updated to At the same time, the fourth lowest total transmission power is used as the new third lowest total transmission power, that is, Updated to At the end of each row replacement loop, j is incremented by 1 until Ends the line replacement process.

[0136] If not satisfied , and is not satisfied judge With the front antenna position selection matrix and Total transmit power under Is the absolute value of the difference less than the predetermined threshold? If so, repeat the above loop iteration optimization process, otherwise, exit the above loop iteration optimization process. And return the updated screening antenna position matrix and , to obtain the optimized antenna position vector.

[0137] Step 804: Based on the optimized antenna position vector and the instantaneous channel matrix model, an optimized base station receiving combining matrix is ​​obtained.

[0138] Step 805: Generate optimized terminal transmission power based on the instantaneous channel matrix model and the receiving noise power of the base station.

[0139] Steps 804 to 805 are described in detail below.

[0140] In some embodiments, after obtaining the optimized antenna position vector, combined with the above formula (14) of the optimized receiving merging matrix, based on the optimized antenna position vector and the instantaneous channel matrix model, the corresponding optimized base station receiving merging matrix can be obtained: . In combination with the above formula (6), the instantaneous channel matrix model It can be further determined based on the optimized antenna position vector.

[0141] And, based on the above minimum transmit power formula (15), after obtaining the optimized antenna position vector, we can further calculate the instantaneous channel matrix model based on and the base station's receiving noise power , generating optimized terminal transmit power .

[0142] Through the above steps 801 to 805, 901 to 904, and 1001 to 1004, the continuous antenna position parameters are first discretized to construct an initial antenna position matrix, and then each initial antenna position is checked one by one through an iterative elimination process, and the influence of removing and adjusting the position on the total transmission power of the system before and after is compared. If the adjusted position can reduce the total transmission power, the antenna position matrix is ​​updated. In this step, by comparing the performance of different antenna positions, the antenna position that is more conducive to reducing the transmission power is preliminarily screened out, thereby reducing the amount of calculation for subsequent optimization; in addition, based on the screened antenna position matrix, further iterative optimization is performed, and by comparing with the unit matrix, the antenna position in the screening matrix is ​​replaced row by row, and the total transmission power after replacement is calculated. If the replaced position can further reduce the total transmission power under the premise of satisfying the position distance constraint, the screening matrix is ​​updated. In this step, based on the preliminary screening, the antenna position is adjusted more finely to find the global optimal antenna position vector; after determining the optimal antenna position vector, the optimal base station receiving merging matrix is ​​calculated based on the instantaneous channel matrix model of all terminals. Finally, the optimal terminal transmit power is determined by combining the instantaneous channel matrix model and the base station's receiving noise power; this allows the global optimal solution to be gradually approached through a phased, iterative optimization approach, while ensuring system performance (such as minimizing the total transmit power) while reducing the complexity of the optimization problem and improving computational efficiency. This method is particularly suitable for multipath transmission environments, and can effectively utilize spatial resources and optimize antenna layout, thereby improving the overall performance of the communication system.

[0143] In practical applications, as the terminal and / or environmental scatterers move, channel coefficients such as the angle of arrival of the channel path from each terminal to the base station change over time. Therefore, the instantaneous channel vector of each terminal exhibits random fading. In these scenarios, frequent adjustment of the antenna position based on the instantaneous channel will result in higher mobility overhead and energy consumption. To solve the above problems, the embodiment of the present application further expands the above-mentioned cross-type movable antenna system optimization method and proposes a cross-type movable antenna array auxiliary communication system based on a dual time scale optimization strategy. This system optimizes the antenna position based on statistical channel parameters, and the design of the terminal's transmit power and the base station's receive combining matrix is ​​still based on the instantaneous channel. Among them, the dual time scale optimization problem of minimizing the terminal's expected transmit power is shown in the following formula (22).

[0144] (twenty two) in, Represents the expected transmit power of the terminal over time.

[0145] In solving the above dual-time-scale optimization problem (22), the expected value of the total transmit power is approximated by Monte Carlo simulation. Specifically, based on the given terminal statistical channel distribution, a sufficient number of instantaneous channel samples are randomly generated. Let the random realization of the sth instantaneous channel mapping be , where S represents the total number of samples. Each sample represents an instantaneous channel realization. For each instantaneous channel realization, the optimized terminal transmit power is calculated by the following formula (23).

[0146] (twenty three) in, Represents the matrix data All row element data for the column.

[0147] The zero-forcing receiving combining matrix shown in the following formula (24) is used to obtain the optimized base station receiving combining matrix.

[0148] (twenty four) Afterwards, the average value of the total transmit power of the S instantaneous channels is calculated as the expected value of the total transmit power in time, that is, the approximate value of the objective function of the dual time scale optimization problem. The antenna position optimization design is completed using the relevant antenna position optimization steps in the above steps 801 to 803. Finally, the optimized antenna position vector is substituted into the design of the optimized receiving merging matrix and the minimum transmit power calculation to optimize the terminal transmit power and optimize the base station receiving merging matrix.

[0149] Step 404: Adjust at least one cross-type movable antenna array based on the optimized antenna position vector, and adjust the receiving parameters of the base station based on the optimized base station receiving combining matrix.

[0150] Step 405: Send the optimized terminal transmit power to the terminal, so that the terminal sends transmission information to the base station according to the optimized terminal transmit power.

[0151] Steps 404 to 405 are described in detail below.

[0152] In some embodiments, after the communication parameter optimization model is calculated to obtain the optimized antenna position vector, the optimized base station receiving merging matrix, and the optimized terminal transmission power, the optimal antenna position vector is used to physically adjust the position of at least one cross-type movable antenna array in the base station, and the receiving parameters of the base station are adjusted according to the optimal base station receiving merging matrix, so that the communication system actually works in the optimal state of antenna position and receiving merging mode. At the same time, the optimal terminal transmission power is sent to the terminal to guide the terminal to use the power for data transmission, so that the entire system achieves the best performance after optimization.

[0153] In order to verify the effectiveness of the method proposed in this application, Monte Carlo simulation and performance comparison experiments were conducted in this embodiment. The experimental parameters are as follows: the size of the cross-type movable antenna array is M×N=6 meters×6 meters, installed on a base station with a height of 10 meters. The size of the antenna moving area is 20λ×20λ, and the optimization algorithm is based on The sector covered by the base station spans an azimuth of 120°. In this sector, it is assumed that there are three cubic buildings located at , and The total number of terminals is K = 18. Half of the terminals are randomly distributed on the ground, with a distance from the base station ranging from 5 to 50 meters; the other half are randomly distributed in buildings. The carrier frequency is 30 GHz. The line-of-sight channel path gain between the base station and each terminal is ,in is the distance between the base station and terminal k. The noise power is -80 dBm, and the minimum rate requirement for each terminal is 3 bps / Hz. The total number of Monte Carlo simulations for terminal distribution and instantaneous channel realization is S = 1000.

[0154] In addition to the communication parameter optimization scheme for a communication system equipped with a cross-type movable antenna proposed in the embodiment of the present application, the following three methods are used as control group schemes.

[0155] (1) Antenna-by-antenna movement scheme: Independent antenna movement is performed within a two-dimensional rectangular area. For each antenna array element, the antenna position is adjusted using the antenna position optimization method proposed in the present invention.

[0156] (2) Dense UPA solution: a uniform planar array (UPA) is used with an antenna spacing of .

[0157] (3) Sparse UPA solution: using a uniform planar array with an antenna spacing of 4 .

[0158] For fair comparison, all baseline schemes use the same number of antennas as the crossed movable antenna array.

[0159] Reference Fig.11 , is a simulation schematic diagram of a first communication system equipped with a cross-type movable antenna array provided in an embodiment of the present application. Fig.11As shown in , the comparison of the total transmission power achieved by the scheme proposed in this embodiment and the benchmark scheme as the number of terminals changes. The results show that the total transmission power of different large-scale antenna and planar phased array schemes increases with the increase in the number of terminals. However, the performance of the movable antenna scheme is much better than that of the dense and sparse uniform planar array schemes. For example, when the number of terminals K = 30, more than 30 dB of power can be saved. This is because the movable antenna array can effectively reduce the channel correlation between terminals by optimizing the antenna position. In addition, the cross-type movable antenna scheme based on statistical channels has better performance than the dense and sparse uniform array schemes, and can avoid the frequent movement of the antenna due to the random movement of the terminal, significantly reducing the energy consumption caused by the movement of the antenna, and providing a feasible solution for designing base stations using cross-type movable antenna arrays.

[0160] Reference Fig.12 , is a simulation schematic diagram of a second communication system equipped with a cross-type movable antenna array provided in an embodiment of the present application. Fig.12 As shown in the figure, the optimization results of the antenna positions of the cross-type movable antenna array based on statistical channel parameters are shown. On the one hand, the antennas are distributed throughout the movable area to maximize the array aperture while reducing the channel correlation between multiple terminals. On the other hand, the antennas are arranged in a non-uniform manner to reduce the beam sidelobes.

[0161] The present application also provides an electronic device, including: at least one memory; at least one processor; at least one program; The program is stored in the memory, and the processor executes the at least one program to implement the communication parameter optimization method and the communication parameter optimization method of the communication system implemented in the present application. The electronic device can be any intelligent terminal including a mobile phone, a tablet computer, a personal digital assistant (PDA), a car computer, etc.

[0162] See also Fig.13 , Fig.13 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes: The processor 1301 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 1302 can be implemented in the form of ROM (Read Only Memory), static storage device, dynamic storage device or RAM (Random Access Memory). The memory 1302 can store operating systems and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1302, and the processor 1301 calls and executes the communication parameter optimization method and communication parameter optimization method of the communication system of the embodiment of the present application; Input / output interface 1303, used to implement information input and output; The communication interface 1304 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.); A bus 1305 that transmits information between various components of the device (e.g., the processor 1301, the memory 1302, the input / output interface 1303, and the communication interface 1304); The processor 1301 , the memory 1302 , the input / output interface 1303 and the communication interface 1304 are connected to each other in communication within the device via a bus 1305 .

[0163] An embodiment of the present application also provides a storage medium, which is a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, the communication parameter optimization method and the communication parameter optimization method of the above-mentioned communication system are implemented.

[0164] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0165] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0166] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0167] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0169] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0170] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0171] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0172] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0173] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0174] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0175] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A cross-type movable antenna array, characterized in that: include: A plurality of mutually parallel first sliding tracks, a plurality of mutually parallel second sliding tracks, at least one antenna unit and a drive control device; The first sliding track and the second sliding track form a two-dimensional plane grid structure after crossing, and the antenna unit is arranged at the intersection of the first sliding track and the second sliding track; When the drive control device receives a drive request for a target position, the drive control device is used to control the first sliding track and / or the second sliding track to slide, so as to drive the plurality of antenna units to move to the target position.

2. The cross-type movable antenna array according to claim 1, characterized in that: include: The drive control device comprises a first drive motor and a second drive motor, the first drive motor is connected to the first sliding track, and the second drive motor is connected to the second sliding track; There are multiple antenna units, and when the drive control device receives a drive request for a target position of a target antenna unit, the drive control device is used to determine a target antenna unit from the multiple antenna units, and the intersection where the antenna unit is located is the target intersection, and the target intersection includes a first direction position corresponding to the moving direction of the first sliding track and a second direction position corresponding to the moving direction of the second sliding track; The first driving motor is used to control the first sliding track to move to the first direction position, and the second driving motor is used to control the second sliding track to move to the second direction position.

3. A communication system, characterized in that: include: A base station, the base station being provided with at least one cross-type movable antenna array as claimed in claim 1; At least one terminal, the base station communicates with the terminal based on the cross-type movable antenna array.

4. A communication parameter optimization method for a communication system, characterized in that: The communication system is as shown in claim 3, the method is applied to the base station, and the method includes: Based on the cross-type movable antenna array, an instantaneous channel vector between the base station and the terminal is acquired, and based on the instantaneous channel vector, a signal-to-interference-and-noise ratio model corresponding to an uplink signal received by the base station from the terminal is generated; Generate a communication parameter optimization model based on the signal to interference and noise ratio model and the transmit power parameter of the terminal; Solving the communication parameter optimization model to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmitting power; adjusting at least one of the cross-type movable antenna arrays based on the optimized antenna position vector, and adjusting the receiving parameters of the base station based on the optimized base station receiving combining matrix; The optimized terminal transmit power is sent to the terminal, so that the terminal sends transmission information to the base station according to the optimized terminal transmit power.

5. The communication parameter optimization method of the communication system according to claim 4, characterized in that: The acquiring, based on the cross-type movable antenna array, an instantaneous channel vector between the base station and the terminal comprises: generating a first direction field response matrix between the terminal and the base station based on a first movement parameter of a first sliding track, a pitch arrival angle and an azimuth arrival angle between the terminal and the base station; generating a second directional field response matrix between the terminal and the base station based on a second movement parameter of a second sliding track, a pitch arrival angle and an azimuth arrival angle between the terminal and the base station; The instantaneous channel vector is obtained based on the Catelli-Rao product of the first directional field response matrix and the second directional field response matrix.

6. The communication parameter optimization method of a communication system according to claim 4, characterized in that: There are multiple terminals, and generating a communication parameter optimization model based on the signal to interference and noise ratio model and the transmit power parameter of the terminal includes: Generating an optimization objective function based on minimizing the transmit power parameters of all the terminals; Generate an optimization variable parameter based on an antenna position vector parameter of the base station, a base station receiving combining matrix parameter of the base station, and the transmit power parameter; Generate a transmission rate constraint based on the signal to interference and noise ratio model, and generate an optimization constraint condition based on the transmission rate constraint, the variable optional domain of the optimization variable parameter, and the position distance constraint of the antenna position vector parameter; The communication parameter optimization model is generated based on the optimization objective function, the optimization variable parameters and the optimization constraint conditions.

7. The communication parameter optimization method of a communication system according to claim 6, characterized in that: The solving the communication parameter optimization model to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmitting power includes: generating a single parameter optimization condition based on the number of terminals of the terminal and the number of tracks of the sliding track; Based on the single transmission path condition and the single parameter optimization condition, the communication parameter optimization model is directly solved to obtain the optimized antenna position vector, the optimized base station receiving combining matrix and the optimized terminal transmitting power.

8. The communication parameter optimization method of a communication system according to claim 6, characterized in that: When there are multiple transmission paths between the terminal and the base station, solving the communication parameter optimization model to obtain an optimized antenna position vector, an optimized base station receiving combining matrix, and an optimized terminal transmitting power includes: Discretize the antenna position vector parameters to obtain discrete antenna position parameters, and construct an initial antenna position matrix based on the discrete antenna position parameters; Iteratively eliminating the initial antenna position matrix to obtain a screening antenna position matrix; Iteratively optimize the screening antenna position matrix based on the optimization objective function to obtain the optimized antenna position vector; The optimized base station receiving combining matrix is ​​obtained based on the optimized antenna position vector and the instantaneous channel matrix model, wherein the instantaneous channel matrix model is generated based on the instantaneous channel vectors of all terminals; The optimized terminal transmit power is generated based on the instantaneous channel matrix model and the receiving noise power of the base station.

9. The communication parameter optimization method of a communication system according to claim 8, characterized in that: The iterative elimination of the initial antenna position matrix to obtain a screening antenna position matrix includes: Using each initial antenna position in the initial antenna position matrix as a test antenna position one by one; Calculating a first minimum total transmit power corresponding to the inspection antenna position; Deleting the corresponding row vector and / or column vector in the initial antenna position matrix where the inspection antenna position is located, adjusting the inspection antenna position to obtain an adjusted inspection antenna position, and calculating the second minimum total transmit power corresponding to the adjusted inspection antenna position; When the second lowest total transmit power is less than the first lowest total transmit power, the verification antenna positions in the initial antenna position matrix are updated based on the adjusted verification antenna positions.

10. The communication parameter optimization method of a communication system according to claim 8, characterized in that: The iteratively optimizing the screening antenna position matrix based on the optimization objective function to obtain the optimized antenna position vector includes: Based on the optimization objective function, a third minimum total transmit power corresponding to the screening antenna position matrix is ​​calculated; Based on the unit matrix, replace the row vectors in the screening antenna position matrix one by one to obtain a first replacement screening antenna position, and calculate the fourth minimum total transmit power corresponding to the first replacement screening antenna position; when the fourth minimum total transmit power is less than the third minimum total transmit power and the first replacement screening antenna position satisfies the position distance constraint, update the screening antenna position matrix based on the first replacement screening antenna position, and use the fourth minimum total transmit power as the new third minimum total transmit power; Based on the updated screening antenna position matrix, the optimized antenna position vector is obtained.

11. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the communication parameter optimization method of the communication system according to any one of claims 4 to 10 is implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the communication parameter optimization method of the communication system according to any one of claims 4 to 10 is implemented.

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