Throughput optimization method and device for uplink communication of space-air-ground communication system

Abstract

The invention discloses a throughput optimization method and device for uplink communication of a space-air-ground communication system, and relates to the technical field of wireless communication. The method comprises the following steps: constructing an air-space-ground communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment; modulating data transmitted in the uplink communication process of the ground-based communication equipment to the satellite communication equipment into a discrete symbol form to obtain mutual information for reflecting the transmission efficiency of discrete symbol information, and representing the throughput of the uplink communication process of the space-air-ground communication system by the mutual information; constructing an original optimization model by taking the maximum throughput as an optimization target and taking the power upper limit of the communication equipment as a constraint condition; and solving the original optimization model to obtain the maximum throughput of uplink communication.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a method and device for optimizing the throughput of uplink communication in an air-to-ground communication system. Background Art

[0002] The air-to-ground communication system is a communication system with a relay station between the ground and the satellite. Uplink communication is the communication process in which the ground station or low-level network node sends information to the satellite or high-level network node. It has the characteristics of long transmission distance, complex transmission environment and limited resources. Among them, throughput is an indicator that reflects the information processing and transmission capabilities of the air-to-ground communication system during uplink communication, that is, the total amount of data that the system can process and successfully transmit per unit time. By adjusting parameters such as power in the air-to-ground communication system to maximize the throughput during uplink communication, communication efficiency and service quality can be improved, thereby promoting the integrated development of air-to-ground.

[0003] In the prior art, Chinese patent CN 116112060 A discloses a method and device for resource allocation of an air-to-ground communication system based on buffer relay, the method comprising: dividing the transmission time into multiple time slots; establishing a resource allocation optimization problem model of the air-to-ground communication system with the goal of maximizing the average system throughput and combining the target constraint conditions; solving the resource allocation optimization problem model by an alternating iteration method, determining the channel access information between the ground terminal and the high-altitude platform and the transmission power of each channel in each time slot, and the channel access information between the high-altitude platform and the satellite and the transmission power of each channel. The method calculates the transmission rate in an air-to-ground communication system based on Gaussian input, that is, the transmission rate is the channel capacity (that is, the maximum transmission rate that can be achieved in theory).

[0004] However, due to various reasons (such as hardware limitations, modulation methods, coding methods, etc.), it is difficult to achieve that the input signal completely obeys the Gaussian distribution. The channel capacity corresponding to the Gaussian input is actually the upper limit of the transmission rate, which is often an unattainable rate. Therefore, the accuracy of the resource allocation results of the air-to-ground communication system obtained based on the above method needs to be improved. Summary of the invention

[0005] Based on this, it is necessary to provide a method and device for optimizing the throughput of uplink communication in an air-to-ground communication system in response to the above technical problems.

[0006] The present invention adopts the following technical solutions:

[0007] The present invention provides a method for optimizing the throughput of uplink communication in an air-to-ground communication system, comprising:

[0008] Construct an air-ground communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment;

[0009] Modulate the data transmitted during the uplink communication from the ground-based communication equipment to the satellite communication equipment into a discrete symbol form, obtain mutual information for reflecting the efficiency of discrete symbol information transmission, and use the mutual information to characterize the throughput of the uplink communication process of the air-to-ground communication system;

[0010] The original optimization model is constructed with maximizing throughput as the optimization goal and the power upper limit of the communication equipment as the constraint condition; the original optimization model is solved to obtain the maximum throughput of the uplink communication.

[0011] Furthermore, the air-ground communication system is constructed based on ground-based communication equipment, relay station communication equipment and satellite communication equipment, including:

[0012] The relay station communication equipment receives the signal transmitted by the ground-based communication equipment:

[0013] y u =H su P s x+n u

[0014]

[0015] in, It is the signal received by the communication equipment of the relay station. is the number of receiving antennas of the relay station communication equipment; N represents the channel from the ground-based communication equipment to the relay station communication equipment. s Indicates the number of transmitting antennas of ground-based communication equipment; Indicates transmission signal Precoder of means that the mean is zero and the variance is Additive Gaussian white noise, β∈[0,1] is the Rice factor in the Rice channel fading model; G LoS and G NLoS They are the LoS and Rayleigh fading components in the Rice channel fading model, respectively;

[0016] The relay station communication equipment forwards the received signal to the satellite communication equipment using the amplification and forwarding protocol:

[0017] y s =h us P u y u +n s

[0018] Among them, y s It is the signal received by satellite communication equipment; It is the LoS channel from the relay station communication equipment to the satellite communication equipment. The number of transmitting antennas for the relay station communication equipment; is used to integrate the signal y u The relay station communication equipment precoder; n s is zero and has a variance of The additive thermal noise of the additive Gaussian white noise follows

[0019] Furthermore, characterizing the throughput of the uplink communication process of the air-to-ground communication system by mutual information specifically includes:

[0020]

[0021] n=h us P u n u +n s

[0022] Among them, I(x; y s |H su ,h us ) represents the throughput of the uplink communication process, N t is the number of transmitting antennas of the ground-based communication equipment; M is the number of points in the signal constellation; d ij =x i -x j , where x i and x j Indicates N in the M-ary constellation diagram t possible modulation symbol vectors; E n (·) indicates the expectation operation.

[0023] Furthermore, the original optimization model is constructed with maximizing throughput as the optimization goal and the power upper limit of the communication device as the constraint condition, specifically including:

[0024]

[0025] in, and are the actual powers of the ground-based communication equipment and the relay station communication equipment, respectively. The superscript H represents the conjugate transpose; P s and P u They are the upper limits of available power for ground-based communication equipment and relay station communication equipment respectively.

[0026] Furthermore, solving the original optimization model specifically includes:

[0027] Use cut-off rate Instead of I(x;y s |Hsu ,h us ) to reduce the computational complexity of the original optimization model;

[0028] I(x;y s |H su ,h us ) is replaced by the original optimization model with the cutoff rate and decomposed into sub-optimization model 1 and sub-optimization model 2;

[0029] The sub-optimization model is As the optimization objective, the power upper limit of the ground-based communication equipment is used as the constraint condition, where: Indicates P u A known feasible solution of ;

[0030] The sub-optimization model is is the optimization target, and the power upper limit of the relay station communication equipment is the constraint condition; in, Indicates P s A known feasible solution of ;

[0031] Iteratively optimize sub-optimization model 1 and sub-optimization model 2 until the set iteration termination condition is reached, and output the optimization results to obtain the maximum throughput.

[0032] The present invention provides a throughput optimization device for uplink communication of an air-to-ground communication system, comprising:

[0033] An air-ground-space communication system building module, which is used to build an air-ground-space communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment;

[0034] The throughput characterization module is used to modulate the data transmitted during the uplink communication from the ground-based communication equipment to the satellite communication equipment into a discrete symbol form, obtain mutual information for reflecting the transmission efficiency of the discrete symbol information, and use the mutual information to characterize the throughput of the uplink communication process of the air-to-ground communication system;

[0035] The throughput optimization module is used to construct an original optimization model with maximizing throughput as the optimization goal and the power upper limit of the communication equipment as the constraint condition; the original optimization model is solved to obtain the maximum throughput of the uplink communication.

[0036] At least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects:

[0037] In the actual uplink communication data modulation process, discrete symbols are the mapping carriers between binary bit streams and data, and measure the actual data transmission rate. Therefore, in the throughput optimization method for uplink communication of the air-to-ground communication system provided by the present invention, mutual information is used to characterize the throughput of the air-to-ground uplink communication in view of the transmission problem of discrete symbols, rather than pursuing the theoretical maximum value under ideal conditions, so as to improve the robustness of the system under non-ideal conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0039] Figure 1 A schematic flow chart of a method for optimizing throughput of uplink communication in an air-to-ground communication system provided by the present invention;

[0040] Figure 2 A schematic diagram of the air-to-ground communication system provided by the present invention;

[0041] Figure 3 A schematic diagram of the optimization model algorithm flow provided by the present invention;

[0042] Figure 4 A data rate display diagram of different design methods provided by the present invention;

[0043] Figure 5 This is a relationship diagram between the signal-to-noise ratio and the data rate under different modulation orders provided by the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present application will be clearly and completely described below in combination with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] Since the integrated air-ground network is affected by factors such as channel fading and multipath effects, the low uplink transmission rate seriously limits the throughput of the integrated air-ground uplink communication. Therefore, how to effectively improve the signal transmission rate has become an inevitable and urgent task before the air-ground uplink transmission. Precoding, as a technology that can effectively improve the signal transmission quality in the communication system, has the ability to improve the transmission reliability of the integrated air-ground multi-hop network. Therefore, how to implement efficient precoding schemes in ground users and drone nodes has important research significance. Traditional optimization methods usually only design precoding for ground users, ignoring the bridging role of drones as relays in the integrated air-ground network. In addition, there may be a variety of interferences and changes in channel characteristics between ground users and aerial nodes. Therefore, only precoding design for ground users may not be able to achieve the anti-interference effect in a targeted manner, resulting in a decrease in the robustness of the integrated air-ground network. Joint precoding for ground users and drones can not only optimize the utilization of air resources, but also improve the transmission reliability. Therefore, the joint precoding design of ground users and drones has a further improvement effect on the uplink communication throughput of air-ground. From the perspective of existing technology, the air-ground uplink communication throughput optimization algorithm usually studies the communication system to calculate the transmission rate under the Gaussian input model. Although in theory the wireless communication system under Gaussian input can reach the channel capacity, that is, the theoretical upper limit described by Shannon's theorem, this does not apply to the actual modulation method based on constellation points, such as orthogonal amplitude modulation. The air-ground integrated network is a resource-constrained and computing-limited transmission system, which is limited by factors including bandwidth, power limitations, and noise interference. Therefore, building an effective transmission scheme is of positive significance to the construction of the air-ground integrated network and helps to implement the scheme as soon as possible. Specifically, for the actual discrete symbols, a rate function between the binary bit stream and the data is established, and by constructing a low-complexity coding optimization scheme, it is of great help to resource allocation and reliable operation of the system.

[0046] In this context, the present application proposes a joint precoding design method for optimizing the throughput of air-to-ground uplink communication based on amplification and forwarding relay. The present application uses mutual information to characterize the real data rate of the air-to-ground uplink for the transmission problem of discrete symbols. Since the function expression of mutual information lacks closure, it is proposed to use the cutoff rate to replace the non-closed mutual information expression, and then construct a concave maximization problem with a standard form, which reduces the computational complexity caused by the expected operation. However, since the precoding design is performed for ground users and drones at the same time, the two variables to be processed are highly coupled in the expression. In view of this, under the model of ground users, drones and satellite communication systems, for the integrated air-to-ground uplink communication with limited character input, the present application proposes a low-complexity solution based on alternating optimization: first, the relationship between the satellite receiving signal and the ground transmitting signal is used to obtain the mutual information of the discrete constellation to characterize the real data rate, and the optimization problem is constructed according to the power constraint; then a closed cutoff rate is given to replace the non-closed mutual information objective function, and then the original optimization problem is decomposed into two sub-problems according to the decoupling method; the two sub-problems are solved by the alternating optimization method, and then the optimal precoder is obtained and the maximum transmission rate is calculated. The present application is applicable to application scenarios of throughput optimization of uplink communication of an air-to-ground communication system, and can optimize the throughput of air-to-ground uplink communication.

[0047] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0048] Figure 1 A schematic flow chart of a method for optimizing throughput of uplink communication in an air-to-ground communication system of this embodiment is shown, which specifically includes the following steps:

[0049] S1: Construct an air-space-ground communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment.

[0050] An air-to-ground communication system is constructed as Figure 2 As shown in the figure, ground users are selected as ground-based communication equipment, drones as relay station communication equipment, and satellite communication equipment as the entity research objects of the communication system model to build an air-ground integrated uplink communication system model. The air-ground communication system specifically includes the following contents:

[0051] In the uplink transmission of the integrated space-ground network, the drone plays the role of a relay to bridge the communication between the ground user and the satellite. In the case considered, the ground user cannot communicate directly with the satellite due to limited access frequency. In the integrated space-ground network, in the first stage, when the ground user first transmits the modulation symbol x, the drone receives the signal y u It can be expressed as:

[0052] y u =H suP s x+n u (1)

[0053] in, represents the channel from the ground user to the UAV, and N s Represents the number of receiving antennas and transmitting antennas of the UAV and ground node respectively. In addition, Indicates transmission signal The precoder of It means that the mean on the drone is zero and the variance is The additive Gaussian white noise is Considering the electromagnetic propagation characteristics affected by the complex ground environment, H su Following the Rice channel fading model, that is:

[0054]

[0055] Where β∈[0,1] is the Rice factor, G LoS and G NLoS are LoS and Rayleigh fading components respectively.

[0056] In the second stage, the drone uses the amplification and forwarding protocol to transmit the received y u The signal is forwarded to the satellite. Then the signal received by the satellite is:

[0057] y s =h us P u y u +n s

[0058] =h us P u H su P s x+h us P u n u +n s (3)

[0059] in For the LoS channel from drone to satellite, is the number of transmitting antennas of the UAV, in addition, is used to integrate the signal y u The drone precoder. s is a satellite with mean zero and variance The additive thermal noise follows

[0060] S2: Modulate the data transmitted during the uplink communication from the ground-based communication equipment to the satellite communication equipment into discrete symbol form, obtain mutual information used to reflect the efficiency of discrete symbol information transmission, and use the mutual information to characterize the throughput of the uplink communication process of the air-to-ground communication system.

[0061] The mutual information of discrete input is used to characterize the transmission rate; the instantaneous mutual information expression is constructed based on the instantaneous signal-to-noise ratio. The mutual information based on finite character input is calculated, and the mutual information of discrete input is used to characterize the actual data rate:

[0062]

[0063] Where n = h us P u n u +n s Since mutual information is used to characterize the actual data rate, and the actual data rate can also characterize the throughput during communication, maximizing I is to maximize the throughput. t =N s is the number of transmitting antennas of the ground-based communication equipment, and M is the number of points in the signal constellation. ij =x i -x j , where x i and x j Indicates N in the M-ary constellation diagram t possible modulation symbol vectors, there are The number of possible combinations. Since two orthogonal time slots are required to complete the transmission of x from the ground user to the satellite via the drone, the above formula contains a factor of 1 / 2; E n (·) indicates the expectation operation.

[0064] S3: Construct an original optimization model with maximizing throughput as the optimization goal and the power upper limit of the communication equipment as the constraint condition; solve the original optimization model to obtain the maximum throughput of the uplink communication.

[0065] According to the actual limited character input constraint characteristics of two-segment communication, the optimization problem of maximizing the achievable average mutual information is constructed; with the maximization of the objective function (4) as the goal, the power constraint optimization problem can be expressed as:

[0066]

[0067]

[0068] Where (5b) and (5c) are the power constraints of ground users and UAVs, respectively. and are the actual power of ground users and UAVs, P s and Pu They are the upper limits of available power for ground users and UAVs, respectively.

[0069] Considering that the mutual information expression form is quite complex and the variables to be processed are highly coupled in the non-closed noise sampling expression, it is difficult to handle. In order to facilitate the analysis and optimize the design of the precoder to improve the mutual information performance, the variables to be processed are alternately optimized to establish a practical solution with low computational complexity. The first step is to decompose the original optimization problem into two sub-problems; specifically, the following are included:

[0070] First, a closed form is given using the cutoff rate to replace I(x; y s |H su ,h us ), which is actually I(x;y s |H su ,h us ). This reduces the computational complexity caused by the expected operation. The cutoff rate associated with the integrated air-ground network based on amplify-and-forward relay can be expressed as:

[0071]

[0072] The substitution in (6) optimizes the efficiency by removing a large number of noise samples. However, it can be noted that the difficulty now lies in how to design an effective method to optimize the variable pair (P s ,P u ). Finally, we choose to use an iterative method to optimize P alternately. s and P u .

[0073] Use R(P s ,P u ) instead of I(x;y s |H su ,h us ), the original optimization problem (5) is decomposed into two sub-problems, namely:

[0074]

[0075] and

[0076]

[0077] in

[0078]

[0079] In the formula, and Respectively represent P u and P s Known feasible solutions of .

[0080] Iteratively optimize the two sub-problems until the set iteration termination conditions are reached, and output the optimization results to obtain the maximum throughput.

[0081] Preferred given P u Optimize P s : In P u When is fixed, the lower bound of the objective function is obtained through Taylor expansion, thus obtaining a convex optimization problem. In a fixed situation, the problem can be solved with the help of an iterative mechanism (7). The lower bound of can be obtained by first-order Taylor expansion, which is at the feasible point P s0 The linear expansion at P is quadratic, forming s A linear function of:

[0082]

[0083] in The basis for the establishment of inequality (11) is:

[0084]

[0085] In use The lower bound After replacing it, it is easy to verify is a linear function and log 2 The compound of ∑exp, log 2 ∑exp for P s is convex. Therefore, given The optimal P can be obtained by iteratively solving the following convex optimization problem. s :

[0086]

[0087] Then given P s Optimize P u :Solve the problem of s Next and P u Related optimization problems. Optimize the objective function by calling auxiliary variables and other methods, and write related optimization problems.

[0088] In problem (8), because P u At the same time In order to solve this problem, Re-expressed as the ratio of two convex functions, it looks like this:

[0089]

[0090] in

[0091] Considering (14) Due to the non-convexity of , we call an auxiliary variable ζ to reformulate problem (8) as:

[0092]

[0093] In order to solve the problem conveniently, given P s Next and P u The related optimization problem proposes the relevant Theorem 1 and proves it, and then the final convex optimization problem is obtained based on Theorem 1.

[0094] Since the optimization problem in (15) is still inconvenient to solve, Theorem 1 is proposed to further improve the optimization problem.

[0095] The specific content of Theorem 1 is: For any semi-positive definite matrix in the numerator of (14) function Relative to p u and ζ>0 are jointly convex.

[0096] Proof: A function is convex if and only if its overlay is a convex set. Using this, we can prove that the function For p u and ζ convexity. For f(p u ,ζ), its upper boundary graph can be expressed as:

[0097]

[0098] represents the field of real numbers, where z represents the function A photogenic graph of . Considering its associated linear matrix inequality:

[0099]

[0100] Combined with D ij ±0, then according to the Schur complement of the semi-positive definite matrix we can get:

[0101]

[0102] It can be further expressed as:

[0103]

[0104] Therefore, we can know that f(p u ,ζ) is the intersection of a strict linear matrix inequality and a non-strict linear matrix inequality, both of which are convex sets. As the intersection of two convex sets, f(p u ,ζ) is also a convex set, so f(pu ,ζ) is about p u is the jointly convex function of and ζ.

[0105] Proof completed.

[0106] When D ij ±0 and ζ>0, according to Theorem 1 In p u0 and 0 Expand it to get its lower bound:

[0107]

[0108] It is for P u and ζ are both affine.

[0109] use replace The above convex minimization problem is transformed into P u Optimize, expressed as:

[0110]

[0111] The optimized P obtained above s Substitute into this optimization problem to obtain the optimal P u value, and then the obtained optimized P u Substitute into the previous solution to find the optimal P s The optimization problem is to find a new optimal P s , and then the new optimized P s Substitute into the optimal P u Find the new optimal P in the optimization problem u . Keep looping until the optimal P is found s and P u , that is, the optimal precoder is found.

[0112] Figure 3 The algorithm flow chart of the throughput optimization method of the uplink communication of the air-to-ground communication system is shown. The method first constructs an air-to-ground integrated uplink communication system model, then obtains the mutual information based on the limited character input, then constructs the optimization problem and decomposes the optimization problem, and finally iterates the decomposed optimization sub-optimization model until the set iteration termination condition is reached to obtain the optimal precoder, and optimizes the throughput based on the optimal precoder. The throughput optimization method of the uplink communication of the air-to-ground communication system proposed in this application has the following advantages:

[0113] (1) According to the power constraint characteristics of actual discrete symbol input, a closed-form optimization problem for maximizing the achievable data rate is constructed.

[0114] (2) Using the lower bound cutoff rate of mutual information instead of mutual information for optimization gives a closed expression and reduces the computational complexity caused by expectation operation;

[0115] (3) The problem of difficulty in optimizing the objective function due to the high coupling of multiple variables in the non-closed noise sampling expression is solved. The original problem is decomposed into two sub-problems for alternating optimization, which reduces the optimization difficulty and makes the analysis and design of the precoder more convenient.

[0116] In order to show the correctness and effectiveness of the above derivation results, the advantages of the proposed throughput optimization algorithm for joint ground user and UAV precoding are further verified through simulation. The specific simulation parameters are set as follows: Number of ground user transmitting antennas N s and the number of transmitting antennas of the drone are both 2, the algorithm’s iteration termination condition ε=0.001, and the noise levels at the drone and satellite are equal (i.e. ), the lower bound of the mutual information, i.e., the cutoff rate, is used to represent the data rate. At the same time, a pair of P that meets the power limit and whose power can reach the maximum value is selected. s and P u , and the maximum ratio combining (MRC) method was used as the control group. The number of antennas in the control group N = 2, the modulation order M = 4, which is the same as the given optimization algorithm. Figure 4 The comparison between the control group method and the optimization algorithm of the present invention also illustrates the advantages of this optimization algorithm. The optimized precoder can not only make the data rate reach the maximum value faster, but also outperform the control group before reaching the maximum value.

[0117] Figure 5 This also proves the effectiveness of the algorithm. Figure 5 The change of the achievable data rate is observed by changing the modulation order. The results show that the achievable data rate increases with the increase of the modulation order. M=2, M=4 and M=8, the corresponding maximum achievable data rate performance is 1bits / s / Hz, 2bits / s / Hz and 3bits / s / Hz, which is also completely consistent with the rate expression. Overall, when M is fixed, the achievable rate will not continue to increase with the signal-to-noise ratio (SNR), but will reach saturation when it reaches a certain level.

[0118] When applying the throughput optimization method for uplink communication of the air-to-ground communication system provided by the present invention, it is not necessary to Figure 1 The steps are executed in the order shown. The specific execution order of the steps can be determined according to needs, and the present invention does not limit this.

[0119] The above is a method for optimizing the throughput of uplink communication of an air-to-ground communication system provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding device for optimizing the throughput of uplink communication of an air-to-ground communication system, including:

[0120] The air-to-ground communication system building module is used to build an air-to-ground communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment.

[0121] The throughput characterization module is used to modulate the data transmitted during the uplink communication from the ground-based communication equipment to the satellite communication equipment into a discrete symbol form, obtain mutual information used to reflect the efficiency of discrete symbol information transmission, and use the mutual information to characterize the throughput of the uplink communication process of the air-to-ground communication system.

[0122] The throughput optimization module is used to construct an original optimization model with maximizing throughput as the optimization goal and the power upper limit of the communication equipment as the constraint condition; the original optimization model is solved to obtain the maximum throughput of the uplink communication.

[0123] For the specific definition of the throughput optimization device for uplink communication of the air-to-ground communication system, please refer to the definition of the throughput optimization method for uplink communication of the air-to-ground communication system mentioned above, which will not be repeated here. Each module in the above-mentioned throughput optimization device for uplink communication of the air-to-ground communication system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0124] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0125] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

Claims

1. A method for optimizing the throughput of uplink communication in an air-to-ground communication system, characterized in that: include: Construct an air-ground communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment; Modulate the data transmitted during the uplink communication from the ground-based communication equipment to the satellite communication equipment into a discrete symbol form, obtain mutual information for reflecting the efficiency of discrete symbol information transmission, and use the mutual information to characterize the throughput of the uplink communication process of the air-to-ground communication system; The original optimization model is constructed with maximizing throughput as the optimization goal and the power upper limit of the communication equipment as the constraint; The original optimization model is solved to obtain the maximum throughput of uplink communication.

2. The method for optimizing the throughput of uplink communication in an air-to-ground communication system according to claim 1, characterized in that: The air-ground-space communication system is constructed based on ground-based communication equipment, relay station communication equipment and satellite communication equipment, including: The relay station communication equipment receives the signal transmitted by the ground-based communication equipment: y u =H su P s x+n u in, It is the signal received by the communication equipment of the relay station. is the number of receiving antennas of the relay station communication equipment; N represents the channel from the ground-based communication equipment to the relay station communication equipment. s Indicates the number of transmitting antennas of ground-based communication equipment; Indicates transmission signal Precoder of means that the mean is zero and the variance is Additive Gaussian white noise, β∈[0,1] is the Rice factor in the Rice channel fading model; G LoS and G NLoS They are the LoS and Rayleigh fading components in the Rice channel fading model, respectively; The relay station communication equipment forwards the received signal to the satellite communication equipment using the amplification and forwarding protocol: y s =h us P u y u +n s Among them, y s It is the signal received by satellite communication equipment; It is the LoS channel from the relay station communication equipment to the satellite communication equipment. The number of transmitting antennas for the relay station communication equipment; is used to integrate the signal y u The relay station communication equipment precoder; n s is zero and has a variance of The additive thermal noise follows 3. The method for optimizing the throughput of uplink communication in an air-to-ground communication system according to claim 2, characterized in that: Characterizing the throughput of the uplink communication process of the air-to-ground communication system by mutual information specifically includes: n=h us P u n u +n s Among them, I(x; y s |H su ,h us ) represents the throughput of the uplink communication process, N t is the number of transmitting antennas of the ground-based communication equipment; M is the number of points in the signal constellation; d ij =x i -x j , where x i and x j Indicates N in the M-ary constellation diagram t possible modulation symbol vectors; E n (·) indicates the expectation operation.

4. The method for optimizing the throughput of uplink communication in an air-to-ground communication system according to claim 3, characterized in that: The original optimization model is constructed with maximizing throughput as the optimization goal and the power upper limit of the communication device as the constraint condition, specifically including: in, and are the actual powers of the ground-based communication equipment and the relay station communication equipment, respectively. The superscript H represents the conjugate transpose; P s and P u They are the upper limits of available power for ground-based communication equipment and relay station communication equipment respectively.

5. The method for optimizing the throughput of uplink communication in an air-to-ground communication system according to claim 4, characterized in that: The solving of the original optimization model specifically includes: Use cut-off rate Instead of I(x;y s |H su ,h us ) to reduce the computational complexity of the original optimization model; I(x;y s |H su ,h us ) is replaced by the original optimization model with the cutoff rate and decomposed into sub-optimization model 1 and sub-optimization model 2; The sub-optimization model is As the optimization objective, the power upper limit of the ground-based communication equipment is used as the constraint condition, where: Indicates P u A known feasible solution of ; The sub-optimization model is is the optimization target, and the power upper limit of the relay station communication equipment is the constraint condition; in, Indicates P s A known feasible solution of ; Iteratively optimize sub-optimization model 1 and sub-optimization model 2 until the set iteration termination condition is reached, and output the optimization results to obtain the maximum throughput.

6. A throughput optimization device for uplink communication of an air-to-ground communication system, characterized in that: include: An air-ground-space communication system building module, which is used to build an air-ground-space communication system based on ground-based communication equipment, relay station communication equipment and satellite communication equipment; The throughput characterization module is used to modulate the data transmitted during the uplink communication from the ground-based communication equipment to the satellite communication equipment into a discrete symbol form, obtain mutual information for reflecting the transmission efficiency of the discrete symbol information, and use the mutual information to characterize the throughput of the uplink communication process of the air-to-ground communication system; The throughput optimization module is used to construct the original optimization model with maximizing throughput as the optimization goal and the power upper limit of the communication equipment as the constraint condition; The original optimization model is solved to obtain the maximum throughput of uplink communication.

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