Joint optimization method and apparatus based on rate maximization and antenna selection

Abstract

The application provides a joint optimization method and device based on rate maximization and antenna selection, comprising: establishing a multi-antenna bidirectional relay amplify-and-forward system model; obtaining a system information rate expression according to the system model; constructing an amplify-and-forward factor and an antenna selection sequence optimization variable; combining the information rate expression to obtain a maximum information rate composite function about the amplify-and-forward factor and the antenna selection sequence, and establishing an optimization problem; and obtaining an analytical expression of the optimal amplify-and-forward factor and the antenna selection sequence under power constraint according to the maximum information rate function. Thus, the joint optimization design of the amplify-and-forward factor and the antenna selection sequence in the multi-antenna relay repeater is realized, the spatial diversity and cooperation diversity gain of the relay repeater system is fully exploited, the information rate of the system is effectively improved, and the complexity is low.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and more specifically, to a joint optimization method and apparatus based on rate maximization and antenna selection. Background Technology

[0002] In the early 21st century, cooperative relay technology was proven to provide cooperative diversity for relay networks, thereby increasing system capacity.

[0003] In recent years, scholars have studied schemes such as distributed space-time codes, digital beamforming, and coherent combining to explore cooperative diversity in relay systems. Traditional research mainly focuses on the combined effects of distributed space-time codes, digital beamforming, and coherent combining schemes. There are also methods that achieve near-optimal beamforming through generalized power iteration, but the solution process is complex and computationally expensive. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a joint optimization method and apparatus based on rate maximization and antenna selection.

[0005] In a first aspect, embodiments of this application provide a joint optimization method based on rate maximization and antenna selection, including:

[0006] Step 1: In the first time slot, the source node transmits a wireless signal to the relay node through the uplink channel; wherein the source node acts as a single-antenna transmitter and the relay node acts as a multi-antenna receiver.

[0007] Step 2: The relay forwarding node amplifies and forwards the received signal vector, and establishes a preliminary optimization problem with the information rate maximization as the objective function and the total transmission power of the relay forwarding node as the constraint.

[0008] Step 3: Match and select the uplink signal and downlink channel, introduce the antenna selection sequence, and extend the preliminary optimization problem into a joint optimization problem of amplifying the forwarding factor and the antenna selection sequence;

[0009] Step 4: Decouple the joint optimization problem of the amplification and forwarding factor and the antenna selection sequence to obtain the globally optimal amplification and forwarding factor and the antenna selection sequence;

[0010] Step 5: In the second time slot, the relay forwarding node transmits a wireless signal to the destination node via the downlink channel according to the globally optimal amplification forwarding factor and the antenna selection sequence; wherein, the relay forwarding node acts as a multi-antenna transmitter, the destination node acts as a single-antenna receiver, and the destination node processes the received signal to parse out the transmitted symbol.

[0011] Optionally, the joint optimization problem of the amplified forwarding factor and the antenna selection sequence in step 3 is as follows:

[0012]

[0013] Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. m Let P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let γ represent the complex additive white Gaussian noise variances of the relay node and the destination node receiver, respectively. Let γ represent the signal-to-noise ratio received at the destination node. The optimization objective is w. m Let p(m) be the amplification and forwarding factor matched by the m-th antenna. p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, which represents the signal amplified by the m-th receiving antenna of the relay forwarding node and forwarded to the destination node through the p(m)-th antenna.

[0014] Optionally, the formula for calculating the globally optimal amplification forwarding factor in step 4 is as follows:

[0015]

[0016] Where: w = [w m ,…w m …w M ] T To amplify the forwarding vector, ζ is the normalization factor, g1 is the channel coefficient from the first antenna of the relay forwarding node to the destination node, h1 is the channel coefficient from the source node to the first antenna of the relay forwarding node, and g M h is the channel coefficient from the Mth antenna of the relay node to the destination node. M Let T be the channel coefficient of the Mth antenna from the source node to the relay node, and T be the transpose operator.

[0017] Optionally, in step 4, it is assumed that |h1|≥|h2|≥…|h M |, then |g p(1) |≥|g p(2) |≥…|g p(M) | p(m) is the optimal antenna selection sequence.

[0018] Optionally, in step 5, the formula for calculating the signal-to-noise ratio received at the destination node is as follows:

[0019]

[0020] Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. m Let P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let represent the complex Gaussian additive white noise variances of the relay node and the destination node receiver, respectively; let γ represent the signal-to-noise ratio received by the destination node; p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, representing the signal amplified by the m-th receiving antenna of the relay node and forwarded to the destination node through the p(m)-th antenna.

[0021] Secondly, embodiments of this application provide a joint optimization device based on rate maximization and antenna selection, comprising: a network architecture consisting of a source node and relay forwarding nodes, wherein:

[0022] The source node is used to transmit wireless signals to the relay node through the uplink channel in the first time slot; the source node acts as a single-antenna transmitter, and the relay node acts as a multi-antenna receiver.

[0023] The relay forwarding node is used to amplify and forward the received signal vector, and to establish a preliminary optimization problem with the information rate maximization as the objective function and the total transmission power of the relay forwarding node as the constraint.

[0024] The matching module is used to match and select the uplink signal and the downlink channel, introduces the antenna selection sequence, and extends the preliminary optimization problem into a joint optimization problem of amplifying the forwarding factor and the antenna selection sequence.

[0025] The decoupling module is used to decouple the joint optimization problem of the amplification and forwarding factor and the antenna selection sequence, so as to obtain the globally optimal amplification and forwarding factor and the antenna selection sequence.

[0026] Relay forwarding node: It is also used in the second time slot to send wireless signals to the destination node by relying on the downlink channel according to the globally optimal amplification forwarding factor and antenna selection sequence; wherein, the relay forwarding node acts as a multi-antenna transmitter, the destination node acts as a single-antenna receiver, and the destination node processes the received signal to parse out the transmitted symbol.

[0027] Alternatively, the joint optimization problem of amplifying the transponder factor and the antenna selection sequence is as follows:

[0028]

[0029] Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. m Let P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let γ represent the complex additive white Gaussian noise variances of the relay node and the destination node receiver, respectively. Let γ represent the signal-to-noise ratio received at the destination node. The optimization objective is w. m Let p(m) be the amplification and forwarding factor matched by the m-th antenna. p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, which represents the signal amplified by the m-th receiving antenna of the relay forwarding node and forwarded to the destination node through the p(m)-th antenna.

[0030] Optionally, the formula for calculating the globally optimal amplification forwarding factor is as follows:

[0031]

[0032] Where: w = [w m ,…w m ,…w M ] T To amplify the forwarding vector, ζ is the normalization factor, g1 is the channel coefficient from the first antenna of the relay forwarding node to the destination node, h1 is the channel coefficient from the source node to the first antenna of the relay forwarding node, and g M h is the channel coefficient from the Mth antenna of the relay node to the destination node. M Let T be the channel coefficient of the Mth antenna from the source node to the relay node, and T be the transpose operator.

[0033] Alternatively, assume that |h1|≥|h2|≥…|h M |, then |g p(1) |≥|g p(2) |≥…|g p(M) | p(m) is the optimal antenna selection sequence.

[0034] Optionally, the formula for calculating the signal-to-noise ratio received at the destination node is as follows:

[0035]

[0036] Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. mLet P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let represent the complex Gaussian additive white noise variances of the relay node and the destination node receiver, respectively; let γ represent the signal-to-noise ratio received by the destination node; p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, representing the signal amplified by the m-th receiving antenna of the relay node and forwarded to the destination node through the p(m)-th antenna.

[0037] Thirdly, embodiments of this application provide a joint optimization device based on rate maximization and antenna selection, comprising: a processor and a memory, wherein the memory stores executable program instructions, and when the processor invokes the program instructions in the memory, the processor is used to:

[0038] Perform the steps of the joint optimization method based on rate maximization and antenna selection as described in any one of the first aspects.

[0039] Fourthly, embodiments of this application provide a computer-readable storage medium for storing a program, which, when executed, implements the steps of the joint optimization method based on rate maximization and antenna selection as described in any one of the first aspects.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] This application mainly focuses on multi-antenna relay systems, proposing a joint optimization scheme based on rate maximization and antenna selection, and deriving its analytical expression. This scheme can fully exploit the spatial diversity and cooperative diversity gains of the system, and has the advantage of low complexity due to its analytical expression. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort. Other features, objects, and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0043] Figure 1 A flowchart illustrating a joint optimization method based on rate maximization and antenna selection, provided for embodiments of this application;

[0044] Figure 2 This is a schematic diagram illustrating an application scenario of an embodiment of this application;

[0045] Figure 3 This is a comparison chart showing the antenna selection performance of the method in this application embodiment compared to the exhaustive search algorithm;

[0046] Figure 4 This is a comparison chart showing the amplification and forwarding performance of the method in this application embodiment compared to the traditional coherent merging algorithm. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] It should be noted that when a component is said to be "fixed" to another component, it can be directly on the other component or it can be in a middle component. When a component is said to be "connected" to another component, it can be directly connected to the other component or it may be in a middle component.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0050] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0051] The technical solutions of the present invention and how they solve the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0052] Figure 1 A flowchart of a joint optimization method based on rate maximization and antenna selection provided for embodiments of this application is shown below. Figure 1 As shown, the method in this embodiment may include:

[0053] Step 1: In the first time slot, the source node transmits a wireless signal to the relay node through the uplink channel; wherein, the source node acts as a single-antenna transmitter and the relay node acts as a multi-antenna receiver.

[0054] Figure 2 This is a schematic diagram illustrating an application scenario of an embodiment of this application, such as... Figure 2 As shown, user A constitutes the source node, user B constitutes the destination node, and signal transmission between user A and user B is achieved through a relay station (relay forwarding node).

[0055] In this embodiment, a three-node relay system model is given, consisting of a source node, a relay forwarding node, and a destination node. The source and destination nodes each use a single antenna for both transmission and reception, while the relay forwarding node is configured with M receiving and transmitting antennas.

[0056] In the first time slot, the signal r received by the m-th antenna of the relay node m It can be represented as:

[0057] r m =h m s+n RS,m

[0058] In the formula, h m Let n be the channel coefficient from user A to the m-th antenna of the relay station. RS,m This indicates that the mean is 0 and the variance is . Complex Gaussian additive white noise.

[0059] Step 2: The relay node amplifies and forwards the received signal vector, and establishes a preliminary optimization problem with the information rate maximization as the objective function and the total transmission power of the relay node as the constraint.

[0060] Step 3: Match and select the uplink signal and downlink channel, introduce the antenna selection sequence, and extend the initial optimization problem into a joint optimization problem of amplifying the forwarding factor and the antenna selection sequence.

[0061] For example, the joint optimization problem of the amplified forwarding factor and the antenna selection sequence in step 3 is as follows:

[0062]

[0063] Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. m Let P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let γ represent the complex additive white Gaussian noise variances of the relay node and the destination node receiver, respectively. Let γ represent the signal-to-noise ratio received at the destination node. The optimization objective is w. m Let p(m) be the amplification and forwarding factor matched by the m-th antenna. p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, which represents the signal amplified by the m-th receiving antenna of the relay forwarding node and forwarded to the destination node through the p(m)-th antenna.

[0064] Step 4: Decouple the joint optimization problem of the amplification forwarding factor and the antenna selection sequence to obtain the globally optimal amplification forwarding factor and antenna selection sequence.

[0065] For example, the formula for calculating the globally optimal amplification forwarding factor in step 4 is as follows:

[0066]

[0067] Where: w = [w m ,…w m ,…w M ] T To amplify the forwarding vector, ζ is the normalization factor, g1 is the channel coefficient from the first antenna of the relay forwarding node to the destination node, h1 is the channel coefficient from the source node to the first antenna of the relay forwarding node, and g M h is the channel coefficient from the Mth antenna of the relay node to the destination node. M Let T be the channel coefficient of the Mth antenna from the source node to the relay node, and T be the transpose operator.

[0068] Optionally, in step 4, it is assumed that |h1|≥|h2|≥…|h M |, then |g p(1) |≥|g p(2) |≥…|g p(M) | p(m) represents the optimal antenna selection sequence. Essentially, it is the uplink and downlink channels arranged sequentially according to channel quality.

[0069] Step 5: In the second time slot, the relay forwarding node transmits a wireless signal to the destination node using the downlink channel based on the globally optimal amplification and forwarding factor and the antenna selection sequence. The relay forwarding node acts as a multi-antenna transmitter, and the destination node acts as a single-antenna receiver. After receiving the signal, the destination node processes the signal to parse out the transmitted symbol.

[0070] For example, in step 5, the formula for calculating the signal-to-noise ratio received by the destination node is as follows:

[0071]

[0072] Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. m Let P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let represent the complex Gaussian additive white noise variances of the relay node and the destination node receiver, respectively; let γ represent the signal-to-noise ratio received by the destination node; p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, representing the signal amplified by the m-th receiving antenna of the relay node and forwarded to the destination node through the p(m)-th antenna.

[0073] In the second time slot, the relay node amplifies and performs antenna selection mapping on the m-th received signal, denoted as the amplification and forwarding factor w. m If the antenna selection factor is p(m), then the received signal r m The signal transmitted by the p(m)th antenna of the relay node can be expressed as:

[0074] x p(m) =w m r m =w m (h m s+n RS,m )

[0075] The signal received by the destination node should be:

[0076]

[0077] To eliminate the effect of phase on the useful signal, the phase of the signals from each antenna must first be aligned, i.e., arg(w m g p(m) h m ) = θ. At this point, the signal-to-noise ratio received at the destination node can be expressed as:

[0078]

[0079] Where w = [|w1|,|w2|,...,|w M |] T , t p =[|g p(1) ||h1|,|g p(2) ||h2|,...,|g p(M) ||h M |] T ,

[0080] To design the optimal amplification and forwarding factor and antenna selection algorithm to maximize the received signal-to-noise ratio, the following joint optimization problem is established:

[0081]

[0082] stp∈S P ,w±0,w T Cw = 1

[0083] Among them, S p Let S represent the set of all permutations and combinations of the sequence {1,2,…,M}. p Since it is a finite set, the above optimization objective can be further expressed as:

[0084]

[0085] In other words, global optimization can be achieved by first optimizing w and then optimizing p. Based on this, the optimal amplification and forwarding factor is obtained using the Rayleigh-Ritz theorem, and the optimal antenna selection sequence is obtained using inequality theorems.

[0086] As attached Figure 3 As shown, the antenna selection algorithm in this invention is completely consistent with the exhaustive search algorithm in terms of information rate, proving that this invention obtains the optimal antenna selection result through derivation.

[0087] As attached Figure 4 As shown, compared with traditional coherent combining algorithms, the amplification forwarding factor obtained by this invention with rate as the optimization objective can bring higher data rates. After introducing the antenna selection algorithm, the data rate of the relay system is further improved, and approximately 2dB of spatial diversity gain can be achieved in the medium-to-high signal-to-noise ratio region.

[0088] This embodiment establishes a system model of a multi-antenna bidirectional repeater amplifier-transponder; obtains the system's information rate expression based on the model; constructs optimization variables for the amplification-transponder factor and antenna selection sequence; combines the aforementioned information rate expression to obtain a composite function maximizing the information rate with respect to the amplification-transponder factor and antenna selection sequence, establishing an optimization problem; and obtains analytical expressions for the optimal amplification-transponder factor and antenna selection sequence under power constraints based on the maximized information rate function. By utilizing spatial diversity and cooperative diversity gains to improve the efficiency of the multi-antenna repeater, the joint optimization design of the amplification-transponder factor and antenna selection sequence in the multi-antenna repeater is achieved, fully exploiting the spatial diversity and cooperative diversity gains of the relay system, effectively improving the system's information rate, and exhibiting low complexity.

[0089] Furthermore, embodiments of this application provide a joint optimization apparatus based on rate maximization and antenna selection, comprising: a network architecture consisting of a source node and relay forwarding nodes, wherein:

[0090] The source node is used to transmit wireless signals to the relay node via the uplink channel in the first time slot; the source node acts as a single-antenna transmitter, and the relay node acts as a multi-antenna receiver.

[0091] The relay forwarding node is used to amplify and forward the received signal vector. The initial optimization problem is established with the information rate maximization as the objective function and the total transmission power of the relay forwarding node as the constraint.

[0092] The matching module is used to match and select the uplink signal and the downlink channel. It introduces an antenna selection sequence, which expands the initial optimization problem into a joint optimization problem of amplified forwarding factor and antenna selection sequence.

[0093] The decoupling module is used to decouple the joint optimization problem of the amplification and forwarding factor and the antenna selection sequence, so as to obtain the globally optimal amplification and forwarding factor and the antenna selection sequence.

[0094] Relay forwarding node: It is also used in the second time slot to send wireless signals to the destination node by relying on the downlink channel according to the globally optimal amplification forwarding factor and antenna selection sequence; wherein, the relay forwarding node acts as a multi-antenna transmitter and the destination node acts as a single-antenna receiver. After receiving the signal, the destination node processes the signal to parse out the transmitted symbol.

[0095] This application provides a joint optimization device based on rate maximization and antenna selection, including: a processor and a memory, wherein the memory stores executable program instructions, and when the processor calls the program instructions in the memory, the processor is used to: execute the steps of the joint optimization method based on rate maximization and antenna selection described above.

[0096] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "platform."

[0097] Furthermore, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions, wherein when at least one processor of a user device executes the computer-executable instructions, the user device performs the various possible methods described above.

[0098] Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of computer programs from one place to another. Storage media can be any available medium accessible to a general-purpose or special-purpose computer. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a user device. Of course, the processor and storage medium can also exist as discrete components in a communication device.

[0099] This application also provides a program product including a computer program stored in a readable storage medium. At least one processor of the server can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the server to implement any of the methods described in the embodiments of the present invention.

[0100] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0101] It can employ a portable compact disc read-only memory (CD-ROM) and include program code, and can run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0102] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0103] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0104] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0105] The various embodiments described in this specification are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0106] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A joint optimization method based on rate maximization and antenna selection, characterized in that, Comprising: Step 1: in the first time slot, the source node transmits wireless signals to the relay forwarding node through the uplink channel; wherein the source node acts as a single antenna transmitter, and the relay forwarding node acts as a multi-antenna receiver; Step 2: the relay forwarding node amplifies and forwards the received signal vector, and establishes a preliminary optimization problem with the maximum information rate as the objective function and the total power of the relay forwarding node transmission as the constraint; Step 3: the uplink signal and the downlink channel are matched and selected, an antenna selection sequence is introduced, and the preliminary optimization problem is expanded into a joint optimization problem of the amplification forwarding factor and the antenna selection sequence; Step 4: the joint optimization problem of the amplification forwarding factor and the antenna selection sequence is decoupled to obtain the globally optimal amplification forwarding factor and the antenna selection sequence; Step 5: in the second time slot, the relay forwarding node sends wireless signals to the destination node according to the globally optimal amplification forwarding factor and the antenna selection sequence through the downlink channel; wherein the relay forwarding node acts as a multi-antenna transmitter, and the destination node acts as a single antenna receiver, and the destination node parses the transmitted symbols after receiving the signals through signal processing; the optimal amplification forwarding factor is obtained by Rayleigh-Ritz method theorem, and the optimal antenna selection sequence is obtained by inequality theorem. 2.The joint optimization method based on rate maximization and antenna selection according to claim 1, characterized in that, The joint optimization problem of the amplification forwarding factor and the antenna selection sequence in step 3 is as follows: where M is the number of antennas of the relay forwarding node, h m is the channel coefficient from the source node to the mth antenna of the relay forwarding node, g m is the channel coefficient from the mth antenna of the relay forwarding node to the destination node, P S is the transmit power of the source node, P RS denotes the average transmit power per antenna of the relay forwarding node, and denote the complex Gaussian additive white noise variance of the relay forwarding node and the destination node receiver respectively, the objective function γ denotes the received signal-to-noise ratio of the destination node, the optimization objective w m is the matched amplify-and-forward factor of the mth antenna, p(m) ∈ p, p = {p(1), p(2), … p(M)} is defined as a group of permutations of the sequence {1, 2, …, M}, and denotes that the signal received by the mth receiving antenna of the relay forwarding node is amplified and then forwarded to the destination node through the p(m)th antenna; |w m | 2 denotes the square of the absolute value of w m , denotes the maximum value of the objective function γ, g p(m) denotes the channel coefficient from the p(m)th antenna of the relay forwarding node to the destination node. 3.The joint optimization method based on rate maximization and antenna selection according to claim 2, characterized in that, The calculation formula of the globally optimal amplification forwarding factor in step 4 is as follows: wherein: w = [w m ,…w m ,…w M ] T is an amplify-and-forward vector, ζ is a normalization factor, g1is a channel coefficient from the 1st antenna of the relay forwarding node to the destination node, h1is a channel coefficient from the source node to the 1st antenna of the relay forwarding node, g M is a channel coefficient from the Mth antenna of the relay forwarding node to the destination node, h M is a channel coefficient from the source node to the Mth antenna of the relay forwarding node, and T is a transpose operator.

4. The joint optimization method based on rate maximization and antenna selection according to claim 3, characterized in that, In step 4, assume that |h1| ≥ |h2| ≥... |h M |, then make |g p(1) | ≥ |g p(2) | ≥... |g p(M) | the optimal antenna selection sequence, g p(1) represents the channel coefficient from the p(1)th antenna of the relay forwarding node to the destination node, g p(2) represents the channel coefficient from the p(2)th antenna of the relay forwarding node to the destination node, g p(M) represents the channel coefficient from the p(M)th antenna of the relay forwarding node to the destination node.

5. The method of joint optimization based on rate maximization and antenna selection according to claim 1, characterized in that, In step 5, the calculation formula of the signal-to-noise ratio of the destination node is as follows: Where: M is the number of relay relay node antennas, h m Let g be the channel coefficient of the m-th antenna from the source node to the relay node. m Let P be the channel coefficient from the m-th antenna of the relay node to the destination node. S P is the source node transmit power. RS This represents the average daily transmit power of the relay node. and Let represent the complex Gaussian additive white noise variances of the relay node and the destination node receiver, respectively; γ represents the signal-to-noise ratio received at the destination node; p(m)∈p, p={p(1),p(2),…p(M)} is defined as a permutation of the sequence {1,2,…,M}, representing the signal amplified by the m-th receiving antenna of the relay node and relayed to the destination node through the p(m)-th antenna; p*(m)∈P*, p * ={p * (1),p * (2),…p * (M)} represents the optimal antenna selection sequence, |g p*(m) | 2 This represents the squared modulus of the channel coefficient from the p*(m)th antenna of the relay node to the destination node.

6. A device for joint optimization based on rate maximization and antenna selection, characterized in that, Comprising: A network architecture composed of a source node and a relay forwarding node, wherein: The source node is configured to transmit wireless signals to the relay forwarding node through the uplink channel in the first time slot; the source node acts as a single antenna transmitter, and the relay forwarding node acts as a multi-antenna receiver; The relay forwarding node is configured to amplify and forward the received signal vector, and establish a preliminary optimization problem with the maximum information rate as the objective function and the total power of the relay forwarding node transmission as the constraint; A matching module is configured to match and select the uplink signal and the downlink channel, introduce an antenna selection sequence, and expand the preliminary optimization problem into a joint optimization problem of the amplification forwarding factor and the antenna selection sequence; A decoupling module is configured to decouple the joint optimization problem of the amplification forwarding factor and the antenna selection sequence to obtain the globally optimal amplification forwarding factor and the antenna selection sequence; The relay forwarding node is further configured to send wireless signals to the destination node according to the globally optimal amplification forwarding factor and the antenna selection sequence through the downlink channel in the second time slot; wherein the relay forwarding node acts as a multi-antenna transmitter, and the destination node acts as a single antenna receiver, and the destination node parses the transmitted symbols after receiving the signals through signal processing; the optimal amplification forwarding factor is obtained by Rayleigh-Ritz method theorem, and the optimal antenna selection sequence is obtained by inequality theorem.

7. A device for joint optimization based on rate maximization and antenna selection, characterized in that Comprising: A processor and a memory, the memory storing executable program instructions, and the processor calling the program instructions in the memory, the processor being configured to: performing the steps of the joint optimization method based on rate maximization and antenna selection of any of claims 1 to 5.

8. A computer readable storage medium for storing a program, characterized in that, said program, when executed, implements the steps of the joint optimization method based on rate maximization and antenna selection of any of claims 1 to 5.

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