Method and device for optimizing throughput of relay cooperation network with energy-carrying transmission

Abstract

The application provides a method and device for optimizing throughput of a signal-energy-carrying transmission relay cooperation network, and belongs to the technical field of wireless communication. The method comprises the following steps: determining network parameters of the signal-energy-carrying transmission relay cooperation network; and based on the network parameters, obtaining the optimal throughput of the signal-energy-carrying transmission relay cooperation network through a throughput optimization function. The throughput optimization function is determined based on a calculation function of outage probability of the signal-energy-carrying transmission relay cooperation network, and variables in the calculation function of the outage probability comprise the network parameters. The embodiment of the application establishes an optimization problem with the target of obtaining the optimal throughput, and adopts an optimization algorithm to obtain the optimal network throughput, which is not only beneficial to finding the optimal throughput of the network, but also simple in calculation.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, specifically to a method and apparatus for optimizing throughput in a telematics relay cooperative network. Background Technology

[0002] In wireless communication, to address the issue of limited device power, the Simultaneous Wireless Information and Power Transmission (SWIPT) technology was proposed. This technology utilizes radio frequency (RF) signals to simultaneously transmit wireless information and power. Furthermore, since relay cooperation technology can expand cell coverage and enhance transmission reliability, existing technologies combine SWIPT with relay cooperation to effectively combat signal fading during transmission and improve reliability. Nodes with SWIPT functionality are used as relay nodes, and the RF signal is split into two separate streams using time switching (TS) or power splitting (PS) protocols. One stream is used for power harvesting, and the other stream is used for information decoding, thus completing the wireless transmission of information.

[0003] Currently, there are methods based on numerical simulation to obtain the optimal throughput of relay cooperative networks using a hybrid protocol of power-based relay (PS-based Relay, PSR) and time-based relay (TS-based Relay, TSR). However, these methods have high computational complexity because they require a set of power (time) splitting factor values ​​to be given separately, to find the throughput corresponding to the continuous change of the time (power) splitting factor, and to combine the results of two numerical simulations to obtain the optimal values ​​of the time and power splitting factors and the optimal throughput of the system. Summary of the Invention

[0004] To address the problems existing in the prior art, this application provides a method and apparatus for optimizing throughput in a telematics relay cooperative network.

[0005] In a first aspect, embodiments of this application provide a method for optimizing throughput in a teleportation relay cooperative network, including:

[0006] Determine the network parameters of the information-carrying relay cooperative network;

[0007] Based on the network parameters, the optimal throughput of the information-energy-carrying relay cooperative network is obtained through a throughput optimization function.

[0008] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0009] In one embodiment, the function for calculating the interruption probability is determined as follows:

[0010] The calculation function for determining the interruption probability of the information-energy-carrying relay cooperative network is based on network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor and target transmission rate.

[0011] In one embodiment, the calculation function for determining the outage probability of the information-energy-carrying relay cooperative network based on network energy harvesting efficiency, source node transmit power, distance between the source node and relay node, time splitting factor, power splitting factor, and target transmission rate includes:

[0012] Based on the network energy harvesting efficiency, the source node's transmit power, the distance between the source node and the relay node, the time splitting factor, and the power splitting factor, the received signal expression of the destination node is determined. The received signal expression of the destination node includes a first expression and a second expression. The first expression represents the signal received by the destination node, and the second expression represents the noise received by the destination node.

[0013] Based on the first expression and the second expression, an approximate signal-to-noise ratio expression for the target node is determined;

[0014] Based on the approximate signal-to-noise ratio (SNR) expression of the destination node, a calculation function is used to determine the interruption probability of the signal-to-noise ratio (SNR) of the signal-to-noise ratio (SNR) of the signal-to-noise ratio (SNR) of the destination node is less than a first SNR threshold, which is determined based on a first threshold of the target transmission rate.

[0015] In one embodiment, the throughput optimization function is:

[0016] maxτ(P s ,α,ρ)=(1-P out )R th (1-α)

[0017] Among them, P s This represents the transmit power of the source node, and 0 <P s <P max P max The maximum value of the source node's transmit power is represented by α; the time splitting factor is represented by α, and 0 < α < 1; ρ is the power splitting factor, and 0 < ρ < 1; Pout The function representing the calculation of the interruption probability; R th This represents the first threshold.

[0018] In one embodiment, obtaining the optimal throughput of the information-energy-carrying relay cooperative network based on the network parameters using a throughput optimization function includes:

[0019] The network energy harvesting efficiency, the source node transmit power, the distance between the source node and the relay node, the time splitting factor, the power splitting factor, and the target transmission rate are input into the throughput optimization function. Based on the variable alternating optimization iterative algorithm, the time splitting factor and the power splitting factor are alternately optimized and iterated to obtain the optimal throughput of the information-energy-carrying relay cooperative network.

[0020] In one embodiment, the step of alternating optimization iteratively optimizing the time splitting factor and the power splitting factor based on the variable alternation optimization iterative algorithm to obtain the optimal throughput of the information-energy-carrying relay cooperative network includes:

[0021] The throughput of the information-energy-carrying relay cooperative network is updated by iteratively optimizing the time splitting factor and the power splitting factor.

[0022] If the error between the first throughput before the update and the second throughput after the update is less than the first error threshold, the time splitting factor and the power splitting factor corresponding to the second throughput after the update are respectively taken as the optimal time splitting factor and the optimal power splitting factor, and the second throughput is taken as the optimal throughput of the information-energy-carrying relay cooperative network.

[0023] In one embodiment, the relay nodes of the information-energy-carrying relay cooperative network are equipped with a single antenna and perform energy harvesting and forwarding of information based on a hybrid energy harvesting protocol.

[0024] Secondly, embodiments of this application provide a throughput optimization device for a telematics relay cooperative network, comprising:

[0025] The determination module is used to determine the network parameters of the information and energy transport relay cooperative network;

[0026] The acquisition module is used to obtain the optimal throughput of the information-energy-carrying relay cooperative network based on the network parameters and through a throughput optimization function.

[0027] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0028] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the program to implement the steps of the throughput optimization method for the information-energy-carrying relay cooperative network described in the first aspect.

[0029] Fourthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the throughput optimization method for the information-energy-carrying relay cooperative network described in the first aspect.

[0030] The method and apparatus for optimizing throughput in a telematics-enabled relay cooperative network provided in this application first determine a throughput optimization function based on a calculation function of the outage probability of the telematics-enabled relay cooperative network. Then, the optimal throughput of the telematics-enabled relay cooperative network is obtained through the throughput optimization function. By establishing an optimization problem with the goal of obtaining the optimal throughput and employing an optimization algorithm to obtain the optimal network throughput, it is not only convenient to find the optimal network throughput but also computationally simple. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in this application 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the throughput optimization method for a teleportation relay cooperative network provided in an embodiment of this application.

[0033] Figure 2 This is a schematic diagram of the transmission time slot structure of the energy harvesting protocol in the energy-carrying relay cooperative network provided in the embodiments of this application;

[0034] Figure 3 This is a graph showing the relationship between throughput and energy harvesting efficiency provided in an embodiment of this application;

[0035] Figure 4 This is a graph showing the relationship between throughput and maximum source node transmit power provided in an embodiment of this application;

[0036] Figure 5 This is a graph showing the relationship between throughput and relay noise power provided in an embodiment of this application;

[0037] Figure 6 This is a graph showing the relationship between throughput and transmission rate provided in the embodiments of this application;

[0038] Figure 7This is a schematic diagram of the throughput optimization device for the information-energy-carrying relay cooperative network provided in the embodiments of this application;

[0039] Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. 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.

[0041] The following is combined with Figures 1-7 This application describes a method and apparatus for optimizing throughput in a teleportation relay cooperative network.

[0042] Figure 1 This is a flowchart illustrating the throughput optimization method for a teleportation relay cooperative network provided in an embodiment of this application. Figure 1 As shown in the embodiments of this application, a method for optimizing throughput in a teleportation relay cooperative network is provided, which may include:

[0043] Step 100: Determine the network parameters of the information-carrying relay cooperative network;

[0044] Step 110: Based on the network parameters, obtain the optimal throughput of the information-energy-carrying relay cooperative network through the throughput optimization function;

[0045] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0046] It should be noted that the energy-carrying relay cooperative network in this embodiment can collect and forward information based on a hybrid energy harvesting protocol, and may include a source node, a relay node with energy-carrying capability, and a destination node. All three nodes may be equipped with a single antenna. It can be assumed that the source node and destination node cannot directly establish a communication link due to poor channel conditions, requiring the relay node to forward signals. The source and destination nodes do not have energy limitations, while the relay node is energy-limited, powered by an energy harvesting module. The collected energy is used for signal transmission by the relay node. Energy loss in the relay node's signal processing circuit is not considered. The relay node adopts a half-duplex mode. Considering the latency-constrained transmission mode, this part can be considered as the applicable condition for the energy-carrying relay cooperative network throughput optimization method provided in this embodiment.

[0047] Optionally, the network parameters of the information-carrying relay cooperative network can be determined.

[0048] Optionally, network parameters may include parameters that affect the throughput of the information-carrying relay cooperative network.

[0049] For example, network parameters may include source node transmit power, time splitting factor, and power splitting factor.

[0050] Optionally, the optimal throughput of the information-energy-carrying relay cooperative network can be obtained based on network parameters through a throughput optimization function.

[0051] Optionally, a throughput optimization function can be established based on network parameters, and an optimization algorithm can be used to solve the throughput optimization function to obtain the optimal throughput of the information-energy-carrying relay cooperative network.

[0052] Alternatively, the throughput optimization function can be determined based on a calculation function of the outage probability of the information-energy-carrying relay cooperative network.

[0053] Optionally, the variables in the function for calculating the interruption probability may include network parameters.

[0054] For example, the interruption probability calculation function of the information-energy-carrying relay cooperative network can be determined first based on the network parameters, then the throughput optimization function can be determined based on the interruption probability calculation function, and finally the optimal throughput of the information-energy-carrying relay cooperative network can be obtained based on the throughput optimization function.

[0055] To ensure the optimal throughput of the telecom-connection relay cooperative network is obtained while reducing the computational complexity of achieving it, this application first determines the network outage probability, then constructs a throughput optimization function with the goal of obtaining the optimal throughput, and finally uses an optimization algorithm to solve the throughput optimization function to obtain the optimal throughput of the telecom-connection relay cooperative network. This approach not only facilitates finding the optimal throughput of the network but also simplifies the calculation.

[0056] The throughput optimization method for information-energy-carrying relay cooperative networks provided in this application first determines the throughput optimization function based on the calculation function of the outage probability of the information-energy-carrying relay cooperative network, and then obtains the optimal throughput of the information-energy-carrying relay cooperative network through the throughput optimization function. By establishing an optimization problem with the goal of obtaining the optimal throughput and employing an optimization algorithm to obtain the optimal network throughput, this method not only facilitates finding the optimal network throughput but also simplifies the calculation.

[0057] Optionally, the function for calculating the interruption probability is determined as follows:

[0058] The calculation function for determining the interruption probability of the information-energy-carrying relay cooperative network is based on network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor and target transmission rate.

[0059] Optionally, the calculation function for the interruption probability of the information-energy-carrying relay cooperative network can be determined based on the network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor and target transmission rate.

[0060] Alternatively, the network energy harvesting efficiency can be determined by the energy harvesting circuit.

[0061] Optionally, the calculation function for determining the outage probability of the information-energy-carrying relay cooperative network based on network energy harvesting efficiency, source node transmit power, distance between the source node and relay node, time splitting factor, power splitting factor, and target transmission rate includes:

[0062] Based on the network energy harvesting efficiency, the source node's transmit power, the distance between the source node and the relay node, the time splitting factor, and the power splitting factor, the received signal expression of the destination node is determined. The received signal expression of the destination node includes a first expression and a second expression. The first expression represents the signal received by the destination node, and the second expression represents the noise received by the destination node.

[0063] Based on the first expression and the second expression, an approximate signal-to-noise ratio expression for the target node is determined;

[0064] Based on the approximate signal-to-noise ratio (SNR) expression of the destination node, a calculation function is used to determine the interruption probability of the signal-to-noise ratio (SNR) of the signal-to-noise ratio (SNR) of the signal-to-noise ratio (SNR) of the destination node is less than a first SNR threshold, which is determined based on a first threshold of the target transmission rate.

[0065] Optionally, the expression for the received signal at the destination node can be determined based on the network energy harvesting efficiency, the source node's transmit power, the distance between the source node and the relay node, the time splitting factor, and the power splitting factor.

[0066] Optionally, the received signal expression of the destination node may include a first expression and a second expression.

[0067] Optionally, the first expression can be used to represent the signal received by the destination node.

[0068] Optionally, the second expression can be used to represent the noise received by the destination node.

[0069] Optionally, an approximate signal-to-noise ratio expression for the destination node can be determined based on the first and second expressions.

[0070] Optionally, the calculation function for the interruption probability of the signal-to-noise ratio relay cooperative network can be determined based on the approximate signal-to-noise ratio expression of the destination node.

[0071] Optionally, the interruption probability can be the probability that the approximate signal-to-noise ratio of the destination node is less than a first signal-to-noise ratio threshold.

[0072] Optionally, the first signal-to-noise ratio threshold can be determined based on a first threshold of the target transmission rate.

[0073] Figure 2 This is a schematic diagram of the transmission time slot structure of the energy harvesting protocol in the energy-carrying relay cooperative network provided in the embodiments of this application, as shown below. Figure 2 As shown, α represents the time splitting factor, and ρ represents the power splitting factor. In the first time slot αT, the relay node splits the received signal into two parts according to power. The ρP part enters the energy harvesting circuit for energy harvesting, and the (1-ρ)P part enters the information processing circuit for information transmission. In the (1-α)T time slot, the relay node amplifies the received signal and sends it to the destination node. Assume that the channel gain and distance between the source node and the relay, and between the relay and the destination node are h1, h2, d1, and d2, respectively. The channel gain is quasi-static Rayleigh block fading. Within each time block, the channel gain is constant, and the channel gain between different transmission blocks follows a Rayleigh distribution.

[0074] Optionally, the signal received by relay R from the source node within the first time slot αT can be expressed as:

[0075]

[0076] Where, p s Let s(t) be the source node's transmit power, and s(t) be the source node's transmit signal, which satisfies E{|s(t)| 2}=1, n a The mean of the signal received by the relay antenna is 0, and the variance is σ. a 2 The additive white Gaussian noise, where m is the path loss factor.

[0077] Alternatively, the signal used for energy harvesting can be represented as:

[0078]

[0079] Optionally, the signal used for information transmission can be represented as:

[0080]

[0081] in, It is relay node noise, n c It is the conversion noise generated when the radio frequency signal is converted into a baseband signal, and it is additive white Gaussian noise, satisfying the following conditions: because so It is an identity symbol.

[0082] Alternatively, the energy collected by the relay node can be expressed as:

[0083]

[0084] Where η represents the energy harvesting efficiency, which is determined by the energy harvesting circuit.

[0085] Optionally, the relay node transmit power can be expressed as:

[0086]

[0087] in,

[0088] Optionally, the signal sent by the relay node to the destination node can be represented as:

[0089]

[0090] Optionally, the signal received by the destination node can be represented as:

[0091]

[0092] Alternatively, combining the above formulas, the signal received by the destination node can be expressed as:

[0093]

[0094] Where, n d (k)=n a (k)+n c (k) is the destination node noise, satisfying...

[0095] Alternatively, the approximate signal-to-noise ratio of the destination node can be expressed as:

[0096]

[0097] Optionally, the function for calculating the interruption probability can be expressed as:

[0098]

[0099] in, γ th This represents the signal-to-noise ratio threshold, and R th Represents the target transmission rate threshold, c = P s Q(1-ρ),

[0100] Alternatively, |h1| 2 The probability density function can be expressed as:

[0101]

[0102] Alternatively, |h2| 2 The cumulative distribution function can be expressed as:

[0103]

[0104] Alternatively, the closed-form expression for the interruption probability can be expressed as:

[0105]

[0106] in, K1(·) is a first-order modified Bessel function of the second kind.

[0107] The embodiments of this application first determine the received signal expression of the destination node based on the network energy harvesting efficiency, the source node's transmit power, the distance between the source node and the relay node, the time splitting factor, and the power splitting factor, and then obtain the approximate signal-to-noise ratio expression of the destination node. Then, based on the approximate signal-to-noise ratio expression of the destination node, the calculation function of the interruption probability of the signal-to-energy carrying relay cooperative network is determined. The calculation process is relatively simple.

[0108] The throughput optimization method for information-energy-carrying relay cooperative networks provided in this application determines the interruption probability calculation function based on network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor and target transmission rate, and then establishes a throughput optimization problem based on the interruption probability. This method is not only conducive to finding the optimal throughput of the network, but also simple to calculate.

[0109] Optionally, the throughput optimization function is:

[0110] maxτ(P s ,α,ρ)=(1-P out )R th (1-α)

[0111] Among them, P s This represents the transmit power of the source node, and 0 <P s <P max P max The maximum value of the source node's transmit power is represented by α; the time splitting factor is represented by α, and 0 < α < 1; ρ is the power splitting factor, and 0 < ρ < 1; P out The function representing the calculation of the interruption probability; R th This represents the first threshold.

[0112] Alternatively, network throughput can be calculated using the following formula:

[0113] τ=(1-P out )R th (1-α)

[0114] Optionally, an objective function (throughput optimization function) P1 can be constructed, and combined with P s α and ρ are used to optimize throughput to obtain the optimal source node transmit power P. s * Optimal time splitting factor α * and optimal power splitting factor ρ * .

[0115]

[0116] Among them, P sP represents the source node's transmit power. max α represents the maximum transmit power of the source node; α represents the time splitting factor, 0 < α < 1 indicates a time splitting factor constraint; ρ represents the power splitting factor, 0 < ρ < 1 indicates a power splitting factor constraint; P out The function representing the probability of interruption; R th This represents the target transmission rate threshold (first threshold).

[0117] It is understandable that, for the objective function P1, given the values ​​of α and ρ, P1 is related to the transmit power P. s Since P1 is a monotonically increasing function, P1 can be transformed into P2:

[0118] P2: maxτ(P) max ,α,ρ)=(1-P out )R th (1-α)

[0119] st 0<ρ<1

[0120] 0<α<1

[0121] Understandably, for the objective function P2, given the value of α, it is difficult to determine the sign of the second derivative of τ(ρ). Therefore, a scientific computing software, such as Mathematica, can be used to determine it. By solving, we can find that when 0 < ρ < 1, the second derivative of τ(ρ) with respect to ρ is less than zero. Therefore, given α, P2 is a convex function with respect to ρ; similarly, given ρ, P2 is a convex function with respect to α.

[0122] Optionally, obtaining the optimal throughput of the information-energy-carrying relay cooperative network based on the network parameters and through a throughput optimization function includes:

[0123] The network energy harvesting efficiency, the source node transmit power, the distance between the source node and the relay node, the time splitting factor, the power splitting factor, and the target transmission rate are input into the throughput optimization function. Based on the variable alternating optimization iterative algorithm, the time splitting factor and the power splitting factor are alternately optimized and iterated to obtain the optimal throughput of the information-energy-carrying relay cooperative network.

[0124] Optionally, the network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor and target transmission rate can be input into the throughput optimization function, and the time splitting factor and power splitting factor can be alternately optimized and iterated based on the variable alternating optimization iterative algorithm to obtain the optimal throughput of the information-energy-carrying relay cooperative network.

[0125] The throughput optimization method for information-energy-carrying relay cooperative networks provided in this application constructs a throughput optimization function and then uses an alternating optimization iterative algorithm to alternately optimize the time splitting factor and the power splitting factor to obtain the optimal value of network throughput.

[0126] Optionally, the step of using an alternating optimization iterative algorithm based on variables to alternately optimize the time splitting factor and the power splitting factor to obtain the optimal throughput of the information-energy-carrying relay cooperative network includes:

[0127] The throughput of the information-energy-carrying relay cooperative network is updated by iteratively optimizing the time splitting factor and the power splitting factor.

[0128] If the error between the first throughput before the update and the second throughput after the update is less than the first error threshold, the time splitting factor and the power splitting factor corresponding to the second throughput after the update are respectively taken as the optimal time splitting factor and the optimal power splitting factor, and the second throughput is taken as the optimal throughput of the information-energy-carrying relay cooperative network.

[0129] Optionally, the time splitting factor and power splitting factor can be alternately optimized and iterated to update the throughput of the information-energy-carrying relay cooperative network.

[0130] Optionally, if the error between the first throughput before the update and the second throughput after the update is less than the first error threshold, the time splitting factor and the power splitting factor corresponding to the updated second throughput can be used as the optimal time splitting factor and the optimal power splitting factor, respectively, and the second throughput can be used as the optimal throughput of the information-energy-carrying relay cooperative network.

[0131] Optionally, the throughput of the information-energy-carrying relay cooperative network can be updated by iteratively optimizing the time splitting factor and power splitting factor through the following steps, thereby obtaining the optimal throughput of the information-energy-carrying relay cooperative network:

[0132] (1) Determine the network parameters, maximum number of iterations, and allowable error values ​​of the information-energy-carrying relay cooperative network;

[0133] (2) Input the iteration number i = 1, determine the initial value of the time splitting factor α, that is, the value of α(1) at the initial iteration (α(1) = 0.5), and determine the initial flag Flag = 0;

[0134] (3) Input the time splitting factor α(i), and solve for the power splitting factor ρ(i) that satisfies the objective function P2 and the throughput τ(α(i),ρ(i)) when the time splitting factor is known;

[0135] (4) Based on the power splitting factor ρ(i) obtained in step (3), update the time splitting factor α(i+1) that satisfies the objective function P2, and obtain the throughput τ(α(i+1),ρ(i)) after the time splitting factor is updated.

[0136] (5) Determine the proximity of the network throughput before and after the time split factor update. When the proximity is less than the allowable error ξ, mark the updated time split factor and the previously obtained power split factor as the best values, and obtain the best throughput corresponding to this set of values. Mark Flag as 1.

[0137] (6) When the proximity is not less than the allowable error ξ, the iteration count is incremented by 1, and it is determined whether the iteration count is less than or equal to the maximum iteration count. If the condition is met, return to step (3) to start executing the program until the value marked as 1 is obtained or the entire iteration count is terminated, and the program ends. Finally, the values ​​of the time splitting factor, power splitting factor and optimal throughput when the system throughput is optimal are obtained.

[0138] The throughput optimization method for information-energy-carrying relay cooperative networks provided in this application constructs a throughput optimization function and then uses an alternating optimization iterative algorithm to alternately optimize the time splitting factor and the power splitting factor to obtain the optimal value of network throughput.

[0139] Optionally, the relay nodes of the information-energy-carrying relay cooperative network are equipped with a single antenna and perform energy harvesting and forwarding of information based on a hybrid energy harvesting protocol.

[0140] Optionally, relay nodes in the telecom relay network can be equipped with a single antenna.

[0141] Optionally, information can be harvested and forwarded based on a hybrid energy harvesting protocol.

[0142] The information-energy-carrying relay cooperative network throughput optimization method provided in this application embodiment adopts a hybrid protocol relay cooperative network for information energy harvesting and forwarding. Compared with relay cooperative networks using PSR or TSR protocols, the hybrid protocol-based relay cooperative network proposed in this application embodiment can improve network throughput.

[0143] The following simulation demonstrates the throughput optimization method for the information-energy-carrying relay cooperative network provided in the embodiments of this application, in order to verify the effectiveness of the method.

[0144] The simulation parameters are set as follows: energy harvesting efficiency η = 0.8, and the distances between the source node, relay node, and destination node satisfy d. sd =d1 + d2, where d1 and d2 are both 1. Path loss factor m = 2.7, target transmission rate threshold R th= 4 bits / s, maximum source node transmit power is P max =30dB, noise power λ1 = 1, λ2 = 1.

[0145] Figure 3 This is a graph showing the relationship between throughput and energy harvesting efficiency provided in an embodiment of this application. Figure 4 This is a graph showing the relationship between throughput and maximum source node transmit power provided in an embodiment of this application. Figure 5 This is a graph showing the relationship between throughput and relay noise power provided in an embodiment of this application. Figure 6 This is a graph showing the relationship between throughput and transmission rate provided in the embodiments of this application, such as... Figure 3-6 As shown, the performance of two hybrid relay forwarding protocols, TPSR (Time Power Switching based Relaying) and HPTSR (Hybridized Power–Time Splitting-based Relaying), is compared with the throughput optimization method for cooperative relay networks (Alternate Hybrid Power–Time Splitting-based Relaying, AHPTSR) provided in the embodiments of this application through simulation. Analytical in the figure represents the numerical simulation results, and Simulation represents the Monte Carlo simulation results. Figures 3 to 6 For different energy harvesting efficiencies η and maximum source node transmit power P max Noise power, target transmission rate threshold R th The throughput of the three methods was compared, and it can be seen from the comparison that the throughput obtained by AHPTSR provided in this application embodiment is better than that of TPSR and HPTSR. Figure 3 In the middle, when P max At 30dB, AHPTSR achieved an 11.3% increase in throughput compared to HPTSR and an 18.5% increase compared to TPSR. Figure 5 In the middle, when R th When the throughput is 4 bits / s, the throughput of HPTSR reaches its peak, while the throughput of TPSR is at R. th The throughput reaches its maximum at 5 bits / s. The throughput obtained by the AHPTSR provided in this embodiment of the application is in R... th It reaches its peak at 4.5 bits / s, and in R th When the throughput is less than 5 bits / s, the throughput is significantly better than TPSR and HPTSR.

[0146] The throughput optimization method for information-energy-carrying relay cooperative networks provided in this application first determines the throughput optimization function based on the calculation function of the outage probability of the information-energy-carrying relay cooperative network, and then obtains the optimal throughput of the information-energy-carrying relay cooperative network through the throughput optimization function. By establishing an optimization problem with the goal of obtaining the optimal throughput and employing an optimization algorithm to obtain the optimal network throughput, this method not only facilitates finding the optimal network throughput but also simplifies the calculation.

[0147] The throughput optimization device for the telematics-enabled relay cooperative network provided in the embodiments of this application is described below. The throughput optimization device for the telematics-enabled relay cooperative network described below and the throughput optimization method for the telematics-enabled relay cooperative network described above can be referred to in correspondence with each other.

[0148] Figure 7 This is a schematic diagram of the throughput optimization device for a relay cooperative network provided in this application embodiment, as shown below. Figure 7 As shown, the device includes: a determining module 710 and an acquiring module 720; wherein:

[0149] The determination module 710 is used to determine the network parameters of the information and energy carrying relay cooperative network;

[0150] The acquisition module 720 is used to obtain the optimal throughput of the information-energy-carrying relay cooperative network based on the network parameters and through a throughput optimization function.

[0151] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0152] The throughput optimization device for a telematics relay cooperative network provided in this application first determines a throughput optimization function based on a calculation function of the interruption probability of the telematics relay cooperative network. Then, it obtains the optimal throughput of the telematics relay cooperative network using the throughput optimization function. By establishing an optimization problem with the goal of obtaining the optimal throughput and employing an optimization algorithm to obtain the optimal network throughput, it not only facilitates finding the optimal network throughput but also simplifies the calculation.

[0153] Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application, such as... Figure 8As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call a computer program in the memory 830 to execute the steps of a throughput optimization method for a teleportation relay cooperative network, such as including:

[0154] Determine the network parameters of the information-carrying relay cooperative network;

[0155] Based on the network parameters, the optimal throughput of the information-energy-carrying relay cooperative network is obtained through a throughput optimization function.

[0156] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0157] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0158] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the information-energy-carrying relay cooperative network throughput optimization method provided in the above embodiments, such as including:

[0159] Determine the network parameters of the information-carrying relay cooperative network;

[0160] Based on the network parameters, the optimal throughput of the information-energy-carrying relay cooperative network is obtained through a throughput optimization function.

[0161] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0162] In another aspect, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing a processor to execute the steps of the information-energy-carrying relay cooperative network throughput optimization method provided in the above embodiments, including, for example:

[0163] Determine the network parameters of the information-carrying relay cooperative network;

[0164] Based on the network parameters, the optimal throughput of the information-energy-carrying relay cooperative network is obtained through a throughput optimization function.

[0165] The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters.

[0166] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0167] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0168] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for optimizing throughput in a signal-carrying relay cooperative network, characterized in that, include: Determine the network parameters of the information-carrying relay cooperative network; Based on the network parameters, the optimal throughput of the information-energy-carrying relay cooperative network is obtained through a throughput optimization function. The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters. The relay nodes of the aforementioned energy-carrying relay cooperative network are equipped with a single antenna and perform energy harvesting and forwarding of information based on a hybrid energy harvesting protocol.

2. The throughput optimization method for information-energy-carrying relay cooperative networks according to claim 1, characterized in that, The function for calculating the interruption probability is determined as follows: The calculation function for determining the interruption probability of the information-energy-carrying relay cooperative network is based on network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor and target transmission rate.

3. The throughput optimization method for information-energy-carrying relay cooperative networks according to claim 2, characterized in that, The calculation function for determining the outage probability of the information-energy-carrying relay cooperative network, based on network energy harvesting efficiency, source node transmit power, distance between source node and relay node, time splitting factor, power splitting factor, and target transmission rate, includes: Based on the network energy harvesting efficiency, the source node's transmit power, the distance between the source node and the relay node, the time splitting factor, and the power splitting factor, the received signal expression of the destination node is determined. The received signal expression of the destination node includes a first expression and a second expression. The first expression represents the signal received by the destination node, and the second expression represents the noise received by the destination node. Based on the first expression and the second expression, an approximate signal-to-noise ratio expression for the target node is determined; Based on the approximate signal-to-noise ratio (SNR) expression of the destination node, a calculation function is used to determine the interruption probability of the signal-to-noise ratio (SNR) of the signal-to-noise ratio (SNR) of the signal-to-noise ratio (SNR) of the destination node is less than a first SNR threshold, which is determined based on a first threshold of the target transmission rate.

4. The throughput optimization method for information-energy-carrying relay cooperative networks according to claim 3, characterized in that, The throughput optimization function is: maxτ(P s ,a,p)=(1-P out )R th (1-a) Among them, P s This represents the transmit power of the source node, and 0 <P s <P max P max The maximum value of the source node's transmit power is represented by α; the time splitting factor is represented by α, and 0 < α < 1; ρ is the power splitting factor, and 0 < ρ < 1; P out The function representing the probability of interruption; R th This represents the first threshold.

5. The method for optimizing throughput in a teleportation relay cooperative network according to any one of claims 2-4, characterized in that, The step of obtaining the optimal throughput of the information-energy-carrying relay cooperative network based on the network parameters and through a throughput optimization function includes: The network energy harvesting efficiency, the source node transmit power, the distance between the source node and the relay node, the time splitting factor, the power splitting factor, and the target transmission rate are input into the throughput optimization function. Based on the variable alternating optimization iterative algorithm, the time splitting factor and the power splitting factor are alternately optimized and iterated to obtain the optimal throughput of the information-energy-carrying relay cooperative network.

6. The throughput optimization method for a teleportation relay cooperative network according to claim 5, characterized in that, The variable-alternating optimization iterative algorithm, which iteratively optimizes the time splitting factor and the power splitting factor to obtain the optimal throughput of the information-energy-carrying relay cooperative network, includes: The throughput of the information-energy-carrying relay cooperative network is updated by iteratively optimizing the time splitting factor and the power splitting factor. If the error between the first throughput before the update and the second throughput after the update is less than the first error threshold, the time splitting factor and the power splitting factor corresponding to the second throughput after the update are respectively taken as the optimal time splitting factor and the optimal power splitting factor, and the second throughput is taken as the optimal throughput of the information-energy-carrying relay cooperative network.

7. A throughput optimization device for a teleportation relay cooperative network, characterized in that, include: The determination module is used to determine the network parameters of the information and energy transport relay cooperative network; The acquisition module is used to obtain the optimal throughput of the information-energy-carrying relay cooperative network based on the network parameters and through a throughput optimization function. The throughput optimization function is determined based on the calculation function of the interruption probability of the information-energy-carrying relay cooperative network, and the variables in the calculation function of the interruption probability include the network parameters. The relay nodes of the aforementioned energy-carrying relay cooperative network are equipped with a single antenna and perform energy harvesting and forwarding of information based on a hybrid energy harvesting protocol.

8. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the throughput optimization method for the information-energy-carrying relay cooperative network according to any one of claims 1 to 6.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the throughput optimization method for the information-energy-carrying relay cooperative network according to any one of claims 1 to 6.

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