PS ratio control system and method for optimizing throughput of SWIPT multi-hop relay
By optimizing the power allocation ratio of relay nodes, the problems of dynamic environment adaptability and computational complexity in SWIPT multi-hop relay technology are solved, achieving efficient improvement in system throughput and extension of network lifetime.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUBEI THREE GORGES POLYTECHNIC
- Filing Date
- 2025-12-30
- Publication Date
- 2026-05-01
AI Technical Summary
In existing SWIPT multi-hop relay technology based on the PS protocol, the static resource allocation strategy is difficult to adapt to dynamic channel environments, has high computational complexity, and is difficult to balance between performance and complexity, resulting in the system throughput not reaching the optimal state.
A low-complexity optimization algorithm is adopted to optimize the power allocation ratio of each relay node by deriving efficient calculation rules, and dynamically adjust the PS ratio to maximize system throughput. It is suitable for actual relay nodes with high computing power and real-time requirements.
It significantly improves the end-to-end throughput performance of the system, overcomes the performance loss of the fixed PS ratio strategy, extends network lifetime, and enables rapid deployment with low computational complexity.
Smart Images
Figure CN121968292A_ABST
Abstract
Description
A PS ratio control system and method for optimizing throughput in SWIPT multi-hop relays Technical Field
[0001] This invention relates to the field of communication technology, and in particular to SWIPT multi-hop relay technology based on the PS protocol, specifically to a PS ratio control system and method for optimizing SWIPT multi-hop relay throughput. Background Technology
[0002] Wireless multi-hop relay networks, through the coordinated operation of multiple relay nodes, forward data hop-by-hop from the source node to the destination node, effectively extending communication coverage and improving signal transmission reliability in complex environments. This network structure has significant application value in scenarios such as wireless sensor networks (WSN), the Internet of Things (IoT), and emergency communications. However, relay nodes typically rely on batteries with limited capacity, and the cost of energy replenishment and replacement maintenance in remote or harsh environments is high, severely restricting the long-term stable operation of the network.
[0003] To address the aforementioned energy constraints, wireless energy harvesting (EH) technology has emerged, allowing nodes to collect energy from ambient radio frequency signals, achieving a degree of self-sufficiency. Building upon this, simultaneous wireless information and power transfer (SWIPT) technology further enables simultaneous information transmission and energy harvesting using the same radio frequency signal, providing a promising solution for energy-constrained multi-hop relay networks. In the practical implementation of SWIPT technology, the power-splitting (PS) protocol is a core mechanism. It uses a power divider to split the received signal into two parts according to a certain ratio: one part for energy harvesting and the other for information decoding. Compared to time-switching protocols, the PS protocol allows devices to perform energy harvesting and information decoding simultaneously, resulting in different trade-offs in system design.
[0004] In SWIPT multi-hop relay systems based on the PS protocol, the power allocation ratio (PS ratio) is a key parameter affecting system performance. The PS ratio directly determines the proportion of signal power used by relay nodes for energy harvesting and information decoding, thus affecting the relay node's forwarding capacity, end-to-end throughput, and network lifetime. Especially in multi-hop scenarios, the PS ratio settings at each relay node are intercoupled. A change in the PS ratio of a single node will affect the energy harvesting and signal reception of downstream nodes by changing its available forwarding power, making the joint optimization of the PS ratio a complex nonlinear constraint problem. Although existing research has focused on optimizing the PS ratio, these methods may have certain limitations in some practical applications. For example, the method proposed in the paper "Throughput Optimization Method and Device for Information-Power Transfer Relay Cooperative Networks" requires complex numerical simulations and multiple iterations, resulting in high computational complexity; or the solution obtained by the method proposed in the paper "Transmit Power Optimization in Multihop Amplify-and-Forward Relay Systems with Simultaneous Wireless Information and Power Transfer" may not be globally optimal in some cases, making it difficult to guarantee that the system throughput always reaches the optimal state.
[0005] Therefore, existing technologies still have the following defects and shortcomings: 1) Static resource allocation strategies are difficult to adapt to dynamic channel environments; existing solutions mostly use fixed power division ratios, failing to consider the time-varying nature of channel states, the differences in path losses, and the mutual coupling relationship of energy between nodes in multi-hop links. This "one-size-fits-all" static allocation strategy cannot dynamically adjust resource allocation according to real-time channel conditions, resulting in a constant mismatch between the collected energy and the signal power required for decoding, thus preventing the system throughput from reaching the theoretically optimal state.
[0006] 2) The optimal algorithm has high computational complexity and lacks practical feasibility. In pursuit of optimal performance, some studies have attempted to solve for the optimal PS ratio through exhaustive search or complex convex optimization iterative algorithms. However, in multi-hop networks, the dimensionality of the optimization variables increases linearly with the number of relay nodes, leading to an exponential increase in computational cost. For example, although numerical iterative methods such as the interior-point method can obtain the theoretically optimal solution, their computational complexity is high, making them difficult to implement on real-world relay nodes where computational power, energy, and latency are limited, and thus unsuitable for real-time communication systems requiring rapid response.
[0007] 3) Existing optimization schemes struggle to balance performance and complexity; current research faces a significant gap between performance and complexity: either a fixed PS ratio is used to sacrifice performance for low complexity, or a highly complex iterative optimization algorithm is used to approximate optimal performance. There is a lack of a solution that can achieve low computational complexity and be easy to deploy quickly while ensuring optimal or near-optimal performance.
[0008] Therefore, for SWIPT multi-hop relay networks, developing a control system and method that can efficiently and in real-time optimize the PS ratio to significantly improve system throughput has important theoretical significance and practical application value; this invention aims to explore this direction in depth. Summary of the Invention
[0009] The purpose of this invention is to address the technical problems in existing PS-SWIPT multi-hop relay technology, such as the static resource allocation strategy being difficult to adapt to dynamic channel environments, the high computational complexity and lack of practical feasibility of the optimal algorithm, and the difficulty in balancing performance and complexity between existing optimization schemes, in order to achieve the optimal system throughput. Therefore, this invention proposes a technology that can solve the PS ratio allocation problem in PS-SWIPT multi-hop decode-and-forward (DF) relay networks.
[0010] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a PS ratio control system for optimizing the throughput of SWIPT multi-hop relays, including a source node. Source node via relay set hop-by-hop forwarding of information to the destination node Source node Powered by internal battery or external power source; relay To relay All operate in a passive state; relay nodes ,in Using SWIPT technology from relay nodes The previous hop neighbor node Energy is collected from the radio frequency signal, and the power allocation (PS) protocol is used to simultaneously decode data packets and forward them to the next hop neighboring node; the power allocation ratio, also known as the PS ratio, is set as... Then the relay node The radio frequency signal at that location is split into two paths: Part of it is used for energy harvesting, the remainder Part of it is used for information decoding.
[0011] Assume all nodes are equipped with a single antenna and operate in half-duplex mode, meaning relay nodes only forward data after fully receiving the information; and The channel coefficient between them is denoted as ,in Furthermore, this channel coefficient remains constant during the time it takes for data to be transmitted from one node to the next adjacent node, i.e., within a transmission frame.
[0012] relay node The energy harvesting circuit receives the radio frequency signal. Partial energy is harvested and stored in supercapacitors; all harvested energy is used for information decoding and data retransmission; a source node is defined as... It possesses channel state information for all nodes, and each relay node... and destination node Knowing only the channel state information of its corresponding communication link and (See Figure 1) express and Channel coefficients between express and (channel coefficients between nodes); assume direct links exist only between adjacent nodes; relay nodes From the previous hop adjacent node The received radio frequency signal can be represented as: (1); where, Indicates that it comes from the previous hop neighbor node. The information symbols, each with a unit average power, i.e. ; express The power spectral density of the emitted power.
[0013] As shown in Figure 2(a), Represents a node The power spectral density of the additive white Gaussian noise introduced at the antenna follows a distribution. , express The variance; as shown in Figure 1 and Figure 2(a), the relay node The received radio frequency signal is then distributed according to the power allocation ratio. It was divided into two paths, one for energy harvesting and the other for information decoding.
[0014] The signal used for energy harvesting can be represented as: (2); relay node The signal used for information decoding can be represented as: (3); among which It is a relay node The power spectral density of the additive white Gaussian noise introduced by the information decoding circuit follows a distribution. , express The variance; assume all collected energy is used for information decoding and data retransmission; therefore, according to formula (2), the node The power spectral density of the emitted power can be derived as follows: (4); among which Represents relay node The rectification efficiency factor; due to Then we further obtain: (5); among which Represents a node and Channel gain between; Indicates the source node The power spectral density of the emitted power; according to formula (3) and relay node The received signal-to-noise ratio at that point can be expressed as: (6) Among them, This refers to the power spectral density of additive noise. The variance of This refers to the power spectral density of additive noise. variance For relay The rectification efficiency, For relay PS ratio, for and Channel gain between.
[0015] In power-sharing-based SWIPT systems, the additive noise at the antenna is typically much smaller than the noise introduced by the information decoding circuitry; therefore, in Under these conditions, we further obtain: (7); among which ; This refers to a node corresponding to a relay node. Auxiliary variables, Refers to the source node With relay node The channel gain between; similarly, based on formulas (3), (5) and relay node The received signal-to-noise ratio at that point can be expressed as: (8); among which It is a node corresponding to a relay node. Auxiliary variables.
[0016] Due to the destination node If only information decoding is performed without energy harvesting, the signal used for information decoding at this node can be represented as: (9); among which, For relay nodes With the target node Channel coefficients between; It is a relay The power spectral density of the emitted power; It comes from The information symbol has a unit average power, that is... ; Indicates the destination node The power spectral density of additive white Gaussian noise introduced at the antenna. ; Indicates the destination node The power spectral density of additive white Gaussian noise introduced by the information decoding circuit. .
[0017] node The received signal-to-noise ratio at the location is: (10); among which , is a corresponding Auxiliary variables. It is a relay node With the target node Channel gain between.
[0018] In obtaining signal-to-noise ratio After that, the The reachability of a jump can be expressed as: (11); among which Indicates the transmission bandwidth; information needs to pass through [various stages] to travel from the source node to the destination node. Jump Therefore, the end-to-end throughput of the multi-hop decode-forward relay network can be expressed as: (The number of transmission frames is not specified in the original text.) (12); In wireless sensor networks, considering hardware costs, when the communication environment is stable and simple, many sensor nodes transmit signals at a preset constant power; therefore, the problem to be solved is the power spectral density of the transmitted power of a given source node. Under the premise of optimizing the power allocation ratio of each relay To maximize system throughput, the optimization problem can be formulated as follows: (13a); st , (13b).
[0019] The following steps are used to solve the problem: Step 1: First, through... , (14); Calculate relay PS ratio at the location; Step 2: Through , (15); In an iterative manner, it is known calculate .
[0020] Compared with existing technologies, the present invention has the following technical advantages: The power segmentation ratio control system and method for SWIPT multi-hop decoding and forwarding relay networks proposed in this invention have the core advantage of significantly improving the end-to-end throughput performance of the system through a low-complexity optimization algorithm; compared with optimization schemes that require complex numerical iterations, this method can quickly determine the PS ratio of each relay node that maximizes the system throughput by deriving efficient calculation rules; this method has a light computational burden that does not increase sharply with the number of relay nodes, making it very suitable for implementation on actual relay nodes that require high computational power and real-time performance.
[0021] This method can dynamically adjust parameters according to channel conditions, overcoming the performance loss caused by the fixed PS ratio strategy's inability to adapt to dynamic environments. Through precise PS ratio control, relay nodes can more effectively harvest energy from radio frequency signals, supporting their self-sustaining operation and thus helping to extend network lifetime.
[0022] In summary, this invention achieves a good balance between system throughput performance, algorithm complexity, and engineering feasibility, providing an efficient and practical solution for SWIPT multi-hop relay networks. Attached Figure Description
[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 is a schematic diagram of a multi-hop DF relay communication network using PS-SWIPT in the present invention; Figure 2 is a schematic diagram of the signal processing flow between the relay node and the destination node in the present invention; wherein, (a) corresponds to the relay node ,in (b) Corresponding to the destination node Figure 3 is a comparison of system throughput and source node transmit power in the embodiment. Figure 4 is a comparison chart of system throughput and number of relays in the embodiment. dBm); Figure 5 Comparison of calculation time and number of repeaters ( dBm). Detailed Implementation
[0024] As shown in Figure 1, a PS ratio control system for optimizing throughput in a SWIPT multi-hop relay (see Figure 1) includes a source node. Source node via relay set hop-by-hop forwarding of information to the destination node Source node Powered by internal battery or external power source; relay To relay All operate in a passive state; relay nodes ,in Using SWIPT technology from relay nodes The previous hop neighbor node Energy is collected from the radio frequency signal, and the power allocation (PS) protocol is used to simultaneously decode data packets and forward them to the next hop neighboring node; the power allocation ratio, also known as the PS ratio, is set as... Then the relay node The radio frequency signal at that location is split into two paths: Part of it is used for energy harvesting, the remainder Part of it is used for information decoding.
[0025] Assume all nodes are equipped with a single antenna and operate in half-duplex mode, meaning relay nodes only forward data after fully receiving the information; and The channel coefficient between them is denoted as ,in Furthermore, this channel coefficient remains constant during the time it takes for data to be transmitted from one node to the next adjacent node, i.e., within a transmission frame.
[0026] relay node The energy harvesting circuit receives the radio frequency signal. Partial energy is harvested and stored in supercapacitors; all harvested energy is used for information decoding and data retransmission; a source node is defined as... It possesses channel state information for all nodes, and each relay node... and destination node Knowing only the channel state information of its corresponding communication link and (See Figure 1) express and Channel coefficients between express and (channel coefficients between nodes); assume direct links exist only between adjacent nodes; relay nodes From the previous hop adjacent node The received radio frequency signal can be represented as: (1); where, Indicates that it comes from the previous hop neighbor node. The information symbols, each with a unit average power, i.e. ; express The power spectral density of the emitted power.
[0027] As shown in Figure 2(a), Represents a node The power spectral density of the additive white Gaussian noise introduced at the antenna follows a distribution. , express The variance; as shown in Figure 1 and Figure 2(a), the relay node The received radio frequency signal is then distributed according to the power allocation ratio. It was divided into two paths, one for energy harvesting and the other for information decoding.
[0028] The signal used for energy harvesting can be represented as: (2); relay node The signal used for information decoding can be represented as: (3); among which It is a relay node The power spectral density of the additive white Gaussian noise introduced by the information decoding circuit follows a distribution. , express The variance; assume all collected energy is used for information decoding and data retransmission; therefore, according to formula (2), the node The power spectral density of the emitted power can be derived as follows: (4); among which Represents relay node The rectification efficiency factor; due to Then we further obtain: (5); among which Represents a node and Channel gain between; Indicates the source node The power spectral density of the emitted power; according to formula (3) and relay node The received signal-to-noise ratio at that point can be expressed as: (6) Among them, This refers to the power spectral density of additive noise. The variance of This refers to the power spectral density of additive noise. variance For relay The rectification efficiency, For relay PS ratio, for and Channel gain between.
[0029] In power-sharing-based SWIPT systems, the additive noise at the antenna is typically much smaller than the noise introduced by the information decoding circuitry; therefore, in Under these conditions, we further obtain: (7); among which ; This refers to a node corresponding to a relay node. Auxiliary variables, Refers to the source node With relay node The channel gain between; similarly, based on formulas (3), (5) and relay node The received signal-to-noise ratio at that point can be expressed as: (8); among which It is a node corresponding to a relay node. Auxiliary variables.
[0030] As shown in Figures 1 and 2(b), due to the destination node If only information decoding is performed without energy harvesting, the signal used for information decoding at this node can be represented as: (9); among which, For relay nodes With the target node Channel coefficients between; It is a relay The power spectral density of the emitted power; It comes from The information symbol has a unit average power, that is... ; Indicates the destination node The power spectral density of additive white Gaussian noise introduced at the antenna. ; Indicates the destination node The power spectral density of additive white Gaussian noise introduced by the information decoding circuit. .
[0031] node The received signal-to-noise ratio at the location is: (10); among which , is a corresponding Auxiliary variables. It is a relay node With the target node Channel gain between.
[0032] In obtaining signal-to-noise ratio After that, the The reachability of a jump can be expressed as: (11); among which Indicates the transmission bandwidth; information needs to pass through [various stages] to travel from the source node to the destination node. Jump Therefore, the end-to-end throughput of the multi-hop decode-forward relay network can be expressed as: (The number of transmission frames is not specified in the original text.) (12); In wireless sensor networks, considering hardware costs, when the communication environment is stable and simple, many sensor nodes transmit signals at a preset constant power; therefore, the problem to be solved is the power spectral density of the transmitted power of a given source node. Under the premise of optimizing the power allocation ratio of each relay To maximize system throughput, the optimization problem can be formulated as follows: (13a); st , (13b).
[0033] The following steps are used to solve the problem: Step 1: First, through... , (14); Calculate relay PS ratio at the location; Step 2: Through , (15); In an iterative manner, it is known calculate .
[0034] Example: This invention evaluates the performance of the proposed optimal solution based on closed-form solutions through numerical simulation. This solution is applied to a multi-hop DF relay system supporting SWIPT. The numerical simulation was performed on a laptop equipped with an AMD Ryzen R9 7945HX processor and 64GB of memory. The algorithm implementation and data analysis both used MATLAB R2022b as the software platform.
[0035] Unless otherwise specified, the simulation in this section uses the following parameter settings: nodes ( The variance of the power spectral density of the additive white Gaussian noise introduced by the information decoding circuit is: dBm / Hz; transmission bandwidth MHz; the rectification efficiency of each relay node is uniformly set to ( ); source node The minimum transmit power is dBm, maximum transmit power is dBm.
[0036] Furthermore, it is assumed that in the multi-hop relay network system under consideration, the distance between any two nodes in each hop is equal, and the total distance is 5 meters. Specifically, if the model contains... A relay network contains a multi-hop relay network. Jump, with a spacing of 1 / 20 between each jump. rice.
[0037] The channel model used in the simulation considers both large-scale and small-scale fading. Large-scale fading employs a logarithmic distance path loss model with a path loss exponent of 3.8, a carrier frequency of 2.4 GHz, and a reference distance of 1 meter. The small-scale fading model assumes a line-of-sight link between each hop of the transmitting and receiving nodes, and the channel gain... ( The distribution follows a Rice distribution with a K-factor of 7. All simulation results were obtained by averaging the results after 1000 random channel simulations.
[0038] The present invention compares the performance of the proposed scheme with the following benchmark schemes: the first is the best-performing scheme based on exhaustive search, which searches the PS ratio combination with a step size of 0.02 to determine the optimal solution; the other three are suboptimal schemes, which fix the PS ratio of each relay node to 0.25, 0.5 and 0.75 respectively.
[0039] First, Figure 3 (or Table 1) shows the relationship between throughput and source node transmit power in the multi-hop DF relay system supporting SWIPT considered in this invention, where the number of relay hops is set to... Accordingly, the distance per hop is calculated to be 1.25 meters. As shown in the figure, the throughput of all schemes increases with the increase of the source node's transmit power. For example, the throughput of the proposed scheme increases from... time bps increased to time Furthermore, the performance curves of the proposed scheme perfectly coincide with those of the exhaustive search-based scheme. This consistency was also observed under other parameter settings, indicating that the proposed scheme achieves optimal throughput performance. On the other hand, the proposed scheme significantly outperforms the three suboptimal schemes using a fixed PS ratio in terms of throughput performance. For example, the results show that the average throughput of the proposed scheme is 123% higher than that of the scheme with a fixed PS ratio of 0.75. Even when the fixed PS ratio is set to other values, the significant advantage of the proposed scheme remains.
[0040] Table 1: Relationship between system throughput and source node transmit power for five schemes
[0041] Figure 4 (or Table 2) shows the throughput and number of relays in a multi-hop relay system. The relationship between them. The power spectral density of the source node's transmit power is set to... As the number of relays in the system increases from 1 to 4, the number of hops between the source and destination nodes increases from 2 to 5. Given that each hop distance is equal and the total distance is 5 meters, the hop distances are 2.5 meters, 1.67 meters, 1.25 meters, and 1 meter, respectively. The conclusions drawn from Figure 4 are consistent with those from Figure 3: the proposed scheme based on the closed-form solution achieves optimal performance, and its throughput exceeds that of the suboptimal scheme using a fixed PS ratio. For example, when the number of relays... At that time, the throughput of the proposed solution was consistent with that of the optimal solution. The throughput of the proposed scheme is 7.41 bps, while the throughput of the scheme with a fixed PS ratio of 0.75 is only 7.41 bps. Furthermore, it can be observed that the throughput of all schemes decreases rapidly with the increase of the number of relays. Taking the proposed scheme as an example, when... At that time, the corresponding throughput is bps; however when At that time, its throughput dropped to a negligible level. This indicates that when deploying a multi-hop relay network, the number of relays must be strictly controlled, provided that channel conditions allow for each hop. However, it can still be observed that the proposed scheme is not only superior to the suboptimal scheme with a fixed PS ratio, but also in terms of the number of relays. As the throughput increases from 1 to 4, the rate of decrease is significantly slower than that of the fixed PS ratio scheme. All of the above phenomena demonstrate the performance advantage of the proposed scheme.
[0042] Table 2. System throughput and number of relays for five schemes Relationship
[0043] In Figure 5 (or Table 3), the performance of the proposed schemes is evaluated from the perspective of computational efficiency. To this end, the computation time of all schemes was measured.
[0044] Table 3 shows the calculation time and number of relays for the five schemes. Relationship
[0045] The results show that the optimal solution based on exhaustive search requires the longest computation time, and this time increases rapidly with the number of relays. When the number of relays... At that time, the optimal solution requires 2.62 seconds to complete the calculation, which is unacceptable for practical communication systems. It is worth noting that in implementing the optimal solution based on exhaustive search in this invention, nested loops are not used. Instead, the built-in MATLAB function "ndgrid" is utilized to generate a grid matrix of all possible PS ratio combinations, thereby accelerating the search process. This method trades increased computational memory usage for a significant reduction in computation time. However, when the number of relays... At larger values, the computation time remains unsatisfactory and may lead to memory explosion issues. On the other hand, as expected, the three schemes with a fixed PS ratio exhibit the same and extremely short computation time, which hardly changes with the increase in the number of relays. In contrast, the computation time of the proposed scheme is on the same order of magnitude as these three suboptimal schemes. For example, when At that time, the computation time of the proposed solution was The computation time is only 168% of that of the suboptimal scheme with a fixed PS ratio of 0.75. Clearly, the proposed scheme is well-suited for practical communication system applications.
Claims
1. A PS ratio control system for optimizing throughput in a SWIPT multi-hop relay, characterized in that, Including source node Source node via relay set hop-by-hop forwarding of information to the destination node Source node Powered by internal battery or external power source; relay To relay All operate in a passive state; relay nodes ,in Using SWIPT technology from relay nodes The previous hop neighbor node Energy is collected from the radio frequency signal, and the power allocation (PS) protocol is used to simultaneously decode data packets and forward them to the next hop neighboring node; the power allocation ratio, also known as the PS ratio, is set as... Then the relay node The radio frequency signal at that location is split into two paths: Part of it is used for energy harvesting, the remainder Part of it is used for information decoding.
2. The system according to claim 1, characterized in that, wherein... All nodes are equipped with a single antenna and operate in half-duplex mode, meaning that relay nodes only forward data after fully receiving the information; and The channel coefficient between them is denoted as ,in Furthermore, the channel coefficient remains constant during the time it takes for data to be transmitted from one node to the next adjacent node, i.e., within a transmission frame.
3. The system according to claim 2, relay node The energy harvesting circuit receives the radio frequency signal. Partial energy is harvested and stored in supercapacitors; all harvested energy is used for information decoding and data retransmission; a source node is defined as... It possesses channel state information for all nodes, and each relay node... and destination node Knowing only the channel state information of its corresponding communication link and Assume that there are direct links only between adjacent nodes; relay node From the previous hop adjacent node The received radio frequency signal can be represented as: (1); where, Indicates that it comes from the previous hop neighbor node. The information symbols, each with a unit average power, i.e. ； express The power spectral density of the emitted power.
4. The system according to any one of claims 1 to 3, characterized in that, Represents a node The power spectral density of the additive white Gaussian noise introduced at the antenna follows a distribution. ， express variance; relay node The received radio frequency signal is then distributed according to the power allocation ratio. It was divided into two paths, one for energy harvesting and the other for information decoding.
5. The system according to claim 4, characterized in that, The signal used for energy harvesting can be represented as: (2); relay node The signal used for information decoding can be represented as: (3); among which It is a relay node The power spectral density of the additive white Gaussian noise introduced by the information decoding circuit follows a distribution. ， express The variance; assume all collected energy is used for information decoding and data retransmission; therefore, according to formula (2), the node The power spectral density of the emitted power can be derived as follows: (4); among which Represents relay node The rectification efficiency factor; due to Then we further obtain: (5); among which Represents a node and Channel gain between; Indicates the source node The power spectral density of the emitted power; according to formula (3) and relay node The received signal-to-noise ratio at that point can be expressed as: (6) Among them, This refers to the power spectral density of additive noise. The variance of This refers to the power spectral density of additive noise. variance For relay The rectification efficiency, For relay PS ratio, for and Channel gain between.
6. The system according to claim 5, characterized in that, In power-sharing-based SWIPT systems, the additive noise at the antenna is typically much smaller than the noise introduced by the information decoding circuitry; therefore, in Under these conditions, we further obtain: (7); among which ； This refers to a node corresponding to a relay node. Auxiliary variables, Refers to the source node With relay node The channel gain between; similarly, based on formulas (3), (5) and relay node The received signal-to-noise ratio at that point can be expressed as: (8); among which It is a node corresponding to a relay node. Auxiliary variables.
7. The system according to claim 1, 2, 3, 5, or 6, characterized in that, Due to the destination node If only information decoding is performed without energy harvesting, the signal used for information decoding at this node can be represented as: (9); among which, For relay nodes With the target node Channel coefficients between; It is a relay The power spectral density of the emitted power; It comes from The information symbol has a unit average power, that is... ； Indicates the destination node The power spectral density of additive white Gaussian noise introduced at the antenna. ； Indicates the destination node The power spectral density of additive white Gaussian noise introduced by the information decoding circuit. 。 8. The system according to claim 7, characterized in that, node The received signal-to-noise ratio at this location is: (10); among which , is a corresponding Auxiliary variables; It is a relay node With the target node Channel gain between.
9. The system according to claim 8, characterized in that, In obtaining signal-to-noise ratio After that, the The reachability of a jump can be expressed as: (11); among which Indicates the transmission bandwidth; information needs to pass through [various stages] to travel from the source node to the destination node. Jump Therefore, the end-to-end throughput of the multi-hop decode-forward relay network can be expressed as: (The number of transmission frames is not specified in the original text.) (12); In wireless sensor networks, considering hardware costs, when the communication environment is stable and simple, many sensor nodes transmit signals at a preset constant power; therefore, the problem to be solved is the power spectral density of the transmitted power of a given source node. Under the premise of optimizing the power allocation ratio of each relay To maximize system throughput, the optimization problem can be formulated as follows: (13a);s.t. , （13b）。 10. The system according to claim 9, characterized in that, The following steps are used to solve the problem: Step 1: First, through... , (14); Calculate relay PS ratio at the location; Step 2: Through , (15); In an iterative manner, it is known calculate 。