WO2020073586A1

WO2020073586A1 - Interference-aware wireless energy-carrying transfer routing method

Info

Publication number: WO2020073586A1
Application number: PCT/CN2019/076003
Authority: WO
Inventors: 何施茗; 李卓宙; 唐杨宁; 邓玉芳; 谢鲲; 王进
Original assignee: 长沙理工大学
Priority date: 2018-10-09
Filing date: 2019-02-25
Publication date: 2020-04-16
Also published as: CN109600816A; CN109600816B

Abstract

Disclosed in the present invention is an interference-aware wireless energy-carrying transfer routing method; a routing problem of a wireless multi-hop network is studied; and a routing method for a wireless multi-hop network is designed by considering the effect and influence of interference on wireless energy-carrying transfer not used in both information and energy aspects. First, an energy-carrying transfer module under interference is established by using a physical interference model; then, under the requirement of minimum energy acquisition, an interference-aware maximum energy-carrying capacity allocation model is constructed, and a solving algorithm is designed; finally, an interference-aware wireless energy-carrying transfer routing algorithm is designed as: the maximum energy-carrying transfer capacity of a link is calculated by using a maximum energy-carrying capacity allocation algorithm in a routing process, and a transfer mode and a path having the maximum transfer capacity of the link are selected according to interference-aware routing indexes.The experimental result shows that interference-aware wireless energy-carrying transfer routing has higher path capacity than interference-free and interference-based information transfer.

Description

Interference-aware wireless energy-carrying transmission routing method

Technical field

The invention relates to a routing method of a wireless multi-hop network using wireless energy transmission, in particular to an interference-aware wireless energy transmission route method.

Background technique

Nodes in a multi-hop wireless network have routing capabilities to forward data, so they have the advantages of flexible networking, easy expansion, self-organization, self-repair, and low deployment costs. The main forms include multi-hop wireless sensor networks (WSNs), mobile sensing Network (Mobile Sensing Networks), Ad Hoc Network, etc. Node energy limitation is a common problem in multi-hop wireless networks, which limits the availability and durability of multi-hop wireless networks. Taking the sensor network as an example, the sensor node is usually powered by a battery, and the battery capacity is limited. After the node is exhausted, it will cause problems such as data unavailability, data unreachability, and bypass.

Therefore, energy harvesting technology is proposed, and wireless nodes supplement their energy by collecting solar energy, wind energy, or thermal energy in the surrounding natural environment, but this method depends on natural environmental resources and has great uncertainty. . Another technology uses radio waves to transmit electrical energy, called wireless power transfer (Wireless Power Transfer, WPT). Compared with natural environmental energy sources, wireless energy transmission is more stable, reliable and controllable. WPT mainly includes two ways: magnetically coupled resonance (Coupled Magnetic Resonance) and radio frequency signal transmission (Radio Frequency Signal). Magnetic coupling resonance requires that the sending and receiving coils resonate at exactly the same frequency and that the coils are large and support mid-range distances. RF signals can be used to achieve long-distance energy transmission and attract much attention.

At the same time, the radio frequency signal is also an effective bearing method for data transmission, so a new wireless transmission technology has recently emerged-wireless energy transmission or wireless information and energy simultaneous transmission (Simultaneous Wireless Information and Power Transfer, SWIPT). Unlike wireless information transmission (Wireless Information Transfer, WIT) which only transmits information and WPT which only transmits energy, wireless energy transmission uses the same radio frequency signal to transmit information and energy.

Wireless energy-carrying transmission has the following advantages: 1) At the same time information is transmitted, the node can be supplemented with energy in a controlled manner to prevent the node from dying due to the exhaustion of power; 2) Compared with the transmission method of separating information and energy, the transmission efficiency of SWIPT higher. Energy and information are sent together without additional infrastructure, and can be applied to some special scenarios (such as in concrete, etc.); 3) Using SWIPT can use interference as an effective source of energy. At the same time, wireless energy-carrying transmission itself also faces some problems, such as energy transmission makes the distance of information transmission shorter, higher radio frequency signal loss and fading leads to lower energy transmission efficiency, which is currently mainly solved by multi-antenna technology [5].

The use of energy-carrying transmission in a multi-hop wireless network can bring the following benefits: 1) All nodes can obtain energy from interference and noisy RF signals, and the range of energy acquisition covers the entire network; 2) By forwarding the received energy as data Compensation for energy consumption, the energy obtained by a certain node can be purposefully and controllably transferred and shared in the network in a multi-hop manner, and the energy distribution of the network is balanced; 3) No complicated separation of energy acquisition, transmission and information transmission equipment is required, Reduce the volume requirements of nodes and save costs.

However, the application of energy-carrying transmission to multi-hop wireless networks still faces many problems. The core problem of a multi-hop wireless network is to determine the next-hop node based on routing indicators. When energy-carrying transmission is applied to a multi-hop network, each hop of data forwarding needs to determine the optimal information and energy distribution, and different information and energy distribution in turn affect the network topology and optimal path selection. Routing and energy-carrying transmission Interdependence and influence. The routing of multi-service flows determines the distribution of traffic, which will produce different degrees of interference. Interfering signals will reduce the quality of information transmission and can also be used as an energy source. The impact of interference on energy-carrying transmission is not only unilateral, but multi-faceted, and what level of interference is appropriate needs to be considered. The interdependence of information and energy distribution, routing, and interference is extremely challenging to solve the above problems.

Summary of the invention

The technical problem to be solved by the present invention is to provide an interference-aware wireless energy-carrying transmission routing method to improve the transmission performance of a multi-hop wireless network in view of the shortage of the existing technology.

In order to solve the above technical problems, the technical solution adopted by the present invention is: a wireless energy-carrying transmission routing method based on interference perception, the specific execution process is as follows:

Step 1), use the physical interference model to establish an energy-carrying transmission model under interference;

Step 2), based on the energy-carrying transmission model under interference, and satisfying the minimum energy acquisition requirements, construct an interference-aware maximum energy-carrying capacity allocation model,

Step 3), design a solution algorithm for the interference-aware maximum capacity-carrying capacity allocation model;

Step 4), design interference-aware routing indicators, combine interference-aware maximum energy-carrying capacity allocation model, and establish interference-aware energy-carrying transmission routing model;

Step 5), solve the interference-aware energy-carrying transmission routing problem model and design the interference-aware wireless energy-carrying transmission routing algorithm. During the pathfinding process, the maximum capacity allocation algorithm is used to calculate the maximum energy-carrying transmission capacity of the link. The interference-aware routing index selects the transmission method that maximizes the link capacity and the path that maximizes the transmission capacity.

In step 1), the signal-to-noise ratio received by the receiving node and the energy obtained in the energy-carrying transmission under interference are as shown in equation (1),

Among them, i represents the sending node, j represents the receiving node,

Represents the signal-to-noise ratio between links (i, j),

The available energy, ρ _ij represents the information on the power and the energy allocation rate, P _ij represents the transmission power between the links (i, j), h _ij represents the channel gain between the links (i, j), Ф _j represents the interfering node set of node j, P _l represents the transmission power of node l in the interference set,

with

Respectively represent the power of the antenna noise n _ij and the signal conversion noise z _ij , and ε represents the power conversion rate.

In step 2), the interference-aware maximum capacity allocation model is: according to the link channel capacity calculation formula, under the energy acquisition constraints, the transmission power and information and energy allocation rate are adjusted to make the link The capacity that can be transmitted is the largest, as in model (2).

Among them, Pc _j represents the minimum energy acquisition requirement, this value is related to the remaining energy of the node and the energy consumed by the node to forward,

It indicates the link capacity using energy-carrying transmission, W indicates the channel bandwidth, and P _max indicates the maximum transmission power.

In step 3), the algorithm for solving the interference-aware maximum capacity allocation model is to calculate the Lagrangian function of problem (2), such as equation (3).

According to the dual and sub-gradient method, the solution algorithm of problem (2) can be obtained.

The first step: random initialization

μ> 0, 0≤φ1, υ∈ (0,1), η> 1, k ← 1;

Step 2: According to

Solve the problem

The solution method is to find the partial derivative of the problem so that the partial derivative is 0, that is

available

Step 3: Check the termination condition, if | L ^k -L ^k-1 | ≤φ, then stop the iteration and output

As the approximate minimum point of the original problem in step 2); otherwise, go to step 4.

The fourth step: update μ, if || L ^k || ≥υ || L ^k-1 ||, then μ: = ημ.

Step 5: Update the multiplier

The sixth step: k: = k + 1, go to the second step.

In step 4), design interference-aware routing indicators and establish interference-aware energy-carrying transmission routing model:

The interference-aware routing indicator (IaCA) of the designed link is the maximum available capacity of the link, as shown in formula (4), which is the maximum capacity of the information transmission link and the capacity of the energy-carrying transmission link value. The interference-aware routing index of a path is the minimum value of the interference-aware routing index of all links on the path, that is, the capacity of the path.

IaCA _sd = min {IaCA _sc , IaCA _cd }, c∈Path _sd (5)

Among them, c is a node on the sd path.

The problem of selecting the maximum capacity path for the source node s to the destination node d through IaCA as the routing index through the joint interference perception-maximized energy-carrying capacity allocation model can be formalized as a problem (6).

Among them, r _ij indicates whether the selected path contains a link (i, j), 1 indicates inclusion, and 0 indicates no inclusion. The required energy supplement value Pc _{j is} determined by the next hop node of node j and the transmission power P _{jk from} node j to the next hop node, so it is set to the transmission power P _jk required by the node to continue forwarding.

In step 5), the interference-aware wireless energy-carrying transmission routing algorithm is:

The algorithm inputs are the network topology graph G and the source node and destination node ( _sk , _dk ) of the kth stream, and the flow information of the first k-1 streams includes the source node, destination node and path information of the stream. Outputs the path selected for the k-th flow and the distribution rate and transmission power of the nodes on the path. The main structure of the algorithm comes from the Dijkstra algorithm,

Routing index from storage node i to destination node d _k (i.e.

) And the next-hop node, S is the set of nodes whose paths have been determined, and Q is the node queue of undetermined paths with the routing index as the key.

The first step: initialize the routing index of all nodes to be positive infinity and the next hop node is empty;

Step 2: Initialize the routing index of the destination node to 0, S is empty and queue Q is all nodes.

Step 3: Take the node j with the smallest routing index from the queue Q until Q is empty;

Step 4: Perform steps 5 to 7 on the links (i, j) formed by all adjacent nodes i;

The fifth step: use the interference algorithm to calculate the interference of the link (i, j), and then use the interference-aware maximum capacity allocation model to solve the algorithm to calculate the maximum capacity that can be obtained using energy-carrying transmission

Corresponding distribution rate and transmission power

Step 6: Use the link number algorithm of the shared node to calculate the link number of the shared node with the link (i, j). The actual usable capacity is the maximum capacity divided by the number of shared node links plus one. Routing index of the link

Step 7: Compare link routing indicators

Routing index with node j

Get the temporary routing index of node i

in case

Routing index of current node i

If it is large, then update the routing index, next hop node, allocation rate, transmission power and forwarding requirements of node i. If the remaining power of node i is lower than the minimum power requirement, then the energy acquisition requirement is the transmission power, otherwise it is 0.

In the fifth step of step 5), the interference algorithm is:

The interference existing in the link is calculated according to the path of the existing k-1 streams and the transmission power of the nodes on the path. For link (i, j), node l is a two-hop neighbor of node j, it is considered that within the interference range of node j, if there is a flow through node l and the next hop node on the flow is not i or j Then, node 1 will cause interference to link (i, j). If multiple flows pass through node 1, then the maximum transmission power of the nodes in all flows is taken as the interference power. Then, the interference generated by all the existing l is accumulated, that is, the product of the accumulated interference power and the channel gain of l to j.

In the sixth step of step 5), the link number algorithm of the shared node is:

The number of links with the shared nodes of the existing k-1 flows is divided into three types according to the status of the nodes through which the flows pass. In the first case, the flow passes through the sending node. If the sending node is not the source or destination node of the existing flow, the number of shared node links is 2, otherwise it is 1. In the second case, the flow passes through the receiving node. If the receiving node is not the source or destination node of the existing flow, the number of shared node links is 2, otherwise it is 1. In the third case, the flow passes through the sending node and the receiving node at the same time. The shared node link is the union of the first two cases. The first two cases have calculated the link (i, j), and the number is equal to the first case plus The number of the second case minus (i, j) is calculated once again.

For the number of shared node links that are currently calculating the k-th stream, there are three cases. In the first case, if the sending node is the source node or the receiving node is the destination node, then the link has only subsequent or predecessor links, and the number of shared node links is 1. In the second case, if the sending node is the source node and the receiving node is the destination node, then the link has no follow-up or predecessor links, and the number of shared node links is 0. In the third case, if the sending node is not the source node and the receiving node is not the destination node, then there are follow-up and precursor links in the link, and the number of shared node links is 2.

Compared with the prior art, the present invention has the following beneficial effects: Compared with information transmission without considering interference and considering interference, the present invention has a higher path capacity for interference-aware wireless energy-carrying transmission routes.

BRIEF DESCRIPTION

Figure 1 is a schematic diagram of an energy-carrying transmission route under interference;

2 is a power split mode wireless power transmission structure diagram;

Figure 3 is a schematic diagram of the impact of interference on energy-carrying transmission;

Figure 4 is an analysis of the impact of interference on energy-carrying transmission; (a) the relationship between interference and capacity; (b) the relationship between interference and information and energy distribution rate;

Figure 5 is a schematic diagram of the shared node link classification; (a) the existing flow passes the sending node; (b) the existing flow passes the receiving node; (c) the existing flow passes both the sending and receiving nodes;

Figure 6 is a schematic diagram of interference-aware energy-carrying routing; (a) initial network flow; (b) new flow arrival (without energy replenishment); (c) new flow arrival (with energy replenishment);

7 is a distribution diagram of the improvement of downstream performance with different numbers of streams;

Figure 8 is the average flow capacity of the second type flow under different flow numbers;

Fig. 9 is the average flow capacity of the third type flow under different flow numbers.

detailed description

There are generally multiple service flows in a multi-hop wireless network, and the service flows may interfere with each other. Therefore, when selecting an energy-carrying transmission path for a service flow, interference needs to be considered to ensure the efficiency of end-to-end transmission of the service flow.

Because the impact of interference on energy-carrying transmission is multifaceted, energy-carrying routing strategies cannot blindly reduce and avoid interference, and it is necessary to design interference-aware routing strategies. Consider the interaction between interference, energy-carrying transmission and routing, determine the information and energy distribution rate of the energy-carrying link in the case of interference, and at the same time evaluate the impact of interference on the path, and make full use of the interference to construct the energy-carrying transmission path. As shown in Figure 1, flow F1 already exists. When selecting a path for flow F2, it is necessary to evaluate that the path with less interference is selected

Or choose the path with more interference

At the same time

Determine the appropriate information and energy distribution rate. The key in multi-service flow is the impact of interference on energy-carrying transmission and routing, so we use theoretical analysis and experimental verification to analyze and design.

The wireless energy transmission node needs to use different circuit processing modules to convert the received radio frequency signal into information or energy. Therefore, the principle of the wireless energy transmission design is to equip the wireless reception node with two sets of modules: information decoding module and energy acquisition module , Let these two sets of different circuit processing modules work together. The information decoding module (Information Decoder, ID) converts the radio frequency signal into a baseband signal through a low-pass filter, and then converts the baseband signal into data through an analog-to-digital converter and decoder. The energy harvesting module (Energy Harvester, EH) forms a rectifier through a diode and a low-pass filter to convert the radio frequency signal into DC power. According to the different cooperative working methods, the architecture mode of the receiving node can be divided into two types: time division switching mode (Time Switching mode, TS) and power splitting mode (Power Splitting mode, PS). In TS mode, the receiving node periodically switches between information decoding and energy acquisition. When switching to information decoding, all received radio frequency signals are decoded. When switching to energy acquisition, all wireless radio frequency signals are converted into energy. In PS mode, the receiving node splits the radio frequency signal into two independent streams with different powers, and then uses the two streams for information decoding and energy conversion, as shown in Figure 2, where ρ represents the information and power Energy distribution rate, n and z represent channel noise and information conversion noise, respectively. The present invention mainly considers the energy-carrying transmission in the PS mode.

Considering the presence of interference, the sending node i sends the signal x (t) with P _ij power, and E [x] = 1, as shown in FIG. 3, the signal received by the receiving node j is

Where h _ij represents the channel gain between links (i, j), Φ _j represents the interference node set of node j, and P ₁ represents the transmission power of node 1 in the interference set.

If information transmission is used, the signal-to-noise ratio and channel capacity of the signal received by the receiving node are:

Where γ _ij represents the signal-to-noise ratio between links (i, j),

Respectively represent the power of antenna noise n _ij and signal conversion noise z _ij ,

Represents the link capacity when using information transmission, and W represents the channel bandwidth.

If energy-carrying transmission is used, after power splitting, the signals used for information decoding and energy acquisition are y ^ID (t) and y ^EH (t).

Then the signal-to-noise ratio received by the receiving node and the energy obtained are shown in equation (5),

Among them, ε represents the power conversion rate.

According to the signal-to-noise ratio and link channel capacity calculation formula obtained by energy-carrying transmission, an information and energy allocation scheme model for maximizing interference-aware transmission link capacity (referred to as interference-aware maximum energy-carrying capacity allocation model) can be established As in question (6). When the energy acquisition constraints are met, the transmission power and information and energy distribution rate are adjusted to maximize the capacity of the link using energy-carrying transmission.

Indicates the link capacity when carrying energy transmission.

For the problem (6), the Lagrange function of the problem (6) is obtained by introducing the dual variables a and b as formula (7), and then according to the dual and sub-gradient method, the solution algorithm of the problem (6) is obtained as shown in algorithm 1. .

Algorithm 1 Maximum interference-aware transmission capacity allocation algorithm for energy-carrying transmission links

Use the interference-aware maximum energy-carrying capacity allocation model to analyze the specific impact of interference on energy-carrying transmission. To fix the location of the transmitting node, receiving node and interfering node, and the transmitting power of the transmitting node, only change the transmitting power P _{l of the} interfering node. According to the interference-aware maximum energy carrying capacity allocation model (6), analyze the interference power and link capacity, The relationship between information and energy distribution rate is shown in Figure 4.

From Figure 4 (a), it can be seen that the impact of interference on information transmission is that the greater the interference, the smaller the link capacity. The impact of interference on energy-carrying transmission is divided into two stages: In the first stage, no matter how the information and energy allocation rate are adjusted, the energy acquisition requirements of the receiving node cannot be met, the energy-carrying transmission link cannot be established, and the link does not exist. With the emergence of interference, interference can be used as a source of energy supplement. When the interference increases to a certain value (16mw), it can meet the energy acquisition requirements of the receiving node. The energy-carrying transmission link is successfully established and enters the second stage. In the second stage, after the energy-carrying transmission link is established, as the interference further increases, the link capacity decreases. Under the same interference conditions, energy-carrying transmission can reach the same capacity as information transmission.

Figure 4 (b) shows the value of the information and energy distribution rate when the maximum capacity is reached under different interference conditions in the second stage. When the energy-carrying link is just established, the signal power received by the receiving node is only sufficient to meet the energy acquisition requirements. The signal power is mostly used for energy acquisition, that is, the distribution rate ρ _{ij is} close to 0, and 1-ρ _{ij is} close to 1. As the interference increases, the signal power received by the receiving node increases, and for the same energy replenishment requirement, the ratio 1-ρ _ij for energy acquisition can be reduced, and the allocation rate ρ _ij can be increased. The interference is proportional to the distribution rate.

According to the analysis results, interference can help build energy-carrying links, but as long as the energy-carrying link is established, the interference is as small as possible, which can guide the principle of formulating interference-aware routing strategies: when energy-carrying links cannot be constructed, Select the node with the most interference as the next hop node to ensure the connectivity of the path; once the energy-carrying link can be built, the interference needs to be avoided. That is to say, select the node with the least interference from the nodes that can form the energy-carrying link to ensure the high efficiency of the path.

In the network, the link can use either information transmission or energy-carrying transmission. Therefore, according to the link capacity of the information transmission and the link capacity of the energy-carrying transmission, the interference-aware routing indicator (Inference-aware Capacity Available metric, IaCA) of the link is designed as the maximum available capacity of the link, as shown in equation (8) It is the maximum value of the capacity of the information transmission link and the capacity of the energy-carrying transmission link.

The interference-aware routing index of a path is the minimum value of the interference-aware routing index of all links on the path, that is, the capacity of the path.

IaCA _sd = min {IaCA _sc , IaCA _cd }, c∈Path _sd (9)

Among them, c is a node on the sd path.

The problem of selecting the maximum capacity path for the source node s to the destination node d using the IaCA as the routing index through the joint interference perception-maximized energy-carrying capacity allocation model can be formalized as a problem (10).

When the node's remaining power is greater than the remaining power requirement E _min , the node does not need to replenish energy, then the energy acquisition demand Pc _j is 0, and the information and energy distribution rate is 1. At this time, the capacity calculated by the maximum energy carrying capacity model is the same Equal to the capacity of information transmission, ie

When the remaining power of the node is less than E _min , the node needs to supplement energy. Therefore, the above model can be simplified to

There are three sets of variables r, ρ, P in the routing model. Since Pc _j is an uncertain value, the routing algorithm for problem (11) cannot directly use the virtual link method. Therefore, consider starting from the destination node to determine Pc _j to perform route calculation, and design interference-aware energy-carrying routing algorithm. During the pathfinding process, algorithm 1 is used to calculate the maximum energy-carrying transmission capacity of the link. According to the interference-aware routing index , Select the transmission method that maximizes the link capacity and the path that maximizes the transmission capacity.

Routing index from storage node i to destination node d _k (i.e.

) And the next-hop node, S is the set of nodes whose paths have been determined, and Q is the node queue of undetermined paths with the routing index as the key. Lines 1-4 initialize the routing index of all nodes to positive infinity and the next hop node is empty. Lines 5-7 initialize the routing index of the destination node to 0, S is empty and queue Q is all nodes. The node j with the smallest routing index is selected from the queue Q, and the following operations are performed on all edges (i, j) formed by adjacent nodes i. Lines 12-13 use algorithm 2 to calculate the interference of the existing k-1 streams on the link (i, j), and then use algorithm 1 to calculate the maximum capacity that can be obtained using energy-carrying transmission

And the corresponding allocation rate and transmission power

Lines 14-16 use Algorithm 4 to calculate the number of links that share the node with the link (i, j). Both the energy-carrying transmission and the information transmission link (i, j) must share the channel with the link of the sharing node, The actual usable capacity needs to be divided by the number of shared node links plus 1, to obtain the link routing index at this time

Lines 17-24 compare the routing indicators of the link

Routing index with node j

Get the temporary routing index of node i

in case

Routing index of current node i

If it is large, then update the routing index, next hop node, allocation rate, transmission power and forwarding demand of node i. If the remaining power of node i is lower than the minimum power requirement, then the energy acquisition demand is the transmission power, otherwise it is 0. Until Q is empty, all nodes find the path to the destination node d _k .

Algorithm 2 Single-stream interference-aware routing algorithm

Interference-aware energy-carrying routing uses Algorithm 3 to calculate the interference present on the link based on the path of the existing k-1 streams and the transmission power of the nodes on the path. For the link (i, j), node l is the two-hop neighbor of node j, it is considered that within the interference range of node j, if there is a flow on node l and the next hop node on the flow is not i or j, Then, node 1 will cause interference to link (i, j). If multiple flows pass through node 1, then the maximum transmission power of the nodes in all flows is taken as the interference power. Then, the interference generated by all the existing l is accumulated, that is, the product of the accumulated interference power and the channel gain of l to j.

Algorithm 3 interference calculation

The interference to link (i, j) in Algorithm 3 only includes the interference generated by the neighboring nodes that do not pass through nodes i and j. When all the links passing through the current k-1 streams share the node with link (i, j), The flow through i and j cannot be reflected in Algorithm 3. In this case, link (i, j) can share the channel with the shared node's link through time division, so the actual usable capacity is the capacity calculated by the interference model divided by the number of shared node's links plus 1, where The added 1 is the link (i, j) itself.

According to the existing k-1 flow nodes, the number of shared node links can be divided into three types, as shown in Figure 5. In the first case, the flow passes through the sending node. As shown in FIG. 5 (a), for link (7, 2), stream 1 passes through node 7, and there are two links (3, 7) and (7, 5) sharing the node with (7, 2). For link (3, 4), stream 1 passes through node 3, but 3 is the source node of the stream, and there is only one link (3, 7) and (3, 4) shared node. In the second case, the flow passes through the receiving node. As shown in FIG. 5 (b), also if the receiving node is not the source or destination node of the existing flow, the number of shared node links is 2, otherwise it is 1. In the third case, the flow passes through the sending and receiving nodes simultaneously. As shown in Figure 5 (c), the shared node link is the union of the first two cases, and the link (i, j) is calculated in the first two cases, so the number of shared node links is equal to the first case Add the quantity of the second case minus 1.

For the k-th stream that is currently being calculated, the number of shared node links needs to be calculated, which can be divided into three cases. In the first case, if the sending node is the source node or the receiving node is the destination node, then the link has only subsequent or predecessor links, and the number of shared node links is 1. In the second case, if the sending node is the source node and the receiving node is the destination node, then the link has no follow-up or predecessor links, and the number of shared node links is 0. In the third case, if the sending node is not the source node and the receiving node is not the destination node, then there are follow-up and precursor links in the link, and the number of shared node links is 2.

Therefore, Algorithm 4 accumulates the number of shared node links of the existing k-1 streams, plus the number of shared node links existing in the k-th stream this time.

Algorithm 4 Number of shared channel links

As shown in Fig. 6 (a), the path of the flow F ₁ is

As shown in Fig. 6 (b), a new flow F ₂ (2 → 6) arrives. The interfering nodes of node 4 include 2, 3, 6, 7 and 8, and there are obstacles between

nodes

4 and 5. The interfering nodes of node 8 include 2, 3, 4, 5, 6, and 7.

Nodes

3, 5 and 7 are in stream F ₁ and will interfere with F ₂ . Node 8 is closer to these nodes, and the interference is greater than that of node 4. Therefore, F ₂ selects node 4 to form the path

According to the capacity calculation under interference, the capacity of the link is respectively

The end-to-end capacity of stream F2 is

As shown in Fig. 6 (c), if new flows arrive,

nodes

4 and 8 need energy replenishment. Node 2 cannot provide enough energy to node 4, the energy-carrying link cannot be established, and the original path cannot be selected. Need to consider other paths, such as

Since the interference at node 8 becomes the source of energy supplementation, the energy-carrying link between

nodes

2 and 8 can be established. The capacity of the link is

The end-to-end capacity of stream F2 is

Taking the topology of Fig. 5 as an example, we build a network with medium network density, scale, and medium residual energy to analyze and test the performance of the proposed scheme. The network includes 9 nodes, and the remaining power of

nodes

1, 3, 4, and 8 is insufficient to forward, and energy needs to be added for forwarding. Randomly select 2 to 4 streams of non-repetitive source and destination nodes, and randomly select 50 sets of source and destination node pairs for each stream number. The evaluation index is the capacity of the last stream selected, that is, the interference routing index of the path.

Depending on whether interference is considered and the transmission method used, the comparison scheme includes four types of information transmission that does not consider interference (WITwoi, WIT without interference), energy-carrying transmission that does not consider interference (SWIPTwoi, SWIPT without interference), and information that considers interference Transmission (WITwi, WIT with interference), energy-carrying transmission considering interference (SWIPTwi, SWIPT with interference). The first three schemes can be implemented using the algorithm framework of the fourth scheme, but the calculation method in the routing indicators is different. Among them, WITwi uses formula (2), WITwoi and SWIPTwoi do not consider interference, and remove formulas (2) and (5) The interference part is formula (11) and (12) respectively.

First analyze the improvement of 50 sets of evaluation indexes for different flow distributions under the same flow number. Regardless of the amount of traffic, it can be divided into three categories. In the first category, the flow capacity of the four algorithms is equal. In the second category, transmission considering interference is higher than transmission not considering interference, but information transmission considering interference is equal to energy-carrying transmission considering interference. In the third category, energy-carrying transmission considering interference is higher than information transmission considering interference.

Previous literature pointed out that according to the distribution of the source and destination nodes of the flow, not all flows can use energy-carrying transmission to improve performance. The path selected using the proposed scheme may be the same as the other three. The first and second types are this Kind of situation. The first four options have the same path. The second type SWIPTwi and WITwi choose the same path, but different from the first two, the result of routing considering interference is different from the result of routing without considering interference, but the result of routing using energy transmission and information transmission is the same. The third category, considering the interference-carrying energy transmission routing results is also different from considering the interference information transmission, it can be seen that energy-carrying transmission improves performance. Therefore, these three categories are named No gain (no gain), Gain from interference (gain from interference), Gain from SWIPT (gain from SWIPT). Figure 7 shows the proportion of different types of flows in all flows. It can be seen from Figure 7 that the sum of the third and second types of flow is greater than 65%, and the proportion of the first type decreases significantly as the number of flows increases, and the third type increases from 30% to 70% . This means that as the number of streams increases, there is more potential for performance gains from considering interference and SWIPT.

In the second type of stream that considers interference to improve performance, the average path capacity of the four schemes is analyzed, as shown in Figure 8. Under the number of three streams, the average value of the capacity of the interference path is about 1.4 times that of the transmission of interference information.

Finally, in the third type of stream that has improved performance due to energy-carrying transmission, the average path capacity of the four schemes is analyzed, as shown in Figure 9. The interference-energy transmission is considered to be 90% to 382% higher than that without interference information transmission, and the interference-energy transmission is considered to be 30% to 110% higher than interference transmission.

Claims

An interference-aware wireless energy-carrying transmission routing method, characterized in that it includes the following steps:

1) Use the physical interference model to establish an energy-carrying transmission model under interference;

2) Based on the energy-carrying transmission model under interference, and meeting the minimum energy acquisition requirements, construct an interference-aware maximum energy-carrying capacity allocation model;

3) Design a solution algorithm to maximize interference perception capacity allocation model;

4) Design interference-aware routing indicators, combine interference-aware maximum energy-carrying capacity allocation model, and establish interference-aware energy-carrying transmission routing model;

5) Solve the interference-aware energy-carrying transmission routing problem model, design the interference-aware wireless energy-carrying transmission routing algorithm, and use the maximum capacity allocation algorithm to calculate the maximum energy-carrying transmission capacity of the link during the pathfinding process. Perceived routing indicators, select the transmission method that maximizes the link capacity and the path that maximizes the transmission capacity.
The interference-aware wireless energy-carrying transmission routing method of claim 1, wherein in step 1), the energy-carrying transmission model under interference is
Among them, i represents the sending node, j represents the receiving node,
Represents the signal-to-noise ratio between links (i, j),
Represents available energy, ρ ij represents information on power and energy allocation rate, P ij represents transmission power between links (i, j), h ij represents channel gain between links (i, j), Φ j represents the interfering node set of node j, P l represents the transmission power of node l in the interference set,
with
Respectively represent the power of the antenna noise n ij and the signal conversion noise z ij , and ε represents the power conversion rate.
The interference-aware wireless energy-carrying transmission routing method according to claim 2, wherein in step 2), the maximum energy-carrying capacity allocation model is: according to the link channel capacity calculation formula, the energy acquisition constraint is satisfied Next, by adjusting the transmission power and information and energy distribution rate to maximize the capacity of the link using energy-carrying transmission:

Among them, Pc j represents the minimum energy demand,
It indicates the link capacity when carrying energy transmission, W indicates the channel bandwidth, and P max indicates the maximum transmission power.
The interference-aware wireless energy-carrying transmission routing method according to claim 3, wherein the algorithm for solving the interference-aware maximum energy-carrying capacity allocation model is:

1) Calculate the maximum energy carrying capacity allocation model of the maximum energy carrying capacity allocation model, as follows:

2) Random initialization
a 1 , b 1 ∈? , Μ> 0, 0≤φ1, υ∈ (0,1), η> 1, k ← 1;

3) According to
Solve the problem
The solution method is the right problem
Find the partial derivative so that the partial derivative is 0, ie
Then get

4) Check the termination condition, if | L k -L k-1 | ≤φ, then stop the iteration and output
As the approximate minimum point of the maximum energy carrying capacity allocation model; otherwise, go to step 4);

5) Update μ, if || L k || ≥υ || L k-1 ||, then μ: = ημ;

6) Update multiplier:

7) k: = k + 1, go to step 2).
The interference-aware wireless energy-carrying transmission routing method according to claim 2, wherein the interference-aware energy-carrying transmission routing problem model is:

Among them, r ij indicates whether the selected path contains a link (i, j), 1 indicates inclusion, and 0 indicates no inclusion; the required energy supplement value Pc j is from the next hop node of node j and node j to the next hop node The transmission power P jk is determined, so it is set to the transmission power P jk required for the node to continue forwarding.
The interference-aware wireless energy-carrying transmission routing method according to claim 2, wherein the interference-aware wireless energy-carrying transmission routing algorithm includes the following steps:

1) Initialize the routing indicators of all nodes to be positive infinity and the next hop node is empty;

2) The routing index of the initialization destination node is 0, S is empty and queue Q is all nodes;

3) Take the node j with the smallest routing index from the queue Q until Q is empty;

4) For the links (i, j) formed by all adjacent nodes i, perform the following steps 5) to 7);

5) Use the interference algorithm to calculate the interference of the link (i, j), and then use the interference-aware maximum capacity allocation model to solve the algorithm to calculate the maximum capacity that can be obtained using energy-carrying transmission
Corresponding distribution rate and transmission power

6) Use the link number algorithm of the shared node to calculate the link number of the shared node with the link (i, j). The actual usable capacity is the maximum capacity divided by the number of shared node links plus 1 to obtain the link at this time Routing index

7) Compare link routing indicators
Routing index with node j
Get the temporary routing index of node i
in case
Routing index of current node i
If it is large, then update the routing index, next hop node, allocation rate, transmission power and forwarding requirements of node i. If the remaining power of node i is lower than the minimum power requirement, then the energy acquisition requirement is the transmission power, otherwise it is 0.
The interference-aware wireless energy-carrying transmission routing method according to claim 5, wherein the interference algorithm comprises: calculating the existence of the link according to the path of the existing k-1 streams and the transmission power of the nodes on the path Interference, for link (i, j), node l is the two-hop neighbor of node j, it is considered that within the interference range of node j, if there is a flow through node l and the next hop node on the flow is not i Or j, node l will interfere with link (i, j). If multiple flows pass through node 1, the maximum transmission power of the nodes in all flows is taken as interference power. Then, the interference generated by all the existing l is accumulated, that is, the product of the accumulated interference power and the channel gain of l to j.
The interference-aware wireless energy-carrying transmission routing method according to claim 5, wherein the algorithm of the number of links of the shared node is: the number of links with the shared node of the existing k-1 flows, according to the flow through There are three types of node conditions: in the first case, the flow passes through the sending node. If the sending node is not the source or destination of the existing flow, the number of shared node links is 2, otherwise it is 1; in the second case, the flow passes through the receiving Node, if the receiving node is not the source or destination node of the existing flow, the number of shared node links is 2, otherwise it is 1; in the third case, the flow passes through the sending node and the receiving node at the same time, and the number of shared node links is the first two The sum of the cases minus 1; the number of links shared with the stream itself: in the first case, the sending node is the source node or the receiving node is the destination node, then the number of shared node links is 1; in the second case, the sending node is If the source node and the receiving node are destination nodes, the number of shared node links is 0; in the third case, the sending node is not the source node and the receiving node is not the destination node, then sharing The number of points is 2 link.