CN109600816B - Interference-aware wireless energy-carrying transmission routing method - Google Patents
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Abstract
The invention discloses an interference-aware wireless energy-carrying transmission routing method, which is used for researching the routing problem of a wireless multi-hop network and designing the routing method of the wireless multi-hop network by considering the effect and influence of interference on wireless energy-carrying transmission on information and energy. Firstly, an energy-carrying transmission model under interference is established by utilizing a physical interference model. And then, under the condition of meeting the requirement of minimum energy acquisition, constructing a maximum energy carrying capacity distribution model of interference perception, and designing a solving algorithm. And finally, designing an interference-aware wireless energy-carrying transmission routing algorithm, in the routing searching process, calculating the maximum energy-carrying transmission capacity of the link by using a maximum energy-carrying capacity allocation algorithm, and selecting the transmission mode of the link and the path with the maximum transmission capacity according to the interference-aware routing index. The experimental result shows that compared with the information transmission without considering interference and considering interference, the wireless energy-carrying transmission route with interference perception has higher path capacity.
Description
Technical Field
The invention relates to a routing method of a wireless multi-hop network using wireless energy-carrying transmission, in particular to a wireless energy-carrying transmission routing method with interference perception.
Background
The nodes in the multi-hop wireless network have routing functions and can forward data, so the method has the advantages of flexible networking, easy expansion, self-organization, self-repair, low deployment cost and the like, and the main forms comprise a multi-hop Wireless Sensor Network (WSNs), a Mobile Sensing network (Mobile Sensing Networks), an Ad hoc network and the like. Node energy limitation is a common problem with multi-hop wireless networks, which limits multi-hop wireless network availability and durability. Taking a sensor network as an example, a sensor node is usually powered by a battery, and the battery capacity is limited, so that after the electric quantity of the node is exhausted and dead, the problems of data acquisition incapability, data unreachable, detour and the like are caused.
Therefore, Energy Harvesting technology (Energy Harvesting) is proposed, and a wireless node supplements Energy by collecting solar Energy, wind Energy or thermal Energy in the surrounding natural environment, but the method depends on natural environment resources and has great uncertainty. Another technique utilizes radio waves to Transfer electrical energy, known as Wireless Power Transfer (WPT). Compared with natural environment energy sources, the wireless energy transmission is more stable, reliable and controllable. WPT mainly includes two modes: magnetic Resonance (Coupled Magnetic Resonance) and Radio Frequency Signal transmission (Radio Frequency Signal). Magnetic coupling resonance requires that the transmitting and receiving coils resonate at the same frequency, and the coils have a large volume and support a medium distance, so that radio frequency signals can realize long-distance energy transmission, and are of great interest.
Meanwhile, the radio frequency signal is also an effective carrying mode for data transmission, so a new Wireless transmission technology, namely Wireless portable energy transmission or Wireless Information and energy Simultaneous transmission (SWIPT), has recently appeared. Unlike Wireless Information Transfer (WIT), which only performs Information Transfer and WPT, which only performs energy Transfer, Wireless energy-carrying Transfer uses the same Wireless rf signal to Transfer Information and energy.
Wireless energy-carrying transmission has the following advantages: 1) energy supplement can be controllably carried out on the nodes while information is transmitted, and the nodes are prevented from dying due to electric quantity exhaustion; 2) compared with the information and energy separated transmission mode, the SWIPT transmission efficiency is higher. Energy and information are sent together without extra infrastructure, and the method can be applied to some special scenes (such as in concrete); 3) interference can be an effective source of energy using SWIPT. Meanwhile, wireless energy-carrying transmission also faces some problems, such as shortening of information transmission distance due to energy transmission, and low energy transmission efficiency due to high wireless radio frequency signal loss and fading, and is mainly solved by a multi-antenna technology [5] at present.
The use of energy-carrying transmission in a multi-hop wireless network may provide the following benefits: 1) all nodes can obtain energy from interference and noise radio frequency signals, and the energy obtaining range covers the whole network; 2) by taking the received energy as compensation of data forwarding energy consumption, the energy acquired by a certain node can be purposefully and controllably transmitted and shared in the network in a multi-hop manner, and the network energy distribution is balanced; 3) energy acquisition, transmission and information transmission equipment which are complex and separated are not required to be equipped, the requirement on the volume of the node is reduced, and the cost is saved.
However, many problems are faced with the application of energy-carrying transmissions to multi-hop wireless networks. The core problem of the multi-hop wireless network is to determine the next hop node according to the routing index. When the energy-carrying transmission is applied to a multi-hop network, optimal information and energy distribution needs to be determined for each hop of data forwarding, and different information and energy distributions adversely affect network topology and optimal path selection, and interdependence and influence between routing and energy-carrying transmission. The routing of multiple service flows determines the distribution of traffic, which will generate interference of different degrees, and the interference signal will reduce the quality of information transmission and can also be used as an energy source. The influence of interference on energy-carrying transmission is not only unilateral, but also multifaceted, and the interference degree needs to be considered to be proper. The interdependent impact of information and energy allocation, routing, and interference is extremely challenging to solve.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an interference-aware wireless energy-carrying transmission routing method aiming at the defects of the prior art, so as to improve the transmission performance of a multi-hop wireless network.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a wireless energy-carrying transmission routing method based on interference perception specifically executes the following processes:
step 1), establishing an energy-carrying transmission model under interference by using a physical interference model;
step 2), constructing an interference perception maximum energy carrying capacity distribution model based on an energy carrying transmission model under interference and meeting the requirement of minimum energy acquisition,
step 3), designing a solving algorithm of the interference perception maximum energy carrying capacity distribution model;
step 4), designing an interference perception route index, combining an interference perception maximum energy carrying capacity distribution model, and establishing an interference perception energy carrying transmission route problem model;
and 5) solving the interference-aware energy-carrying transmission routing problem model to design an interference-aware wireless energy-carrying transmission routing algorithm, calculating the maximum energy-carrying transmission capacity of the link by using a maximum capacity allocation algorithm in the route searching process, and selecting a transmission mode enabling the maximum link capacity and a path with the maximum transmission capacity according to the interference-aware routing index.
In step 1), the signal-to-noise ratio received by the receiving node and the obtained energy in the energy-carrying transmission under the interference are shown as formula (1),
where i denotes a transmitting node, j denotes a receiving node,
representing the signal-to-noise ratio between links (i, j),
available energy, ρijRespectively representing information on power and energy distribution ratio, PijRepresents the transmit power between links (i, j), hijDenotes the channel gain between links (i, j), phijSet of interfering nodes, P, representing node jlRepresents the transmit power of the node/in the interference set,
and
respectively representing antenna noise nijSum signal conversion noise zijRepresents the power conversion rate of the power.
In step 2), the interference-aware maximum capacity allocation model is: according to a link channel capacity calculation formula, under the condition that energy acquisition constraint is met, the capacity of energy-carrying transmission adopted by a link is maximized by adjusting the sending power and the information and energy distribution rate, such as a model (2).
Wherein PcjRepresenting the lowest energy harvesting requirement, which is related to the remaining energy of the node and the energy consumed by the node for forwarding,
indicating the link capacity using energy-carrying transmission, W indicating the channel bandwidth, PmaxIndicating the maximum transmit power.
In step 3), the solution algorithm of the interference-aware maximum capacity allocation model is as follows: the lagrangian function of problem (2) is calculated as equation (3).
The solution algorithm for problem (2) can be obtained from the method according to dual and sub-gradients.
The first step is as follows: random initialization
The second step is that: according to
Solving a problem
The solution is to solve the problem by solving the partial derivatives so that the partial derivatives are 0, i.e.
Can obtain
The third step: checking for termination conditions if Lk-Lk-1If | is less than or equal to phi, stopping iteration and outputting
As an approximate minimum point of the original problem in step 2); otherwise, turning to step 4.
The fourth step: update μ if Lk||≥υ||Lk-1If, then μ: η μ.
The fifth step: updating multipliers
And a sixth step: k ═ k +1, go to the second step.
In step 4), designing an interference-aware routing index and establishing an interference-aware energy-carrying transmission routing problem model are as follows:
an interference-aware routing index (IaCA) of a link is designed to be the maximum Available Capacity of the link, as shown in formula (4), that 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, i.e. the capacity of the path.
IaCAsd＝min{IaCAsc,IaCAcd}，c∈Pathsd (5)
Where c is the node on the sd path.
The problem of the maximum capacity path from the source node s to the destination node d is selected by taking IaCA as a routing index through a joint interference perception maximum energy carrying capacity distribution model, and can be formalized as a problem (6).
Wherein r isijIndicating whether the selected path contains link (i, j), 1 indicates contained, and 0 indicates not contained. Required supplementary energy value PcjNode j's next hop node and node j's transmit power P to next hop nodejkDetermines, therefore, the transmission power P required for the node to continue forwardingjk。
In step 5), the interference-aware wireless energy-carrying transmission routing algorithm is as follows:
the algorithm inputs are a source node and a destination node(s) of a network topological graph G and a k flowk,dk) And the flow information of the first k-1 flows comprises source node, destination node and path information of the flows. And outputting the path selected for the k-th flow and the distribution rate and the transmission power of the nodes on the path. The main architecture of the algorithm is derived from Dijkstra's algorithm,
store node i to destination node dkIs a route index (i.e. a route index of
) And the next hop node, S is the determined pathAnd Q is a node queue of an undetermined path with the routing index as a key value.
The first step is as follows: initializing the routing indexes of all nodes to be infinite and the next hop node to be null;
the second step is that: and initializing the routing index of the destination node to be 0, wherein S is empty and the queue Q is all nodes.
The third step: taking out the node j with the minimum routing index from the queue Q until Q is empty;
the fourth step: executing the fifth step to the seventh step on all links (i, j) formed by the adjacent nodes i;
the fifth step: calculating the interference of the link (i, j) by using an interference algorithm, and then calculating the maximum capacity obtainable by energy-carrying transmission by using an interference-aware maximum capacity allocation model solving algorithm
Corresponding allocation rate and transmission power
And a sixth step: calculating the number of the links sharing the nodes with the links (i, j) by using a link number algorithm of the sharing nodes, and obtaining the routing index of the link at the moment by dividing the actually usable capacity by the maximum capacity by adding 1 to the number of the links of the sharing nodes
The seventh step: comparing route metrics of links
And the route index of node j
Obtaining temporary routing index of node i
If it is not
Route index of current node i
If the residual capacity of the node i is lower than the lowest capacity requirement, the energy acquisition requirement is the transmission power, otherwise, the energy acquisition requirement is 0.
In the fifth step of step 5), the interference algorithm is as follows:
and calculating the interference existing in the link according to the paths of the existing k-1 flows and the transmission power of the nodes on the paths. For the link (i, j), if the node l is a two-hop neighbor of the node j, the node l is considered to be in the interference range of the node j, if a flow passes through the node l and the next hop node on the flow is not i or j, the node l can generate interference on the link (i, j), and if a plurality of flows pass through the node l, the maximum transmission power of the nodes in all the flows is taken as the interference power. All l generated interference present is then accumulated, i.e. the product of the accumulated interference power and the channel gain l to j.
In the sixth step of step 5), the algorithm of the number of links of the shared node is as follows:
the number of links with the shared nodes of the existing k-1 flows is divided into three types according to the conditions of the nodes passed by the flows. In the first case, the flow passes through the sending node, and 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, and 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 both the sending node and the receiving node, the shared node link is the union of the first two cases, both of which have calculated link (i, j), the number of which is equal to the sum of the first case plus the second case minus the number of cases (i, j) that has been repeatedly calculated once.
There are three cases for the number of links of the shared node of the kth flow which is currently being calculated. In the first case, the sending node is the source node or the receiving node is the destination node, then the link only has the subsequent or previous link, and the number of the shared node links is 1. In the second case, the sending node is the source node and the receiving node is the destination node, then there is no subsequent or previous link for the link, and 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 the links have subsequent and previous links, and the number of shared node links is 2.
Compared with the prior art, the invention has the beneficial effects that: compared with information transmission without considering interference and considering interference, the interference-aware wireless energy-carrying transmission route has higher path capacity.
Drawings
FIG. 1 is a schematic diagram of energy-carrying transmission routing under interference;
FIG. 2 is a block diagram of a power splitting mode wireless energy carrying transmission;
FIG. 3 is a schematic illustration of the effect of interference on energy-carrying transmission;
FIG. 4 is a graph of interference impact on energy-carrying transmissions; (a) interference versus capacity; (b) interference versus information and energy allocation rate;
FIG. 5 is a schematic diagram of a shared node link classification; (a) existing flows pass through the sending node; (b) the existing flow passes through the receiving node; (c) existing flows pass through both the sending and receiving nodes;
FIG. 6 is a schematic diagram of interference aware energy-carrying routing; (a) an initial network flow; (b) new stream arrival (no energy replenishment required); (c) new stream arrival (energy replenishment required);
FIG. 7 is a graph of flow performance improvement at different numbers of flows;
FIG. 8 is the average flow capacity for the second type of flow at different flow numbers;
fig. 9 is the average flow capacity of the third type of flow for different numbers of flows.
Detailed Description
In a multi-hop wireless network, there are generally multiple traffic flows, and the traffic 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 high efficiency of end-to-end transmission of the service flow.
Since the influence of interference on energy-carrying transmission is manifold, the energy-carrying routing strategy cannot reduce and avoid the interference at once, and a routing strategy for sensing the interference needs to be designed. And considering the interaction among interference, energy-carrying transmission and routing, determining the information and the energy distribution rate of the energy-carrying link under the interference condition, simultaneously evaluating the influence of the interference on the path, and fully utilizing the interference to construct the energy-carrying transmission path. As in fig. 1, flow F1 already exists, and when routing flow F2, the evaluation is needed to select a path with less interference
Or selecting a path with more interference
At the same time, the energy-carrying link
And
appropriate information and energy allocation rates are determined. The key of the multi-service flow is the influence of interference on energy-carrying transmission and routing, so a method of theoretical analysis plus experimental verification is adopted for analysis and design.
The wireless energy-carrying transmission node needs to convert received wireless radio frequency signals into information or energy by using different circuit processing modules, so that the principle of wireless energy-carrying transmission design is that two sets of modules are arranged for a wireless receiving node: the information decoding module and the energy acquisition module enable the two different circuit processing modules to work cooperatively. An Information decoding block (ID) converts a 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 a Decoder. The Energy Harvester module (Energy Harvester, EH) converts the radio frequency signal into direct current through a rectifier formed by a diode and a low-pass filter. According to different cooperative working modes, the architecture modes of the receiving node can be divided into two types: time Switching mode (TS) and Power Splitting mode (PS). In the TS mode, a receiving node periodically switches between information decoding and energy acquisition, all received radio frequency signals are subjected to information decoding when the information decoding is switched, and all the received radio frequency signals are converted into energy when the energy acquisition is switched. 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, respectively, as shown in fig. 2, where ρ represents information on power and energy distribution ratio, and n and z represent channel noise and information conversion noise, respectively. The invention mainly considers the energy-carrying transmission of the PS mode.
Considering the presence of interference, the transmitting node i is given PijPower transmission signals x (t), and E [ x]As shown in fig. 3, the signal received by the receiving node j is 1
Wherein h isijDenotes the channel gain between links (i, j), phijSet of interfering nodes, P, representing node jlRepresenting the transmit power of the node/in the interference set.
If information transmission is adopted, the signal-to-noise ratio and the channel capacity of the signals received by the receiving node are as follows:
wherein, γijRepresenting the signal-to-noise ratio between links (i, j),
respectively representing antenna noise nijSum signal conversion noise zijThe power of (a) is determined,
indicating the link capacity when information transmission is employed and W indicates the channel bandwidth.
If energy-carrying transmission is used, the signal used for information decoding and energy acquisition, respectively, after power splitting is yID(t)，yEH(t)。
Then the received snr and the obtained energy at the receiving node are as shown in equation (5),
where ε represents the conversion rate of power.
According to a signal-to-noise ratio obtained by energy carrying transmission and a link channel capacity calculation formula, an interference-aware information and energy distribution scheme model (referred to as an interference-aware maximum energy carrying capacity distribution model for short) for maximizing the capacity of the energy carrying transmission link can be established as a problem (6). Under the condition of meeting the energy acquisition constraint, the capacity of energy-carrying transmission adopted by a link is maximized by adjusting the transmission power and the information and energy distribution rate.
Wherein PcjRepresenting the lowest energy harvesting requirement, which is related to the remaining energy of the node and the energy consumed by the node for forwarding,
indicating the link capacity when energy-carrying transmission is used.
For the problem (6), a lagrangian function of the problem (6) is obtained by introducing dual variables a and b as shown in a formula (7), and then a solving algorithm of the problem (6) is obtained according to a dual and sub-gradient method and is shown in an algorithm 1.
And analyzing the specific influence of the interference on energy-carrying transmission by utilizing an interference-aware maximum energy-carrying capacity allocation model. Fixing the positions of transmitting, receiving and interfering nodes, and the transmitting power of the transmitting node, varying only the transmitting power P of the interfering nodelAnd analyzing the relation of interference power and link capacity, information and energy distribution rate according to the interference perception maximization energy carrying capacity distribution model (6), as shown in figure 4.
From fig. 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 influence of interference on energy-carrying transmission is divided into two stages: in the first stage, no matter how information and energy distribution rate are adjusted, the requirement of receiving node energy acquisition cannot be met, an energy-carrying transmission link cannot be established, and a link does not exist. With the occurrence of interference, the interference can be used as a source of energy supplement, when the interference is increased to a certain value (16mw), the energy acquisition requirement required by the receiving node can be met, the energy-carrying transmission link is successfully established, and the second stage is entered. In the second phase, after the energy-carrying transmission link is established, the link capacity decreases as the interference increases further. Under the same interference condition, the energy-carrying transmission can reach the same capacity as the information transmission.
Fig. 4(b) shows the values of the information and the energy allocation rate when the maximum capacity is reached under different interference conditions in the second stage. When an energy-carrying link is just established, the signal power received by a receiving node only can meet the energy acquisition requirement, and most of the signal power is used for energy acquisition, namely the distribution rate rhoijClose to 0, 1-rhoijClose to 1. As the interference increases, the received signal power at the receiving node increases, and for the same energy replenishment requirement, the ratio 1- ρ for energy acquisitionijThe allocation rate p can be reducedijAnd (4) increasing. Interference is proportional to the allocation rate.
According to the analysis result, the interference can help to construct an energy carrying link, but as long as the energy carrying link is established, the interference is smaller as better, and the principle of making an interference perception routing strategy can be guided: when the energy-carrying link cannot be constructed, selecting a node with large interference as a next hop node to ensure the connection of the path; once an energy-carrying link can be constructed, interference needs to be avoided. That is, the nodes that can form the energy-carrying link are selected to minimize interference to ensure the high efficiency of the path.
In the network, the link may adopt information transmission or energy-carrying transmission. Therefore, according to the link capacity of information transmission and the link capacity of energy-carrying transmission, an interference-aware routing index (IaCA) of the link is designed to be the maximum available capacity of the link, as shown in formula (8), that is, the maximum value of the information transmission link capacity and the energy-carrying transmission link capacity.
The interference aware routing index of a path is the minimum value of the interference aware routing index of all links on the path, i.e. the capacity of the path.
IaCAsd＝min{IaCAsc,IaCAcd}，c∈Pathsd (9)
Where c is the node on the sd path.
The problem of the maximum capacity path from the source node s to the destination node d is selected by taking IaCA as a routing index through a joint interference perception maximum energy carrying capacity distribution model, and can be formalized as a problem (10).
Wherein r isijIndicating whether the selected path contains link (i, j), 1 indicates contained, and 0 indicates not contained. Required supplementary energy value PcjNode j's next hop node and node j's transmit power P to next hop nodejkDetermines, therefore, the transmission power P required for the node to continue forwardingjk。
When the residual capacity of the node is larger than the residual capacity requirement EminIn time, the nodes do not need to supplement energy, and then the energy acquisition requirement Pc j0, and an information and energy distribution ratio of 1, where the capacity calculated by the maximized energy carrying capacity model is equal to the capacity of information transmission, i.e., the capacity is calculated by the maximized energy carrying capacity model
When the node residual capacity is less than EminWhen the node is in use, the node needs to be supplemented with energy. Therefore, the model can be simplified to
Three sets of variables r, rho, P exist in the routing model. Due to PcjIs an indeterminate value and therefore the routing algorithm for problem (11) cannot directly utilize the virtual link method. Thus, Pc is determined considering the reverse narrative starting from the destination nodejAnd carrying out route calculation, designing an interference-aware energy-carrying routing algorithm, calculating the maximum energy-carrying transmission capacity of the link by using the algorithm 1 in the route searching process, and selecting a transmission mode enabling the link capacity to be maximum and a path with the maximum transmission capacity according to the interference-aware routing index.
The algorithm inputs being the network topology G and the kth flowSource node and destination node(s)k,dk) And the flow information of the first k-1 flows comprises source node, destination node and path information of the flows. And outputting the path selected for the k-th flow and the distribution rate and the transmission power of the nodes on the path. The main architecture of the algorithm is derived from Dijkstra's algorithm,
store node i to destination node dkIs a route index (i.e. a route index of
) And next hop nodes, wherein S is a node set of a determined path, and Q is a node queue of an undetermined path with the routing index as a key value.
Lines 1-4 initialize the route index of all nodes to be positive infinity and the next hop node to be null. Rows 5-7 initialize the route index of the destination node to 0, S to empty and queue Q to all nodes. The node j with the smallest route index is selected from the queue Q, and the following operations are performed on the edges (i, j) formed by all the adjacent nodes i. Lines 12-13 calculate the interference that k-1 streams already exist have on the link (i, j) using Algorithm 2, and then calculate the maximum capacity that can be achieved with energy-carrying transmission using Algorithm 1
And corresponding allocation rate and transmission power
Lines 14-16 use algorithm 4 to calculate the number of links sharing the node with link (i, j), and the links sharing the channel with the shared node regardless of whether the energy transmission link or the information transmission link (i, j) is carried, so the actually usable capacity needs to be divided by the number of links sharing the node plus 1 to obtain the route index of the link at that time
Rows 17-24 compare the route metrics of the links
And the route index of node j
Obtaining temporary routing index of node i
If it is not
Route index of current node i
If the residual capacity of the node i is lower than the lowest capacity requirement, the energy acquisition requirement is the transmission power, otherwise, the energy acquisition requirement is 0. Until Q is empty, all nodes find the destination node dkThe path of (2).
The interference-aware energy-carrying route utilizes algorithm 3 to calculate the interference existing in the link according to the paths of the existing k-1 flows and the transmission power of the nodes on the paths. For the link (i, j), if the node l is a two-hop neighbor of the node j, the node l is considered to be in the interference range of the node j, if a flow passes through the node l and the next hop node on the flow is not i or j, the node l can generate interference on the link (i, j), and if a plurality of flows pass through the node l, the maximum transmission power of the nodes in all the flows is taken as the interference power. All l generated interference present is then accumulated, i.e. the product of the accumulated interference power and the channel gain l to j.
The interference to the link (i, j) in the algorithm 3 only includes interference generated by neighbor nodes which do not pass through the nodes i and j, and when all the links which pass through the current k-1 flows share the node with the link (i, j), the flows which pass through the i and the j cannot be embodied in the algorithm 3. For this case, the link (i, j) may share a channel with the link of the sharing node by time division, and thus the capacity actually usable is the capacity calculated by the interference model divided by the number of links of the sharing node plus 1, where the plus 1 is the link (i, j) itself.
According to the node situation that k-1 flows pass through, the number of links sharing the node can be divided into three types, as shown in fig. 5. In the first case, the flow passes through the sending node. As shown in fig. 5(a), for link (7,2), flow 1 passes through node 7, and there are two links (3,7) and (7,5) and (7,2) sharing the node. For link (3,4), flow 1 passes through node 3, but 3 is the source node of the flow, and there is only one link (3,7) that shares the node with (3, 4). 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 both the sending and receiving nodes. As shown in fig. 5(c), the shared node links are now the union of the first two cases, both of which have computed link (i, j), so the number of shared node links is equal to the number of the first case plus the second case minus 1.
The number of links of the shared node needs to be calculated for the k-th flow which is currently calculated, and the similarity can be divided into three cases. In the first case, the sending node is the source node or the receiving node is the destination node, then the link only has the subsequent or previous link, and the number of the shared node links is 1. In the second case, the sending node is the source node and the receiving node is the destination node, then there is no subsequent or previous link for the link, and 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 the links have subsequent and previous links, and the number of shared node links is 2.
Thus, algorithm 4 accumulates the number of shared node links for the existing k-1 flows, plus the number of shared node links for the current k-th flow.
As shown in FIG. 5(a), flow F1Has a path of
As shown in FIG. 5(b), a new flow F2(2 → 6). The interfering nodes of node 4 include 2, 3, 6, 7 and 8, with an obstacle 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 flow F1In, will be to F2Interference is generated. Node 8 is closer to these nodes and interferes more than node 4. Thus, F2Selecting nodes 4 to form paths
According to the calculation of the capacity under the interference condition, the capacity of the link is respectively
Flow F2 has an end-to-end capacity of
As shown in fig. 5(c), nodes 4 and 8 require energy replenishment if a new flow arrives. The node 2 cannot provide enough energy to the node 4, the energy-carrying link cannot be established, and the original path cannot be selected. Taking into account other paths, e.g.
Since more interference at node 8 becomes a source of energy replenishment, an energy carrying link between nodes 2 and 8 can be established. The capacities of the links are respectively
Flow F2 has an end-to-end capacity of
Taking the topology of fig. 5 as an example, we build a network with medium network density, scale and medium residual energy, and analyze and test the performance of the proposed scheme. The network comprises 9 nodes, and the surplus energy of the nodes 1, 3,4 and 8 is insufficient for forwarding, so that the additional energy is needed. Randomly selecting 2 to 4 non-repetitive streams of source nodes and destination nodes, and randomly selecting 50 groups of source node and destination node pairs under each stream number. The evaluated index is the capacity of the last flow selected, namely the interference route index of the path.
The comparison scheme includes four types, i.e., information transmission without interference (WITwoi, WIT without interference), energy transmission without interference (SWIPTwoi, SWIPT with interference), information transmission with interference (WITwi, WIT with interference), and energy transmission with interference (SWIPTwi, SWIPT with interference), according to whether interference and the transmission method are considered. The first three schemes can be implemented by using the algorithm framework of the fourth scheme, except that the calculation method in the route index is different, wherein, WITwi uses formula (2), WITwo and SWIPTWoi do not consider interference, and the interference parts of formulas (2) and (5) are removed, namely formulas (11) and (12) respectively.
Firstly, the improvement conditions of evaluation indexes of 50 groups of different flow distributions under the condition of the same flow number are analyzed. Under either flow number, three categories can be distinguished. In the first category, the flow capacities of the four algorithms are all equal. In the second category, interference-considered transmissions are higher than interference-not considered transmissions, but interference-considered information transmissions are equal to interference-considered energy-carrying transmissions. In the third category, interference-considered energy-carrying transmissions are higher than interference-considered information transmissions.
The previous document states that not all flows can take advantage of energy-carrying transport to improve performance, depending on the source and destination node distribution of the flows, and the path selected using the proposed scheme may be the same as the other three, as is the case with the first and second classes. The paths selected by the first four schemes are the same. The second kind of SWIPtwi is the same as the path selected by the WITwi, but is different from the former two kinds of paths, the routing result considering the interference is different from the routing result not considering the interference, but the routing result adopting the energy-carrying transmission and the information transmission is the same. In the third category, the interference-carrying transmission routing result is considered and is different from the information transmission considering the interference, so that the performance of the energy-carrying transmission is improved. Therefore, these three classes are named No Gain, Gain from interference, Gain from SWIPT, respectively. The proportions of the different classes of flows in all flows are shown in fig. 6. As can be seen from fig. 6, the sum of the third and second classes is greater than 65% for all three streams, with the first class percentage decreasing significantly as the number of streams increases and the third class increasing from 30% to 70%. This means that as the number of streams increases, there is more potential to obtain performance gains from considering interference and SWIPT.
In the second category of flows with performance improvement due to interference considerations, the path capacity averages of the four schemes are analyzed, as shown in fig. 7. For three streams, the average interference path capacity considered is about 1.4 times the transmission of the interference-free information.
Finally, in the third category of flows with performance improvement due to energy-carrying transmission, the path capacity average of the four schemes is analyzed, as shown in fig. 8. Considering that the interference carrying energy transmission is 90% -382% higher than that of the interference information transmission, and considering that the interference carrying energy transmission is 30% -110% higher than that of the interference information transmission.
Claims (7)
1. An interference-aware wireless energy-carrying transmission routing method is characterized by comprising the following steps:
1) establishing an energy-carrying transmission model under interference by using a physical interference model;
2) based on an energy-carrying transmission model under interference, and meeting the requirement of minimum energy acquisition, constructing an interference-aware maximum energy-carrying capacity distribution model;
3) designing a solving algorithm of a maximum energy carrying capacity distribution model of interference perception;
4) designing an interference perception routing index, and establishing an interference perception energy-carrying transmission routing problem model in combination with an interference perception maximum energy-carrying capacity distribution model;
5) solving an interference-aware energy-carrying transmission routing problem model, designing an interference-aware wireless energy-carrying transmission routing algorithm, calculating the maximum energy-carrying transmission capacity of a link by using a maximum capacity allocation algorithm in the routing searching process, and selecting a transmission mode enabling the maximum link capacity and a path with the maximum transmission capacity according to an interference-aware routing index;
in step 1), the energy-carrying transmission model under the interference is as follows:
where i denotes a transmitting node, j denotes a receiving node,
representing the signal-to-noise ratio between links (i, j),
representing the available energy, pijRepresenting information on power and energy distribution ratio, PijRepresents the transmit power between links (i, j), hijDenotes the channel gain between links (i, j), phijSet of interfering nodes, P, representing node jlRepresents the transmit power of the node/in the interference set,
and
respectively representing antenna noise nijSum signal conversion noise zijRepresents the power conversion rate of the power.
2. The interference-aware wireless energy carrying transmission routing method according to claim 1, wherein in step 2), the maximum energy carrying capacity allocation model is: according to a link channel capacity calculation formula, under the condition of meeting energy acquisition constraint, the capacity of energy-carrying transmission adopted by a link is maximized by adjusting the transmission power, the information and the energy distribution rate:
Pij∈[0,Pmax]
ρij∈[0,1]；
wherein PcjThe minimum energy capture requirement is indicated and,
indicating the link capacity when energy-carrying transmission is used, W indicating the channel bandwidth, PmaxIndicating the maximum transmit power.
3. The interference-aware wireless energy-carrying transmission routing method according to claim 2, wherein the solution algorithm of the interference-aware maximum energy-carrying capacity allocation model is as follows:
1) calculating a maximum energy-carrying capacity allocation model of the maximum energy-carrying capacity allocation model, which is as follows:
2) random initialization
a1,
μ＞0,0≤φ＜＜1,υ∈(0,1),η＞1,k←1；
3) According to
Solving a problem
Solving the problem by
Calculating the partial derivatives so that the partial derivatives are 0, i.e.
Then obtain
4) Checking for termination conditions if Lk-Lk-1If | is less than or equal to phi, stopping iteration and outputting
As an approximate minimum point of the maximum energy-carrying capacity allocation model; otherwise, go to step 4);
5) update μ if Lk||≥υ||Lk-1If, then μ: η μ;
6) updating the multiplier:
7) k ═ k +1, go to step 2).
4. The interference-aware wireless energy-carrying transmission routing method according to claim 1, wherein the interference-aware energy-carrying transmission routing problem model is:
wherein r isijIndicating whether the selected path contains link (i, j), 1 indicating contained, 0 indicating not contained; required supplementary energy value PcjNode j's next hop node and node j's transmit power P to next hop nodejkDetermines, therefore, the transmission power P required for the node to continue forwardingjk。
5. The interference-aware wireless energy-carrying transmission routing method according to claim 1, wherein the interference-aware wireless energy-carrying transmission routing algorithm comprises the steps of:
1) initializing the routing indexes of all nodes to be infinite and the next hop node to be null;
2) initializing a routing index of a destination node to be 0, S to be null and a queue Q to be all nodes;
3) taking out the node j with the minimum routing index from the queue Q until Q is empty;
4) the following operations from step 5) to step 7) are executed for all links (i, j) formed by the adjacent nodes i;
5) calculating the interference of the link (i, j) by using an interference algorithm, and then calculating the maximum capacity obtainable by energy-carrying transmission by using an interference-aware maximum capacity allocation model solving algorithm
Corresponding allocation rate and transmission power
6) Calculating the number of the links sharing the nodes with the links (i, j) by using a link number algorithm of the sharing nodes, and obtaining the routing index of the link at the moment by dividing the actually usable capacity by the maximum capacity by adding 1 to the number of the links of the sharing nodes
7) Comparing route metrics of links
And the route index of node j
Obtaining temporary routing index of node i
If it is not
Route index of current node i
If the residual capacity of the node i is lower than the lowest capacity requirement, the energy acquisition requirement is the transmission power, otherwise, the energy acquisition requirement is the transmission powerIs 0.
6. The interference-aware wireless energy carrying transmission routing method according to claim 4, wherein the interference algorithm comprises: calculating the interference existing in a link according to paths of existing k-1 flows and the transmission power of nodes on the paths, regarding the link (i, j), if a node l is a two-hop neighbor of the node j, considering that the node l is in the interference range of the node j, if the node l has a flow passing through and the node of the next hop on the flow is not i or j, the node l will generate interference on the link (i, j), if the node l has a plurality of flows passing through, the maximum transmission power of the nodes in all the flows is taken as the interference power, and then the existing interference generated by all the flows is accumulated, namely the product of the accumulated interference power and the channel gain from l to j.
7. The interference-aware wireless energy-carrying transmission routing method according to claim 4, wherein the algorithm for the number of links of the sharing node is as follows: the number of links with the shared nodes of the existing k-1 flows is divided into three types according to the conditions of the nodes passed by the flows: 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 the shared node links is 2, otherwise, the number 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 the shared node links is 2, otherwise, the number is 1; in the third situation, the flow passes through the sending node and the receiving node at the same time, and the number of the shared node links is the sum of the first two situations minus 1; number of links sharing a node with the flow itself: in the first case, if the sending node is the source node or the receiving node is the destination node, the number of the 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, the number of the 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 the number of shared node links is 2.
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