Successive Interference Cancellation Based Throughput Optimization for Multi-Hop Wireless Rechargeable Sensor Networks

Abstract

Wireless Sensor Networks are constrained by low channel utilization and limited battery capacity, so they are widely regarded as the mainly performance bottlenecks. In this paper, in order to improve channel utilization and prolong network lifetime, we investigate the cooperation of multi-hop Wireless Rechargeable Sensor Networks (WRSNs) with Successive Interference Cancellation (SIC) technology. In WRSNs, since the flow rate of each node is unknown, the power of the nodes is not constant. However, SIC will not work if the signal power levels at receive node cannot be sorted. To solve this issue, we first construct a minimum energy routing and unify the transmit rate to determine the transmit power. We can also obtain the time scheduling scheme after determining the routing and power. Next, we formulate an optimization problem, with the objective of maximizing the mobile charger’s vacation time over the rechargeable cycle. Finally, we provide a near-optimal solution and prove its feasible performance. Simulation results present that SIC can achieve the better upper boundary on throughput (compared to inference avoidance increasing about 180–450%) and no extra transmit and receive energy consumption in the multi-hop WRSNs.

The Management of Educational Talents in Vocational Colleges Based on Wireless Network in the Artificial Intelligence Era

“…Zhang et al proposed a joint power tying and subchannel allocation algorithm, which can improve the capacity of the Femtocell network and protect the communication service quality of macrocell users [18]. Wang et al have done relevant research on soft frequency reuse technology in home base station network [19].…”

“…Each vertex in the minimum rigid graph has at least two adjacent edges [17], so the minimum rigid graph has less communication complexity and stronger robustness. Especially, the singular value of the stiffness matrix provides a method to measure the algebraic properties of the network [18]. Define the stiffness matrix of edges in the network as follows:…”

“…Figure 6 counts the traces of the stiffness matrix of the topological graph generated from the algorithm of reference [18] based on the topology of the least rigid graph and the least rigid graph constructed by the algorithm in this paper.…”

“…It demonstrates that the algorithm has good algebraic connectivity and stiffness properties. E distance from relay node Our ref [18] ref [20] ref [21] Figure 9: e relationship between the distance from E relay and users' safety satisfaction.…”

Cooperative Recharge Scheme Based on a Hamiltonian Path in Mobile Wireless Rechargeable Sensor Networks

“…However, the rate of energy consumption varies dynamically due to the uncertainty of environmental conditions; therefore, a periodical charging scheme was infeasible for complex and changeable networks. In [16], a optimization problem with the target of maximizing the ratio of MC's vacation time over one entire cycle time is proposed to improve channel utilization and prolong network lifetime. However, this method did not involve the dynamic topology of WRSN.…”