State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel). 2019 Feb 14;19(4):785. doi: 10.3390/s19040785.
In this work, we investigate the capacity allocation problem in the energy harvesting wireless sensor networks (WSNs) with interference channels. For the fixed topologies of data and energy, we formulate the optimization problem when the data flow remains constant on all data links and each sensor node harvests energy only once in a time slot. We focus on the optimal data rates, power allocations and energy transfers between sensor nodes in a time slot. Our goal is to minimize the total delay in the network under two scenarios, i.e., no energy transfer and energy transfer. Furthermore, since the optimization problem is non-convex and difficult to solve directly, by considering the network with the relatively high signal-to-interference-plus-noise ratio (SINR), the non-convex optimization problem can be transformed into a convex optimization problem by convex approximation. We attain the properties of the optimal solution by Lagrange duality and solve the convex optimization problem by the CVX solver. The experimental results demonstrate that the total delay of the energy harvesting WSNs with interference channels is more than that in the orthogonal channel; the total network delay increases with the increasing data flow for the fixed energy arrival rate; and the energy transfer can help to decrease the total delay.
在这项工作中，我们研究了具有干扰信道的能量收集无线传感器网络（WSN）中的容量分配问题。对于数据和能量的固定拓扑结构，我们在所有数据链路上的数据流量保持不变且每个传感器节点在一个时隙中仅一次收集能量的情况下制定了优化问题。我们专注于时隙中传感器节点之间的最优数据速率、功率分配和能量传输。我们的目标是在两种情况下（即无能量传输和能量传输）下最小化网络中的总延迟。此外，由于优化问题是非凸的且难以直接求解，因此通过考虑具有较高信噪比（SINR）的网络，可以通过凸逼近将非凸优化问题转换为凸优化问题。我们通过拉格朗日对偶获得最优解的性质，并通过 CVX 求解器求解凸优化问题。实验结果表明，具有干扰信道的能量收集 WSN 的总延迟大于正交信道的总延迟；对于固定能量到达率，总网络延迟随数据流量的增加而增加；并且能量传输可以帮助降低总延迟。
