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Throughput Maximization of Wireless-Powered Communication Networks: An Energy Threshold Approach

机译:无线通信网络的吞吐量最大化:能量阈值方法

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In this paper, we consider a wireless-powered communication network (WPCN) where one mobile hybrid access point (HAP) coordinates the wireless energy transfer to sensor nodes and receives data from sensor nodes, which are powered exclusively by the harvested wireless energy. As the harvest-then-transmit protocol is employed by sensor nodes, a major challenge lies on the tradeoff between achievable throughput and energy harvesting opportunity of sensor nodes. Confronting this challenge, we develop an energy threshold approach by jointly considering geographic locations and energy states of sensor nodes, where wireless energy transfer occurs when none of the sensor nodes in the range of data transmission has more energy than the threshold, otherwise data transmission from one randomly chosen qualified sensor node to the HAP occurs. By comparing the range of energy harvesting and that of data transmission, we divide the network topology into two cases for throughput analysis, and formulate the energy states of sensor nodes as Markov chain processes with different energy state spaces in the two cases. Through monotonicity analysis of achievable throughput and probability distribution of energy states, we prove the existence of the optimal energy threshold that maximizes the achievable throughput, and find that the achievable throughput under infinite battery size could be viewed as the upper bound of that under the limited battery size. Finally, simulation results validate theoretical results of the optimal energy threshold, and show the impacts of system parameters on the achievable throughput.
机译:在本文中,我们考虑一种无线供电的通信网络(WPCN),其中一个移动混合接入点(HAP)将无线能量传输与传感器节点坐标坐标并从传感器节点接收数据,其专门由收获的无线能量供电。随着传感器节点采用收获 - 发射协议,主要挑战在于可实现的吞吐量和传感器节点的能量收集机会之间的权衡。面对这一挑战,我们通过联合考虑传感器节点的地理位置和能量状态来开发能量阈值方法,其中无线能量传输在数据传输范围内的任何传感器节点都具有比阈值更多的能量时,否则数据传输发生一个随机选择的合格传感器节点到HAP。通过比较能量收集的范围和数据传输的范围,我们将网络拓扑分为两种情况下的吞吐量分析,并在两种情况下配制传感器节点的能量状态作为马尔可夫链过程。通过单调性分析可实现的吞吐量和能量状态的概率分布,我们证明了最大化能量阈值的存在,以最大化可实现的吞吐量,并发现可实现的无限电池尺寸下的可实现的吞吐量被视为下限的限制下方电池尺寸。最后,仿真结果验证了最佳能量阈值的理论结果,并显示了系统参数对可实现的吞吐量的影响。

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