Multiantenna Clustering Collaboration for WPCNs Based on Nonlinear EH

IF 2.3 4区 计算机科学 Q1 Engineering
Lina Yuan, Huajun Chen, Anran Zhou, Rong Wang, Xianli Wen
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引用次数: 0

Abstract

This article considers a wireless-powered communication network (WPCN) composed of a multiantenna hybrid access point (HAP) based on nonlinear energy harvesting (EH). To improve some distant WDs’ throughput performance, one of them is allowed to be selected as a cluster head (CH) to help transfer information from other cluster members (CMs). Nevertheless, the proposed clustering collaboration’s performance is essentially restricted by the CH’s energy-intensive consumption (EC), which requires to transfer every WDs’ information, covering its own. In order to figure out the question, the HAP’s energy beamforming (EB) capability with multiple antennas is utilized that can concentrate greater transmission power into the CH to equilibrate its EC to assist other WDs. To be specific, each WD’s throughput performance is firstly derived under the proposed approach. A high-efficiency optimization algorithm for addressing cooperative optimization problem is put forward. In addition, the simulations are carried out in the actual network environment, and the results demonstrate that our proposed clustering collaboration with multiple antennas can validly enhance the WPCN’s throughput fairness based on nonlinear EH.
基于非线性EH的wpcn多天线聚类协同
本文研究了一种基于非线性能量收集(EH)的多天线混合接入点(HAP)组成的无线供电通信网络(WPCN)。为了改善一些远程wd的吞吐量性能,允许选择其中一个wd作为集群头(CH),以帮助从其他集群成员(CMs)传输信息。然而,所提出的聚类协作的性能本质上受到CH的能源密集消耗(EC)的限制,这需要传输每个wd的信息,覆盖其自身。为了解决这个问题,利用HAP的多天线能量波束形成(EB)能力,可以将更大的发射功率集中到CH中,以平衡其EC以协助其他WDs。具体而言,首先根据所提出的方法推导出每个WD的吞吐量性能。提出了一种求解协同优化问题的高效优化算法。此外,在实际网络环境中进行了仿真,结果表明,基于非线性EH的多天线聚类协作可以有效地提高WPCN的吞吐量公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Distributed Sensor Networks
International Journal of Distributed Sensor Networks Computer Science-Computer Networks and Communications
CiteScore
6.00
自引率
4.30%
发文量
94
审稿时长
11 weeks
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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