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Joint resource optimization for DF relaying SWIPT based cognitive sensor networks

机译:DF中继基于SWIPT的认知传感器网络的联合资源优化

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摘要

Spectrum and energy are two important resources for wireless sensor networks (WSNs). Cognitive Radio (CR) can improve the efficiency of spectrum utilization by allowing secondary users (SUs) access to the licensed bands as long as they do not significantly affect the performance of primary users (PUs). Simultaneous wireless information and power transfer (SWIPT) can harvest energy and decode information simultaneously from radio-frequency (RF) signal, which can prolong the life time of energy-constraint networks (e.g., WSNs). In this paper, we propose a joint resource optimization scheme in respect of transmission power and power splitting ratio for decode-and-forward (DF) relaying SWIPT based cognitive sensor networks (CSNs), where relay sensor node (RSN) harvests energy from the signal of source sensor node (SSN) by using power splitting (PS) receiver architecture and utilize the harvested energy to help forward SSNs information. We maximize the throughput of SUs while guaranteeing the interference to PUs caused by SUs is smaller than the interference threshold. Simulation results demonstrate the performance of the joint resource optimization scheme.
机译:频谱和能量是无线传感器网络(WSN)的两个重要资源。认知无线电(CR)可以通过允许次要用户(SU)访问许可频段来提高频谱利用效率,只要它们不会显着影响主要用户(PU)的性能即可。同时进行无线信息和功率传输(SWIPT)可以从射频(RF)信号中收集能量并同时解码信息,这可以延长能量受限网络(例如WSN)的寿命。在本文中,我们针对基于解码和转发(DF)中继SWIPT的认知传感器网络(CSN)提出了一种针对传输功率和功率分配比的联合资源优化方案,其中中继传感器节点(RSN)收集来自通过使用功率分配(PS)接收器体系结构来对源传感器节点(SSN)的信号进行采样,并利用所收集的能量来帮助转发SSN信息。我们在保证SU引起的对PU的干扰小于干扰阈值的同时,最大化SU的吞吐量。仿真结果证明了联合资源优化方案的性能。

著录项

  • 来源
    《Physical Communication》 |2018年第4期|93-98|共6页
  • 作者单位

    College of Information Engineering, Zhejiang University of Technology;

    College of Information Engineering, Zhejiang University of Technology;

    College of Information Engineering, Zhejiang University of Technology;

    Faculty of Electrical Engineering and Computer Science, Ningbo University;

    School of Electronic Information and Electrical Engineering, Dalian University of Technology;

    College of Information Engineering, Zhejiang University of Technology;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Energy harvesting; Cognitive sensor network; Decode-and-forward; Throughput;

    机译:能量收集;认知传感器网络;解码转发;吞吐量;

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