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基于定量能量收集机制的安全 SWIPT 网络资源分配。

Resource Allocation for a Secure SWIPT Network Based on a Quantitative Energy Harvesting Mechanism.

机构信息

School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China.

Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

出版信息

Sensors (Basel). 2023 May 27;23(11):5117. doi: 10.3390/s23115117.

DOI:10.3390/s23115117
PMID:37299845
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10255812/
Abstract

Simultaneous wireless information and power transfer (SWIPT) technology can effectively extend the lifecycle of energy-constrained networks. In order to improve the energy harvesting (EH) efficiency and network performance in secure SWIPT networks, this paper studies the resource allocation problem based on the quantitative EH mechanism in the secure SWIPT network. Based on a quantitative EH mechanism and nonlinear EH model, a quantified power-splitting (QPS) receiver architecture is designed. This architecture is applied in the multiuser multi-input single-output secure SWIPT network. With the goal of maximizing the network throughput, the optimization problem model is established under the conditions of meeting the legal user's signal-to-interference-plus-noise ratio (SINR), EH requirements, the total transmit power of the base station, and the security SINR threshold constraints. Due to the coupling of variables, the problem is a nonconvex optimization problem. To deal with the nonconvex optimization problem, a hierarchical optimization method is adopted. Firstly, an optimization algorithm based on the optimal received power of EH circuit is proposed, and a power mapping table is constructed through the optimization algorithm, from which the optimal power ratio to meet the user's EH requirements is obtained; then, the nonconvex problem is transformed into a convex problem by using variable substitution, semidefinite relaxation, dichotomous optimization, etc. The simulation results show that compared with the power splitting receiver architecture, the input power threshold range of the QPS receiver architecture is larger, which can avoid the EH circuit falling into the saturated working area and maintain high network throughput.

摘要

同时无线信息与能量传输(SWIPT)技术可以有效地延长能量受限网络的生命周期。为了提高安全 SWIPT 网络中的能量收集(EH)效率和网络性能,本文研究了基于安全 SWIPT 网络中定量 EH 机制的资源分配问题。基于定量 EH 机制和非线性 EH 模型,设计了一种量化功率分割(QPS)接收器架构。该架构应用于多用户多输入单输出安全 SWIPT 网络中。以最大化网络吞吐量为目标,在满足合法用户信干噪比(SINR)、EH 要求、基站总发射功率和安全 SINR 阈值约束条件下,建立了优化问题模型。由于变量的耦合,该问题是一个非凸优化问题。为了解决这个非凸优化问题,采用了分层优化方法。首先,提出了一种基于 EH 电路最优接收功率的优化算法,并通过优化算法构建功率映射表,从中获得满足用户 EH 要求的最优功率比;然后,通过变量替换、半定松弛、二分优化等方法将非凸问题转化为凸问题。仿真结果表明,与功率分割接收架构相比,QPS 接收架构的输入功率阈值范围更大,可避免 EH 电路进入饱和工作区,并保持较高的网络吞吐量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/8c2057c43509/sensors-23-05117-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/fcf1d7fbd2fa/sensors-23-05117-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/153e9d338cd8/sensors-23-05117-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/0469b8b2c3d3/sensors-23-05117-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/70efbad76ec9/sensors-23-05117-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/3d9eb7f16d9d/sensors-23-05117-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/627ba052bfae/sensors-23-05117-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/8c2057c43509/sensors-23-05117-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/fcf1d7fbd2fa/sensors-23-05117-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/153e9d338cd8/sensors-23-05117-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/9f65ca9393ec/sensors-23-05117-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/09c78f0ba06e/sensors-23-05117-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/0469b8b2c3d3/sensors-23-05117-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/70efbad76ec9/sensors-23-05117-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/3d9eb7f16d9d/sensors-23-05117-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/627ba052bfae/sensors-23-05117-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3e/10255812/8c2057c43509/sensors-23-05117-g009.jpg

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