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[电气工程与系统科学] 带内全双工能量分布式功率控制方案 收获无线网络 [推广有奖]

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nandehutu2022 在职认证  发表于 2022-3-11 17:41:30 来自手机 |只看作者 |坛友微信交流群|倒序 |AI写论文

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摘要翻译:
本文研究了一个混合基站(HBS)和所有用户设备(UE)工作在带内全双工模式下的能量收集无线网络中的两个功率控制问题。我们考虑在服务质量需求约束下最小化总功率和最大化总吞吐量。针对这两个问题,我们提出了两种分布式功率控制方案,分别由UE控制上行链路发射功率和由HBS控制下行链路能量收集信号功率。在我们提出的方案中,HBS更新能量收集信号的下行链路发射功率电平,使得每个UE能够收集其所需的能量,用于为操作电路供电并以由所提出的方案确定的功率电平发射其上行链路信息信号。我们证明了我们提出的功率控制方案从任意初始发射功率开始收敛到它们相应的唯一不动点。我们将证明我们所提出的方案很好地解决了所述问题,这也是我们广泛的仿真结果所证明的。
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英文标题:
《Distributed Power Control Schemes for In-Band Full-Duplex Energy
  Harvesting Wireless Networks》
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作者:
Rojin Aslani, Mehdi Rasti
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最新提交年份:
2018
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分类信息:

一级分类:Electrical Engineering and Systems Science        电气工程与系统科学
二级分类:Signal Processing        信号处理
分类描述:Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用,包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、(生物)医学、图像、视频和多模态自然和人为信号,包括通信信号和数据。感兴趣的主题包括:统计信号处理、谱估计和系统辨识;滤波器设计;自适应滤波/随机学习;(压缩)采样、传感和变换域方法,包括快速算法;用于机器学习的信号处理和用于信号处理应用的机器学习;网络与图形信号处理;信号处理中的凸和非凸优化方法;雷达、声纳和传感器阵列波束形成和测向;通信信号处理;低功耗、多核、片上系统信号处理;信息物理系统的传感、通信、分析和优化,如电网和物联网。
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一级分类:Computer Science        计算机科学
二级分类:Networking and Internet Architecture        网络和因特网体系结构
分类描述:Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
涵盖计算机通信网络的所有方面,包括网络体系结构和设计、网络协议和网络间标准(如TCP/IP)。还包括与Internet体系结构和性能直接相关的主题,如web缓存。大致包括除C.2.4以外的所有ACM主题类C.2,后者更有可能将分布式、并行和集群计算作为主要主题领域。
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英文摘要:
  This paper studies two power control problems in energy harvesting wireless networks where one hybrid base station (HBS) and all user equipments (UEs) are operating in in-band full-duplex mode. We consider minimizing the aggregate power subject to the quality of service requirement constraint, and maximizing the aggregate throughput. We address these two problems by proposing two distributed power control schemes for controlling the uplink transmit power by the UEs and the downlink energy harvesting signal power by the HBS. In our proposed schemes, the HBS updates the downlink transmit power level of the energy-harvesting signal so that each UE is enabled to harvest its required energy for powering the operating circuit and transmitting its uplink information signal with the power level determined by the proposed schemes. We show that our proposed power control schemes converge to their corresponding unique fixed points starting from any arbitrary initial transmit power. We will show that our proposed schemes well address the stated problems, which is also demonstrated by our extensive simulation results.
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PDF链接:
https://arxiv.org/pdf/1807.07622
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关键词:无线网络 无线网 全双工 分布式 Architecture 链路 方案 problems 能量 发射功率

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