认知网络中的能量回收技术:性能分析及优化设计

发布时间：2018-01-21 07:18

本文关键词： 认知无线电网络能量回收频谱检测马尔可夫过程　出处：《电讯技术》2017年08期 　论文类型：期刊论文

【摘要】：通信网络中有限的能源和频带资源限制了网络容量的进一步提升。对能量回收技术在认知网络中的应用进行研究,量化评估用户可回收的能量以及可达吞吐率,并进行优化设计很有必要。在所分析的系统中,当授权用户进行通信时,非授权用户可回收无线信号中所带有的能量,并利用回收的能量进行频谱检测;当检测到授权用户空闲时,非授权用户将接入频谱,利用回收到的能量进行数据传输。采用马尔科夫链模型对通信场景进行描述分析,发现授权用户的活跃程度对非授权用户可回收的能量、获得的传输机会带来影响,进而决定了非授权用户的可达吞吐量。在此基础上,提出一种通过控制授权用户业务量,以最大化网络能量效用和频谱效用的优化方案,并通过仿真证实了理论分析的正确性。
[Abstract]:Limited energy and frequency band resources in communication networks limit the further improvement of network capacity. The application of energy recovery technology in cognitive networks is studied to quantitatively evaluate the user recoverable energy and reachable throughput. It is necessary to optimize the design. In the system analyzed, when the authorized user communicates, the unauthorized user can recover the energy from the wireless signal, and use the recovered energy to detect the spectrum. When the authorized user is idle, the unauthorized user will access the spectrum and transmit the data using the recovered energy. The Markov chain model is used to describe and analyze the communication scene. It is found that the active degree of authorized users has an impact on the recoverable energy and transmission opportunities of unauthorized users, and then determines the reachable throughput of unauthorized users. An optimization scheme is proposed to maximize the energy utility and spectrum utility of the network by controlling the traffic volume of authorized users, and the correctness of the theoretical analysis is verified by simulation.
【作者单位】：华为技术有限公司;上海交通大学电子工程系;
【基金】：国家高技术研究发展计划(863计划)项目(2014AA01A704)
【分类号】：TN925
【正文快照】： ***1引言随着通信业务量的爆炸式增长,人们对无线通信技术提出了越来越高的要求:一方面,由于通信终端数量的快速增加,需要有更多的频谱或者更高的频谱利用率来支持各类业务的大容量传输;另一方面,由于通信终端通常不一定带有稳定供能设备,如何提升设备能效也成为亟待解决的问

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