Optimal Spectrum Sensing-Access Policy in Energy Harvesting Cognitive Radio Sensor Networks

被引:4
|
作者
Zhang, Fan [1 ,2 ]
Jing, Tao [1 ]
Huo, Yan [1 ]
Ma, Liran [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
[2] Sci & Technol Commun Networks Lab, Beijing, Peoples R China
[3] Texas Christian Univ, Dept Comp Sci, Ft Worth, TX 76129 USA
来源
2017 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS | 2018年 / 129卷
基金
中国国家自然科学基金;
关键词
Energy harvesting; cognitive radio sensor networks; cooperative sensing; partially observable Markov decision process;
D O I
10.1016/j.procs.2018.03.034
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we introduce energy harvesting into a cognitive radio sensor network to power the network with renewable energy sources so as to achieve self-sustainability of energy-limited sensors. In our work, the cognitive radio technology enable sensors access to the underutilized spectrum for the purpose of coping with the spectrum-scarcity problem in the unlicensed band. Using centralized cooperative spectrum sensing, a set of cognitive sensors is chosen from candidate sensors with different received primary users' signal powers and energy-arrival rates. After detecting the state of a primary channel, we also need to determine which cognitive sensor can get to access the primary channel as well as the power level to be used upon the transmission. The above sensing-access design problem is formulated as an infinite-horizon partially observable Markov decision process, in which the primary goal is to maximize the long-term expected throughput. Through using a value iteration approach, we propose an optimal sensing-access policy. At last, numerical results are presented to verify the superiority of our proposed policy to the existing policy. Copyright (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:194 / 200
页数:7
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