CONSTANT FALSE ALARM ENERGY DETECTION BASED ON MARKOV TRANSFER CHARACTERISTICS IN COGNITIVE RADIO

被引：0
|
作者：
Qin, Xiongfei [1 ]
Peng, Shengliang [1 ]
Gao, Renyang [1 ]
Zheng, Weibin [1 ]
机构：
[1] Huaqiao Univ, Sch Informat Sci & Engn, Quanzhou, Peoples R China
来源：
2017 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ISPACS 2017) | 2017年
基金：
中国国家自然科学基金;
关键词：
Cognitive Radio; Markov Transfer Characteristics; Constant False Alarm Probability; Energy Detection; SPECTRUM ACCESS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Cognitive Radio is an emerging technology to improve the utilization of licensed spectrum. Spectrum sensing is one of the key tasks for cognitive radio. Previous research on spectrum sensing has not fully investigated the characteristics of the primary user. This paper analyzes the Markov transfer characteristics of the primary user, based on which the current state of the primary user is predicted to adjust the decision threshold and improve detection accuracy. Firstly, we illustrate the Markov transfer characteristics of the primary user. Secondly, we illustrate benefits of the characteristics and derive the upper bound of the detection probability we can achieve. Finally, we introduce a new algorithm to exploit the Markov transfer characteristics. Simulation results are given to verify the performance of the proposed algorithm in this paper.
引用
收藏
页码：125 / 129
页数：5
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