Spectrum Sensing in Cognitive Radio Based on Hidden Semi-Markov Model

2019 ◽  
pp. 275-286
Author(s):  
Lujie Di ◽  
Xueke Ding ◽  
Mingbing Li ◽  
Qun Wan
Keyword(s):  
Cognitive Radio ◽  
Markov Model ◽  
Spectrum Sensing

scholarly journals Markov Model-Based Energy Efficiency Spectrum Sensing in Cognitive Radio Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Jiao ◽  
Inwhee Joe
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Markov Model ◽  
Sensor Network ◽  
Spectrum Sensing ◽  
Wireless Sensor ◽  
Time Interval ◽  
Sensing Time

Cognitive Radio Sensor Network (CRSN), incorporating cognitive radio capability in wireless sensor networks, is a new paradigm of the next-generation sensor network. Sensor nodes are usually battery powered and hence have strict energy constraints. As a result, energy efficiency is also a very critical problem in the CRSN. In this paper, we focus on energy consumption because of spectrum sensing. Furthermore, we present an adaptive spectrum sensing time interval strategy, in which SUs can adjust the next spectrum sensing time interval according to the current spectrum sensing results (namely, channel status). In order to find an optimal spectrum sensing time interval, we introduce the Markov model. Then, we establish a Markov model-based mathematical modeling for analyzing the relationship between spectrum sensing time interval and prior spectrum sensing results. Finally, numerical results demonstrate that the proposed strategy with dynamic adaptive spectrum sensing time interval exceededlisten before talk(LBT) strategy which is widely used for traditional wireless sensor networks.

In-band Spectrum Sensing without Quiet Period for OFDM System in Cognitive Radio

2011 ◽  
Vol 30 (11) ◽  
pp. 2638-2641
Author(s):  
Dong Chen ◽  
Jian-dong Li ◽  
Ji-yong Pang ◽  
Jing Ma
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Band Spectrum ◽  
Quiet Period ◽  
Ofdm System
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