Sensor Selection Based on Dempster-Shafer Evidence Theory under Collaborative Spectrum Sensing in Cognitive Radio Sensor Networks

2019 ◽  
Author(s):  
Ying Gao ◽  
Ming Diao ◽  
Takeo Fujii
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Evidence Theory ◽  
Sensor Selection ◽  
Cognitive Radio Sensor Networks ◽  
Collaborative Spectrum Sensing

Spectrum Sensing in Cognitive Radio Sensor Networks

2014 ◽  
pp. 48-72 ◽  
Author(s):  
Farooq Alam ◽  
Zahooruddin ◽  
Ayaz Ahmad ◽  
Muhammad Iqbal
Keyword(s):  
Wireless Sensor Networks ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Wireless Sensor ◽  
Research Issues ◽  
Comprehensive Review ◽  
Cognitive Radio Sensor Networks ◽  
Cognitive Radio Sensor Network ◽  
Core Issues

In this chapter, the authors provide a comprehensive review of spectrum sensing in cognitive radio sensor networks. Firstly, they focus on general techniques utilized for spectrum sensing in wireless sensor networks. To have good understanding of core issues of spectrum sensing, the authors then give a brief description of cognitive radio networks. Then they give a thorough description of the main techniques that can be helpful in doing spectrum sensing in cognitive radio sensor network. The authors conclude this chapter with open research issues and challenges that need to be addressed to provide efficient spectrum sensing in order to minimize the limitations in cognitive radio sensor networks.

scholarly journals A Linear Weighted Sum Multi-objective Optimization Algorithm Based on PSO for Wideband Spectrum Sensing

2015 ◽  
Vol 11 (9) ◽  
pp. 9 ◽  
Author(s):  
Yonghua Wang ◽  
Yuehong Li ◽  
Yiquan Zheng ◽  
Ting Liang ◽  
Yuli Fu
Keyword(s):  
Particle Swarm Optimization ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Weighted Sum ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Cognitive Radio Sensor Networks ◽  
Wideband Spectrum Sensing

In order to maximize throughput and minimize interference of the wideband spectrum sensing problem in OFDM cognitive radio sensor networks, a linear weighted sum multi-objective algorithm based on the Particle Swarm Optimization is proposed. The multi-objective optimization advantages of Particle Swarm Optimization are utilized to solve the optimal threshold vector of the spectrum sensing problem in OFDM cognitive radio sensor networks. So the network can get a larger throughput under the condition of small interference. The simulation results show that the proposed algorithm can make larger throughput while keeping the interference is smaller in OFDM cognitive radio sensor networks. Thus the spectrum resources are used more effectively.

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