Signal Detection Methods in Cognitive Radio Networks: A Performance Comparison

2020 ◽  
pp. 63-74
Author(s):  
Pablo Palacios Játiva ◽  
Milton Román-Cañizares ◽  
Carlos Saavedra ◽  
José Julio Freire
Keyword(s):  
Cognitive Radio ◽  
Signal Detection ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Performance Comparison ◽  
Detection Methods ◽  
A Performance

Spectrum Assignment Algorithm Based on Clonal Selection in Cognitive Radio Networks

2012 ◽  
Vol 457-458 ◽  
pp. 931-939
Author(s):  
Xiao Fei Wang ◽  
Xi Zhang ◽  
Yue Bing Chen ◽  
Lei Zhang ◽  
Chao Jing Tang
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Constraint Satisfaction ◽  
Clonal Selection ◽  
Radio Networks ◽  
Performance Comparison ◽  
Immune Optimization ◽  
Spectrum Assignment ◽  
Network Utilization ◽  
Assignment Algorithm

An improved-immune-clonal-selection based spectrum assignment algorithm (IICSA) in cognitive radio networks is proposed, combing graph theory and immune optimization. It uses constraint satisfaction operation to make encoded antibody population satisfy constraints, and realizes the global optimization. The random-constraint satisfaction operator and fair-constraint satisfaction operator are designed to guarantee efficiency and fairness, respectively. Simulations are performed for performance comparison between the IICSA and the color-sensitive graph coloring algorithm. The results indicate that the proposed algorithm increases network utilization, and efficiently improves the fairness.

Sign in / Sign up

Export Citation Format

Share Document