Analytical Modeling and Performance Evaluation of Cognitive Radio Networks

2010 ◽  
Author(s):  
Derya Cavdar ◽  
H. Birkan Yilmaz ◽  
Tuna Tugcu ◽  
Fatih Alagöz
Keyword(s):  
Performance Evaluation ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Analytical Modeling ◽  
Radio Networks ◽  
And Performance

Modeling and Performance Evaluation

2015 ◽  
pp. 746-769
Author(s):  
Yuehong Gao ◽  
Zhidu Li ◽  
Guoting Zhang ◽  
He Bai
Keyword(s):  
Markov Chain ◽  
Performance Evaluation ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Queuing Theory ◽  
Deep Understanding ◽  
Radio Networks ◽  
Network Calculus ◽  
And Performance ◽  
Stochastic Network Calculus

Performance evaluation and analysis are of key importance to obtain deep understanding of cognitive radio networks. Some effects have been made to model and analyze the performance of cognitive radio networks. In the literature, there are two methodologies: queuing theory/Markov chain-based analysis and stochastic network calculus-based analysis. These two methodologies rely on different mathematical basics and modeling approaches. Thus, they lead to different output metrics on various viewpoints. This chapter aims to give an overall introduction to both methodologies. First, the fundamental models used in queuing/Markov chain-based analysis are presented, followed by their applications in cognitive radio networks. Then, network calculus basics are introduced with the modeling and application in performance analysis of the cognitive radio network.

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