Data Dissemination and Channel Selection in Cognitive Radio Networks

Author(s):  
Mubashir Husain Rehmani ◽  
Yasir Faheem

In this chapter, the authors provide a comprehensive review of broadcasting and channel selection strategies for wireless cognitive radio networks. In the beginning, some applications of the data dissemination in wireless cognitive radio networks are discussed to highlight their importance and utility. Next, the authors provide a detailed classification of broadcasting protocols in light of the existing literature, and the pros and cons of each classified category are discussed. Afterwards, the data dissemination is briefly discussed in the context of multi-channel environments and the related issues are highlighted. Then, the authors discuss the challenges of data dissemination in cognitive radio networks, followed by the classification of channel selection strategies along with their advantages and disadvantages for various classes of applications. In the last part, the authors conclude this chapter with open research issues that need to be addressed to provide efficient channel selection and data dissemination strategies in cognitive radio networks.

2013 ◽  
Vol 36 (10-11) ◽  
pp. 1172-1185 ◽  
Author(s):  
Mubashir Husain Rehmani ◽  
Aline Carneiro Viana ◽  
Hicham Khalife ◽  
Serge Fdida

Author(s):  
Yong Yao ◽  
Alexandru Popescu ◽  
Adrian Popescu

Cognitive radio networks are a new technology based on which unlicensed users are allowed access to licensed spectrum under the condition that the interference perceived by licensed users is minimal. That means unlicensed users need to learn from environmental changes and to make appropriate decisions regarding the access to the radio channel. This is a process that can be done by unlicensed users in a cooperative or non-cooperative way. Whereas the non-cooperative algorithms are risky with regard to performance, the cooperative algorithms have the capability to provide better performance. This chapter shows a new fuzzy logic-based decision-making algorithm for channel selection. The underlying decision criterion considers statistics of licensed user channel occupancy as well as information about the competition level of unlicensed users. The theoretical studies indicate that the unlicensed users can obtain an efficient sharing of the available channels. Simulation results are reported to demonstrate the performance and effectiveness of the suggested algorithm.


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