Power and rate allocation to secondary users in competitive cognitive radio networks

In the case of Opportunistic Spectrum Access (OSA), unlicensed secondary users have only limited knowledge of channel parameters or other users' information. Spectral opportunities are asymmetric due to time and space varying channels. Owing to this inherent asymmetry and uncertainty of traffic patterns, secondary users can have trouble detecting properly the real usability of unoccupied channels and as a consequence visiting channels in such a way that they can communicate with each other in a bounded period of time. Therefore, the channel service quality, and the neighborhood discovery (NB) phase are fundamental and challenging due to the dynamics of cognitive radio networks. The authors provide an analysis of these challenges, controversies, and problems, and review the state-of-the-art literature. They show that, although recently there has been a proliferation of NB protocols, there is no optimal solution meeting all required expectations of CR users. In this chapter, the reader also finds possible solutions focusing on an asynchronous channel allocation covering a channel ranking.

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Security for Cognitive Radio Networks

Advances in Wireless Technologies and Telecommunication - Cognitive Radio and Interference Management ◽

10.4018/978-1-4666-2005-6.ch013 ◽

2012 ◽

pp. 238-256 ◽

Cited By ~ 2

Author(s):

Rajni Dubey ◽

Sanjeev Sharma ◽

Lokesh Chouhan

Keyword(s):

Cognitive Radio ◽

Wireless Network ◽

Cognitive Radio Networks ◽

Reference Model ◽

Development Stage ◽

Radio Networks ◽

Full Duplex ◽

Secondary Users ◽

Wireless Communication Network ◽

Open Systems Interconnection

Most of the frequency spectrum bands have already been licensed, and the licensed spectrum is not being utilized efficiently. Cognitive Radio Networks (CRNs) are the kind of full duplex radio that automatically altered its transmission or reception parameters, in such a way that the entire wireless communication network of which it is a node communicates efficiently, while avoiding interference with primary or secondary users. In this chapter, the authors introduce the concept of security threats that may pose a serious attack in CRN. Due to the unique characteristics of CRN, such network is highly vulnerable to security attacks compared to wireless network or infrastructure-based wireless network. The main objective of this chapter is to assist CR designers and the CR application engineers to consider the security factors in the early development stage of CR techniques. Challenges and various security issues are explored with respect to OSI (Open Systems Interconnection) reference model. Various possible and attacks are discussed broadly and respective solutions are also proposed by this chapter. Different architectures and models are also explained, and compared with the existing models.

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On the Use of Particle Swarm Optimization Techniques for Channel Assignments in Cognitive Radio Networks

Multidisciplinary Computational Intelligence Techniques ◽

10.4018/978-1-4666-1830-5.ch012 ◽

2012 ◽

pp. 202-214 ◽

Cited By ~ 1

Author(s):

Hisham M. Abdelsalam ◽

Haitham S. Hamza ◽

Abdoulraham M. Al-Shaar ◽

Abdelbaset S. Hamza

Keyword(s):

Cognitive Radio ◽

Cognitive Radio Networks ◽

Channel Assignment ◽

Assignment Problem ◽

Pso Algorithm ◽

Radio Networks ◽

Optimization Techniques ◽

Secondary Users ◽

Swarm Optimization ◽

Channel Assignment Problem

Efficient utilization of open spectrum in cognitive radio networks requires appropriate allocation of idle spectrum frequency bands (not used by licensed users) among coexisting cognitive radios (secondary users) while minimizing interference among all users. This problem is referred to as the spectrum allocation or the channel assignment problem in cognitive radio networks, and is shown to be NP-hard. Accordingly, different optimization techniques based on evolutionary algorithms were needed in order to solve the channel assignment problem. This chapter investigates the use of particular swarm optimization (PSO) techniques to solve the channel assignment problem in cognitive radio networks. In particular, the authors study the definitiveness of using the native PSO algorithm and the Improved Binary PSO (IBPSO) algorithm to solve the assignment problem. In addition, the performance of these algorithms is compared to that of a fine-tuned genetic algorithm (GA) for this particular problem. Three utilization functions, namely, Mean-Reward, Max-Min-Reward, and Max-Proportional-Fair, are used to evaluate the effectiveness of three optimization algorithms. Extensive simulation results show that PSO and IBPSO algorithms outperform that fine-tuned GA. More interestingly, the native PSO algorithm outperforms both the GA and the IBPSO algorithms in terms of solution speed and quality.

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