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Self-Organization in IEEE Standard 1900.4-Based Cognitive Radio Networks
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Author(s): Majed Haddad (INRIA Sophia-Antipolis, France), Eitan Altman (INRIA Sophia-Antipolis, France), Sana ben Jemaa (Orange Labs, France), Salah Eddine Elayoubi (Orange Labs, France)and Zwi Altman (Orange Labs, France)
Copyright: 2013
Pages: 19
Source title:
Self-Organization and Green Applications in Cognitive Radio Networks
Source Author(s)/Editor(s): Anwer Al-Dulaimi (Brunel University, UK), John Cosmas (Brunel University, UK)and Abbas Mohammed (Blekinge Institute of Technology, Sweden)
DOI: 10.4018/978-1-4666-2812-0.ch004
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Abstract
Distributing Radio Resource Management (RRM) in heterogeneous wireless networks is an important research and development axis that aims at reducing network complexity, signaling, and processing load in heterogeneous environments. Performing decision-making involves incorporating cognitive capabilities into the mobiles such as sensing the environment and learning capabilities. This falls within the larger framework of cognitive radio (Mitola, 2000) and self-organizing networks (3GPP, 2008). In this context, RRM decision making can be delegated to mobiles by incorporating cognitive capabilities into mobile handsets, resulting in the reduction of signaling and processing burden. This may however result in inefficiencies such as those known as the “Tragedy of commons” (Hardin, 1968) that are inherent to equilibria in non-cooperative games. Due to the concern for efficiency, centralized network architectures and protocols keep being considered and being compared to decentralized ones. From the point of view of the network architecture, this implies the co-existence of network-centric and terminal-centric RRM schemes. Instead of taking part within the debate among the supporters of each solution, the authors propose a hybrid scheme where the wireless users are assisted in their decisions by the network that broadcasts aggregated load information (Elayoubi, 2010). At some system’s states, the network manager may impose his decisions on the network users. In other states, the mobiles may take autonomous actions in reaction to information sent by the network. Specifically, the authors derive analytically the utilities related to the Quality of Service (QoS) perceived by mobile users and develop a Bayesian framework to obtain the equilibria. They then analyze the performance of the proposed scheme in terms of achievable throughput (for both mobile terminals and the network) and evaluate the price of anarchy which measures how good the system performance is when users play selfishly instead of playing to achieve the social optimum (Johari, 2004). Numerical results illustrate the advantages of using the hybrid game framework in a network composed of HSDPA and 3G LTE system that serve streaming and elastic flows. Finally, this chapter addresses current questions regarding the integration of the proposed hybrid Stackelberg scheme in practical wireless systems, leading to a better understanding of actual cognitive radio gains.
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