Energy efficiency analysis and modeling of cognitive and heterogeneous wireless networks

The surging energy costs and the environmental consequences of energy generation and exploitation have put energy efficiency aspect of wireless systems into focus in an unprecedented manner. Moreover, the capacity expectations and requirements for wireless networks have been relentlessly increasing with the adoption of new services and sophisticated wireless terminals. In this thesis, we evaluate cognitive and heterogeneous wireless network paradigms from energy efficiency perspective that has become vital due to the above mentioned phenomena. We specifically focus on energy efficiency analysis and modeling of these systems for realizing the "green networks" objective. We first provide a comprehensive account of energy efficiency of wireless networks. At a cross-sectional level, we consider cognitive radios (CR) paradigm which is affecting all facets of wireless data communications. The CR concept is evaluated from the "energy-efficient operation" and "energy efficiency enabler" perspectives. At the microscopic level, we focus on small cells, namely femtocells, and propose a new networking paradigm called cognitive femtocell networks (CFN). We analyze them in terms of energy efficiency via our analytical model and compare their performance with that of macrocell-only networks as well as traditional femtocell networks.