Abstract
Spectrum efficiency and energy efficiency are two critical issues for wireless communication networks. Cognitive radio has emerged as a promising paradigm to improve the spectrum usage efficiency and cope with spectrum scarcity problem. However, cognitive radio may cause extra energy consumption because it relies on new and extra technologies and algorithms. Optimizing the energy-efficiency of cognitive radio networks not only reduces environmental impact, but also cuts network cost to enable economical green cognitive radio. Thus high energy efficiency will be one of key requirements for practical cellular cognitive radio networks. Because of the dynamic nature of Cognitive Radio Network (CRN), the activity of Secondary User (SU) such as “when and how to sense” and “when and how to transmit” significantly affects the throughput of SUs, protection of Primary User (PU) and energy efficiency of the whole CRNs. In this context, this thesis mainly focuses on energy efficiency and throughput enhancement problem with sufficient protection to PU in CRNs as a function of SU frame structure. Three contributions are provided to tackle the challenge and address this issue: 1) an upperbound approach for eigenvalue ratio based detection, 2) a strategy for normalized throughput enhancement by frame length optimization for CRN, 3) a joint design of spectral and energy efficient cellular CRN with uplink power adaptation. The impact of power control, optimal sensing time and frame length on the achievable energy efficiency, throughput and interference are illustrated and analysed in CRN. It is shown that the enhancement of energy efficiency and throughput, and the mitigation of interference to PUs could be realized by frame structure optimization and proper uplink power adaptation. The analytical results are useful to determine how to select frame structure as well as the power control strategy, subject to network environment and required performance objectives.