| Summary: | Recent unprecedented growth in the wireless market has forced network operators to find new techniques to reduce the operating costs, increase data rates, improve the spectrum utilization and reduce the energy consumption of various network elements. To overcome these challenges, opportunistic spectrum access through cognitive radios and relay-based cooperative communications have emerged as a new communication paradigm. However, to make these technologies practical, various resource management techniques must be optimized. Furthermore, we also need to explore the energy efficiency of these next generation wireless systems and identify key research issues and challenges in order to achieve sustainable "green" communication networks.
In this thesis, we design efficient resource allocation techniques for cognitive and cooperative networks and explore the energy efficiency of these systems. First, we study a capacity-maximizing power allocation problem in orthogonal frequency-division multiplexing (OFDM) based cognitive radio system while considering the allowed interference limits. We resort to an energy-aware capacity expression taking into account subcarrier availability and propose several suboptimal schemes that perform at a level close to that of optimal schemes. Second, we explore joint power and subcarrier allocation algorithms and fairness for OFDMA-based multiuser cooperative wireless systems. We challenge the traditional view of relaying algorithms by relaying only if it is beneficial. We state the problem in the form of a capacity-maximizing integer programming optimization problem and propose a heuristic solution. Next, we study the problem of relay selection in a cooperative network where regular mobile nodes could act as relays and cooperate if provided with incentives to do so. Using concepts from economics of asymmetric information, we propose incentive compatible schemes for relays and suggest a low-complexity heuristic relay selection scheme. Finally, we investigate the energy efficiency of the next generation wireless systems and present a short summary of methods and techniques to improve the energy efficiency of cellular networks. We also describe some important research issues and examine the major challenges to reduce the energy consumption of the cognitive and cooperative based emerging wireless networks. In concluding remarks, we also give some future research directions towards which the research in this thesis could lead. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
|
|---|
