Resource Allocation In Cognitive Radios

The fixedness of the current Command and Control spectrum allocation approach has lead to an artificial scarcity of spectrum due to under utilization;which in turn affect the optimization of the whole scope of wireless communication resources.A radio,therefore,that can sense and be aware of its radio spectrum environment and available services;to identify vacant spectrum resources and use it freely or at a price, has the potential to provide higher bandwidth services,improve spectrum efficiency, and reduce inefficiency due to the human factor in spectrum management.This could be achieved by a radio that can make autonomous decisions about how it utilizes radio resources at its disposal.Cognitive radios are strong candidates for achieving this.In this thesis,we present several resource allocation methodologies in cognitive radios,primarily in the context of efficient spectrum resource allocation and power control,to more efficiently support flexibility and optimization in wireless networks. Our theoretical modeling provides guidelines for achieving Pareto optimal spectrum allocation and characterizes optimization problems under uncertain resource availability constraints.Our numerical and simulations results demonstrate significant improvement in spectral resources utilization efficiency and acquisition delay,robust Quality of Service,and budget efficient power-control strategies.Resource allocation in cognitive radios is investigated under two schemes:the free spectrum usage,Opportunistic Spectrum Access scheme,under the current Command and Control regime,and the paid spectrum usage,Dynamic Spectrum Leasing.For the Opportunistic Spectrum Access,where the secondary spectrum user searches for spectrum holes which are not used by primary users(license holders) and communicate through them,we propose variable-persistence spectrum recovery schemes.A key feature of the proposed methods is that insight about the spectrum recovery strategy and development of cognitive radio systems is gained.The variable-persistence schemes are analyzed under the identically independently distribution(i.i.d.) and the 2-state Markov primary user traffic patterns.Numerical case studies are presented to verify the theoretical analysis and illustrate the performance of the schemes proposed.Successful resource allocation in cognitive radio systems operating under opportunistic spectrum usage has to overcome the uncertainty of spectrum bands availability as well as the chaotic wireless propagation environment.One of the highlights of this work is the application of the concept of portfolio optimization to characterize the joint power control and spectrum band discovery problems under uncertain cognitive radio operative environments.The resulting power strategy also marks out the subbands to be used-essentially achieving soft spectrum sensing.The limitations of the strategies are investigated through the sensitivity analysis of the solutions obtained.A raw data processing approach is also given leading to an alternative algorithm for stable data processing.Numerical results are presented to demonstrate the potential of the proposed approaches.As for paid spectrum usage,this work proposes a hierarchical framework for dynamic spectrum leasing.A centralized spectrum price setting mechanism to facilitate the framework is also proposed.Further,the advantages and social optimality of the framework are analyzed.Based on that,we holistically develop a mechanism that enables joint spectrum allocation,revenue maximization and power control through spectrum pricing while achieving a desired QoS performance.This lets the Spectrum Manager (SM) to maximize the spectrum usage efficiency through monopolistic based price setting;the Network Operator(NetOp) to maximize its revenue;and the end user(s) to autonomously trade-off between its utility and spectrum cost through emission power control-essentially forming a non-cooperative power control game for which we show the existence and uniqueness of the Nash equilibrium.Numerical results are presented to demonstrate the potential of the proposed framework in the spectrum price setting by the SM,revenue maximization by the NetOp,and power control strategy adopted by the user in various price thresholds.