Dynamic Spectrum Allocation For Heterogeneous Cognitive Radio Network

The rapid growth of wireless communication technology has resulted in the increasing demand on spectrum resources. However, according to a recent study, most of the allocated frequency bands experience significant under-utilization.Cognitive radio is proposed as an efficient way to address the issue of spectrum scarcity and under-utilization. It allows the secondary users(SUs)/cognitive radio(CR) to opportunistically utilize the allocated spectrum without causing harmful interference to the primary users(PUs). Spectrum sensing is required to be performed first before accessing the channels, sensing the idle spectrum in the surrounding environment and adjusting operating parameters, further making effective use of detected spectrum resources. During sensing, the system also needs to decide which channel is allocated to which SU for sensing and utilization(spectrum allocation). In order to protect the PUs,the SU is required to vacate the channel, and to find another idle channel to resume its unfinished transmission, as soon as the return of the PU is detected(spectrum handoff). These are the so- called spectrum management problems in cognitive radio networks(CRNs). In this dissertation, the author widely exploits the spectrum sensing, spectrum allocation problems to improve the system performance, while leaving the spectrum handoff problem for possible future work. It is shown that the spectrum, if well managed, is able to enhance the network performance, and increase the achievable throughput.One of the most fundamental problems of spectrum management in cognitive radio network is: how to appropriately allocate the spectrum to the secondary sender-destination(S-D) for sensing and utilization. In this work, the author studies the spectrum allocation problem under a more practical scenario where taking the heterogeneous characteristics of both secondary S-D and PU channels into consideration. The PU channel is characterized by channel idle probability and channel capacity, while the secondary S-D is depicted by the energy detection threshold, received SNR and geographical location.With the objective to maximize the achievable throughput for secondary S-D, the author formulates the spectrum allocation problem into a linear integer optimization problem under availability constraint, spectrum span constraint and interference free constraint. This problem is proved to be NP-complete, and a recent result in theoretical computer science called randomized rounding algorithm with polynomial computational complexity is developed to find the suboptimal solution. Evaluation results show that our proposed algorithm can achieve a close-to-optimal solution while keeping the complexity low.