Efficient and Robust Spectrum Management for Cognitive Radio Networks.

The recent advent of cognitive radio (CR) technology has potential for making a significant improvement in spectrum efficiency by allowing secondary (unlicensed) devices or users (SUs) to opportunistically utilize unused portions of the licensed spectrum bands. Such opportunistic spectrum access has drawn considerable attention for its ability to alleviate the spectrum scarcity problem that we may soon face due to the rapid increase in wireless spectrum demand and also due to the inefficiency of the current static spectrum-allocation policies. We identify and address two main challenges that hinder the realization of dynamic spectrum access (DSA): (i) primary users’ (PUs’) fear of interference that can lead to potential loss of customers, and (ii) lack of economic incentives to PUs for spectrum sharing. We provide novel approaches and comprehensive solutions to these challenges to fully exploit the benefits of DSA. In order to meet these challenges from a comprehensive perspective, we first address the problem of detecting large-scale primary signals (e.g., TV signals) and present a framework that minimizes the sensing overhead while achieving the detectability requirements imposed by regulatory bodies such as the Federal Communications Commission (FCC). Second, we deal with security vulnerabilities of cooperative spectrum sensing and propose an attack- and fault-tolerant spectrum sensing algorithm. The proposed algorithm preserves the detection accuracy in the presence of compromised or faulty sensors by detecting and filtering out abnormal sensing reports. Third, we propose a small-scale primary signal (e.g., wireless microphones) detection framework that jointly performs cooperative sensing and location/transmit-power estimation to improve the detection accuracy and efficiency. Fourth, we present a robust PU-tracking scheme that exploits the temporal correlation in shadow fading in received primary signal strengths. Fifth, we explore the problem of enabling DSA for mobile CRs and address the key challenges—modeling spectrum opportunities, protecting primary communications, and devising an optimal spectrum access strategy in such mobile CR networks. Finally, we address the problem of providing economic incentives to PUs for spectrum sharing and propose optimal spectrum pricing and wireless service provider selection strategies in dynamic spectrum markets.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86501/1/alexmin_1.pd