Dynamic spectrum access based on cognitive radio has been regarded as a prospective solution to improve spectrum utilization for wireless communications. By considering the allocation efficiency, fairness, and economic incentives, spectrum marketing has been attracting more and more attentions in recent years. In this thesis, we focus on one of the most effective spectrum marketing methods, i.e., auction approach, in multi-channel cognitive radio networks. After presenting some fundamentals and related works, we begin our discussion in a recall-based auction system where buyers have various service requirements and the seller could recall some sold items after the auction to deal with a sudden increase of its own demand. Both single-winner and multi-winner auctions are designed and analyzed. In addition, we also consider the heterogeneity of radio resource sellers and formulate a framework of combinatorial spectrum auction. With theoretical analyses and simulation results, we show that our proposed algorithms can improve spectrum utilization while satisfy the heterogeneous requirements of different wireless users.

Radio spectrum is scarce in wireless communication. While there is an increasing demand for spectrum due to the substantial growth of wireless communication systems, extensive measurements observe that conventional static spectrum allocation policies introduce significant inefficiency in spectrum utilization. To achieve higher spectrum efficiency, cognitive radio networks have emerged as a revolutionary technology by allowing unlicensed (secondary) users to utilize licensed bands opportunistically without harming licensed (primary) users. In this thesis, we seek to design a new framework that addresses three important issues in cognitive radio networks simultaneously: protection of primary users, incentives for primary networks to share their spectrum and the performance guarantee for secondary users. Leveraging the idea of Value at Risk from economics, in our solution, primary networks maximize their profits by charging secondary users for opportunistic spectrum access, while in the meantime secondary users impose utility constraints to manage the risks and guarantee performance probabilistically.

Radio spectrum is scarce in wireless communication. While there is an increasing demand for spectrum due to the substantial growth of wireless communication systems, extensive measurements observe that conventional static spectrum allocation policies introduce significant inefficiency in spectrum utilization. To achieve higher spectrum efficiency, cognitive radio networks have emerged as a revolutionary technology by allowing unlicensed (secondary) users to utilize licensed bands opportunistically without harming licensed (primary) users. In this thesis, we seek to design a new framework that addresses three important issues in cognitive radio networks simultaneously: protection of primary users, incentives for primary networks to share their spectrum and the performance guarantee for secondary users. Leveraging the idea of Value at Risk from economics, in our solution, primary networks maximize their profits by charging secondary users for opportunistic spectrum access, while in the meantime secondary users impose utility constraints to manage the risks and guarantee performance probabilistically.

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 120-126).

Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 101-105).

Thesis (M.S.)--Rutgers University, 2008. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 59-60).

Thesis (M.S.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 62-63)

Includes bibliographical references (p. 56-60).

Thesis (M.E.)--University of Canterbury, 2009. / Typescript (photocopy). "December 2009." Includes bibliographical references (p. [95)-102). Also available via the World Wide Web.

The increased demand on wireless applications, coupled with the current inefficiency in spectrum usage, mandate a new communication paradigm shift from fixed spectrum assignment to dynamic spectrum sharing which can be achieved using the cognitive radio technology. Cognitive radio allows unlicensed secondary nodes to form communication links over licensed spectrum bands on an opportunistic basis which increases the spectrum management efficiency. Cognitive radio networks (CRN), however, impose unique challenges due to the fluctuation in the available spectrum as well as the diverse quality of service requirements. One of the main challenges is the establishment and maintenance of routes in multi-hop CRNs. In this thesis, we critically investigate the problem of routing in multi-hop CRNs. The main objective of this research is to maximize network connectivity while limiting routing delay. We developed a general connectivity metric for single-band and multi-band CRNs based on the properties of the Laplacian matrix eigenvalues spectrum. We show through analytical and simulation results that the developed metric is more robust and has lower computational complexity than the previously proposed metrics. Furthermore, we propose a new position-based routing algorithm for large scale CRNs which significantly reduces the routing computational complexity with negligible performance degradation compared to the traditional full node search algorithm. In addition, the connectivity metric developed in this thesis is used to develop a connectivity-aware distributed routing protocol for CRNs. Finally, we use a commodity cognitive radio testbed to demonstrate the concept of CR Wi-Fi networks.