CAREER: Cross-layer optimization in Cognitive Radio Networks in the Physical interference model based on SINR constraints: Algorithmic Foundations

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One of the most significant recent advances in wireless networks is theCognitive Radio Network (CRN), which can allow unlicensed (or secondary) users to access spectrum bands allocated to licensed (primary) users, without disrupting their performance.Since many licensed spectrum bands have been found to be greatly underutilized,CRNs can potentially enhance the spectrum usage significantly.The basic principle underlying CRNs is to first sense the spectrum usage by primary users, and then allocate power levels and channels opportunistically to the secondary users, so that the interference levels at primary users are within an acceptable threshold. Most theoretical analyses of protocols in such networks use disk/graph based approximations (in which "close-by" links cannot transmit simultaneously) to model wireless interference; however, these are inadequate and can lead to infeasible solutions with unacceptable interference levels at the primary users.The goal of this proposal is to examine the theoretical foundations of cross-layer optimization in Cognitive Radio Networks in the Physical interference model, which is considered a much better approximation of interference than disk based models. The results of this proposal will contribute to the theoretical underpinnings of the broader area of wireless networks, not just the application of CRN, because of the central role interference plays.