Computationally efficient algorithms for resource allocation in cognitive radio and green communication systems

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Thesis type
(Thesis) Ph.D.
Date created
Cognitive radio is an interesting concept for solving the problem of spectrum availability by allowing non-licensed users to exploit underutilized licensed frequency bands. We note that a combination of the cognitive radio with cooperative communication and/or MIMO technology can possibly enhance the system performance significantly. In this research, a number of resource allocation problems are examined for cognitive radio systems (CRS) that have relaying and/or MIMO capabilities, and computationally efficient resource allocation schemes are proposed. The general objective is to devise resource allocation schemes in the cognitive radio that maximize the resource utilization under the constraint of acceptable interference to the primary (licensed) users. In particular, in this thesis we present efficient schemes for jointly deciding the assignment of multiple relays to users and their power levels. Fairness is also considered in assigning multiple relays to multiple secondary users. We also propose low-complexity distributed schemes for joint subcarrier and relay assignment in cooperative multi-carrier multi-cast CRS. Another class of resource allocation problems addressed this thesis regards selecting and scheduling users in multiuser systems. In multiuser cognitive MIMO systems, user selection and scheduling significantly affects the system performance. This thesis addresses joint user scheduling and power allocation in the CRS equipped with multiple antennas. Optimization of such user scheduling and power allocation has combinatorial aspects, and the exhaustive search for an exactly optimal solution is impractical due to its computational complexity. This thesis presents low-complexity suboptimal algorithms to maximize the sum-rate capacity of the uplink communication in cognitive MIMO systems under the constraint that the interference to the primary users is below a specified level.
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Supervisor or Senior Supervisor
Thesis advisor: Lee, Daniel C.
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