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Joint beamforming, channel and power allocation in multi-user and multi-channel underlay MISO cognitive radio networks

In this thesis, we consider joint beamforming, power, and channel allocation in a multi-user and multi-channel underlay cognitive radio network (CRN). In this system, beamforming is implemented at each SU-TX to minimize the co-channel interference. The formulated joint optimization problem is a non-convex, mixed integer nonlinear programming (MINLP) problem. We propose a solution which consists of two stages. At first, given a channel allocation, a feasible solutions for power and beamforming vectors are derived by converting the problem into a convex form with an introduced optimal auxiliary variable and semidefinite relaxation (SDR) approach. Next, two explicit searching algorithms, i.e., genetic algorithm (GA) and simulated annealing (SA)-based algorithm are proposed to determine optimal channel allocations. Simulation results show that beamforming, power and channel allocation with SA (BPCA-SA) algorithm achieves a close optimal sum-rate with a lower computational complexity compared with beamforming, power and channel allocation with GA (BPCA-GA) algorithm. Furthermore, our proposed allocation scheme shows significant improvement than zero-forcing beamforming (ZFBF).

Identiferoai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/30077
Date03 December 2014
CreatorsDadallage, Suren Tharanga Darshana
ContributorsCai, Jun (Electrical and Computer Engineering), Yahampath, Pradeepa (Electrical and Computer Engineering) Luo, Yunhua (Mechanical Engineering)
Source SetsUniversity of Manitoba Canada
Detected LanguageEnglish

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