Optimization algorithms exploiting unitary constraints
IEEE Transactions on Signal Processing
Compensation of Phase Noise in OFDM Wireless Systems
IEEE Transactions on Signal Processing
Phase Noise Estimation and Mitigation for OFDM Systems
IEEE Transactions on Wireless Communications
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
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In this paper, a novel maximum likelihood (ML) method is proposed to estimate and mitigate phase noise (PN) for cognitive orthogonal frequency division multiplexing (OFDM) systems. In the proposed method, PN estimation is formulated as a unitary-constrained optimization problem based on the ML criterion. Using the obtained estimate of the PN vector, both common phase error and inter-carrier interference are effectively mitigated and reduced for symbol error rate (SER) performance improvement. Simulation results show that the proposed method can mitigate PN effectively, and obtain better SER performance for cognitive OFDM systems compared with conventional methods.