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Bandwidth efficient joint estimation of CFO and doubly selective channel in OFDM based cognitive radio

In this paper we propose a bandwidth efficient joint carrier frequency offset (CFO) and doubly selective channel (DCS) estimation technique for high mobility OFDM based cognitive radio (CR) system. As the OFDM based CR systems are having a non contiguous band nature due to the dependency of subcarriers on the availability, the channel estimation for such system is a tedious task. Moreover, in high mobility OFDM systems the number of parameters to be estimated is considerably high and hence channel estimation with limited number of pilots is a quiet challenging issue. By exploring the sparse nature of the wireless channel and using the Complex Exponential Basis Expansion Model (CE-BEM), we propose a bandwidth efficient iterative joint estimation technique by formulating the estimation problem into compressive sensing (CS) frame work. Our proposed technique make use of Orthogonal Matching Pursuit (OMP) and Expectation Conditional Maximization (ECM) algorithms after formulating the problem into CS frame work for formally estimating carrier frequency offset and channel coefficients. The simulation studies conducted at different mobile speeds validates the performance of proposed technique.