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Maximum likelihood (ML) carrier-frequency offset (CFO) estimation for orthogonal frequency-division multiple-access (OFDMA) uplink with generalized carrier-assignment scheme (GCAS) is a complex multi-parameter estimation problem. The computational complexity of ML solution based on a multi-dimensional exhaustive search is prohibitive. The existing sub-optimal solutions reduce the complexity by replacing the multi-dimensional search with a sequence of single-dimensional searches. However, these solutions suffer from either poor estimation accuracy or being still of fairly high complexity. In this paper, we propose a new approach called divide-and-update frequency estimator (DUFE), for CFO estimation. Compared with the existing approaches, the proposed DUFE has lower computational complexity while maintaining high estimation accuracy similar to that of the exact ML solution. Performance and complexity comparisons are provided, along with numerical results to illustrate the effectiveness of the proposed method.
Date of Publication: March 2009