Carrier-Frequency Offset Estimation for MIMO-OFDMA Uplink Transmission

Maximum likelihood (ML) carrier-frequency offset (CFO) estimation in the uplink of an orthogonal frequency- division multiple-access (OFDMA) system with a generalized carrier- assignment scheme (GCAS) is a complex multiple-parameter estimation problem. The inclusion of multiple-input multiple-output (MIMO) processing renders the problem even more complicated. The computational complexity of the ML solution based on a multi-dimensional exhaustive search is prohibitive. In this paper, we propose to decompose the MIMO-OFDMA CFO estimation into a series of multiple-input single-output (MISO) ML estimations, each of which adopts a new iterative approach. The proposed solution has affordable computational complexity while maintaining high estimation accuracy similar to the exact ML solution. Performance and complexity comparisons are provided with numerical results to illustrate the effectiveness of the proposed method.