Semi-blind MIMO OFDM systems with precoding aided CFO estimation and ICA based equalization

We propose a semi-blind multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, with a precoding aided carrier frequency offset (CFO) estimation approach, and an independent component analysis (ICA) based equalization structure. A number of reference data sequences are carefully designed offline and are superimposed to source data via a non-redundant linear precoding process, which can kill two birds with one stone, without introducing any extra total transmit power and spectral overhead. First, the reference data sequences are selected from a pool of carefully designed orthogonal sequences. The CFO estimation is to minimize the sum cross-correlation between the CFO compensated signals and the rest orthogonal sequences in the pool. Second, the same reference data enable elimination of the permutation and quadrant ambiguity in the ICA equalized signals by maximizing the cross-correlation between the ICA equalized signals and the reference data. Simulation results show that, without extra bandwidth and power needed, the proposed semi-blind system achieves a bit error rate (BER) performance close to the ideal case with perfect channel state information (CSI) and no CFO. Also, the precoding aided CFO estimation outperforms the constant amplitude zero autocorrelation (CAZAC) sequences based CFO estimation approach, with no spectral overhead.