A novel adaptive algorithm is proposed in this paper to remove I/Q mismatch, the second-order intermodulation (IM2), lSI and A WGN simultaneously in a direct conversion receiver (DCR) by using cascaded adaptive filters. 1M2 signals are treated as variable real DC values both in in-phase and quadrature channels separately, so they can be removed simultaneously with only one complex tap incorporated into a complex feed forward equalizer (CFFE). In addition, a real valued adaptive mismatch canceller is employed before the CFFE. Furthermore, a complex decision feedback equalizer (CDFE) is employed to cancel the residual lSI. To accelerate the convergence rates of the taps and to reduce the estimation variance, an internal iterative algorithm is introduced. Simulation results are provided to verify the superior performance of the proposed method.

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This work studies the effect of in-phase/quadrature (I/Q) imbalance on time-reversal space-time block coded (TR-STBC) communication systems operating over frequencyselective fading channels. The transceiver I/Q imbalance in a 2 × 1 TR orthogonal STBC (TR-OSTBC) system is studied in detail, and low-complexity mitigation solutions are proposed by exploiting the special structure of the received data. Our results show that the proposed solutions both in time domain and in frequency domain can effectively mitigate the I/Q distortion in such a system.

A novel algorithm is proposed in this paper to remove DC offsets, flicker noise and lSI simultaneously in a direct conversion receiver (DCR) by using adaptive filters and system identification. The time-varying complex DC offsets are treated as real DC values both in in-phase and quadrature channels separately and can be removed simultaneously with only one complex tap. Flicker noise is modeled as a complex autoregressive (AR) random process so the whole system to be identified transforms to an ARX model. After joint estimating the unknown coefficients in the model during training period, the desired signal can be estimated by using decision feedback method. Simulation results reveal the superior performance obtained by the proposed algorithm.