An adaptive algorithm for direct conversion receivers: Architecture and performance analysis

Abstract

An adaptive algorithm is proposed in this thesis to remove in-phase and quadrature (I/Q) mismatch, direct current (DC) offsets, flicker noise and inter-symbol interference (ISI) simultaneously in a direct conversion receiver (DCR). I/Q mismatch is cancelled by a real valued adaptive mismatch canceller and DC offsets are removed with one complex tap. In addition, flicker noise is modeled as a complex autoregressive (AR) random process so the system to be identified transforms to an Auto Regressive with eXternal input (ARX) model. After estimating the coefficients in the model during training period, the desired signal can be estimated by using decision feedback method. To accelerate the convergence of the algorithm and to mitigate the interactions among the adaptations of the different groups of the taps of the filters, an internal iterative algorithm is introduced. Moreover, the analysis of the convergence in the mean of the taps of the proposed filters is given. Simulation results are provided to verify the superior performance of the proposed algorithm