Adaptive Reduced-Rank MBER Linear Receive Processing for Large Multiuser MIMO Systems

In this work, we propose a novel adaptive reduced-rank strategy based on joint interpolation, decimation and filtering (JIDF) for large multiuser multiple-input multiple-output (MIMO) systems. In this scheme, a reduced-rank framework is proposed for linear receive processing and multiuser interference suppression according to the minimization of the bit error rate (BER) cost function. We present a structure with multiple processing branches that performs dimensionality reduction, where each branch contains a group of jointly optimized interpolation and decimation units, followed by a linear receive filter. We then develop stochastic gradient (SG) algorithms to compute the parameters of the interpolation and receive filters along with a low-complexity decimation technique. Simulation results are presented for time-varying environments and show that the proposed MBER-JIDF receive processing strategy and algorithms achieve a superior performance to existing methods at a reduced complexity.

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