B-spline neural network assisted space-time equalization for single-carrier multiuser nonlinear frequency-selective MIMO uplink

Abstract

This paper designs a nonlinear space-time equalizer based on B-spline neural network (BSNN) for the single-carrier high-throughput multiuser frequency-selective multiple-input multiple-output (MIMO) nonlinear uplink. Specifically, based on a BSNN parametrization of the nonlinear high power amplifiers (NHPAs) at mobile terminals' transmitters, a novel nonlinear identification scheme is developed to estimate the nonlinear dispersive MIMO uplink channel, which includes the BSNN models for the NHPAs at transmitters as well as the frequency-selective MIMO channel impulse response (CIR) matrix. Furthermore, the BSNN inverse models of the NHPAs are also estimated in closed-form. This allows the base station to implement nonlinear multiuser detection effectively using the space-time equalization (STE) based on the estimated frequency-selective MIMO CIR matrix and followed by compensating for the nonlinear distortion of the transmitters' NHPAs based on the estimated BSNN inverse models. Simulation results are utilized to demonstrate the superior bit error rate performance of our nonlinear STE approach for single-carrier high-throughput multiuser nonlinear frequency-selective MIMO uplink.

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