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This paper considers signal detection in massive multiple-inputmultiple-output (MIMO) systems with general additive hardware impairments andone-bit quantization. First, we present the quantization-unaware and Bussgangdecomposition-based linear receivers by generalizing them for the consideredhardware impairment model. We propose an optimization problem to estimate theuplink data signals by choosing a suitable cost function that treats theunquantized received signal at the base station as the variable. We exploit theadditional structure of the one-bit quantization and signal modulation byincluding proper constraints. To solve the non-convex quadratically-constrainedquadratic programming (QCQP) problem, we propose an ADMM-based algorithm withclosed-form update equations. Then, we replace the harsh projectors in theupdates with their soft versions to improve the detection performance. We showthat the proposed ADMM-based algorithm outperforms the state-of-the-art linearreceivers significantly in terms of bit error rate (BER) and the performancegain increases with the number of antennas and users.

ADMM-Based One-Bit Quantized Signal Detection for Massive MIMO Systems with Hardware Impairments