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Massive multiple-input multiple-output (MIMO) is a key technology for 5Gwireless communications with a promise of significant capacity increase. Theuse of low-resolution data converters is crucial for massive MIMO to make theoverall transmission as cost- and energy-efficient as possible. In this work,we consider a downlink millimeter-wave (mmWave) transmission scenario, wheremultiple users are served simultaneously by massive MIMO with one-bitdigital-to-analog (D/A) converters. In particular, we propose a novel precoderdesign based on signal-to-leakage-plus-noise ratio (SLNR), which minimizesenergy leakage into undesired users while taking into account impairments dueto nonlinear one-bit quantization. We show that well-known regularizedzero-forcing (RZF) precoder is a particular version of the proposed SLNR-basedprecoder, which is obtained when quantization impairments are totally ignored.Numerical results underscore significant performance improvements along withthe proposed SLNR-based precoder as compared to either RZF or zero-forcing (ZF)precoders.

SLNR Based Precoding for One-Bit Quantized Massive MIMO in mmWave Communications