Quantized Iterative Precoding for Spatially Correlated mmWave Rician Massive MIMO with Oversampling

Massive multiple-input multiple-output (MIMO) systems have gained a lot of attention due to their notable benefits with respect to spectral and energy efficiency. In order to make these systems more cost and power-efficient, using low-resolution digital-to-analog converters (DAC) at each antenna is a preferred implementation method. However, using such low-resolution DACs can introduce quantization distortion which needs to be mitigated by employing various quantized precoding algorithms. In this study, an iterative oversampling precoder (IDAPR) that can be used with quantized massive MIMO under Rician fading channels is presented. It is demonstrated IDAPR outperforms existing oversampling precoders of similar computational complexity with respect to bit error-rate and/or out-of-band (OOB) emissions under spatially correlated mmWave Rician fading channels. Additionally, it is shown that IDAPR can achieve the performance of unquantized precoders for many cases.