Reducing Quantizer Distortion Due to Insufficient Resolution in Massive MIMO Receivers

Use of low-resolution (1-4 bits) Analog-to-Digital Converters (ADCs) can reduce power consumption in Massive Multiple-Input, Multiple-Output (MIMO) receivers. Ordinary linear beamforming may suffice for low-resolution ADCs under conditions on the Signal-to-Noise Ratio (SNR) and number of antennas that may be called low but sufficient resolution. However, if the SNR increases or number of antennas decreases, an error floor will typically occur. We introduce three low-complexity iterative algorithms to reduce quantization noise in such low but insufficient resolution cases. These algorithms process the raw quantizer outputs prior to detection, achieving up to two orders-of-magnitude reduction in Bit Error Rate (BER). Our algorithms are based on the new `equivalent model' for quantizers developed in our prior work. These algorithms can be applied to any number of bits and any modulation format. We focus on Orthogonal Frequency-Division Multiplexing (OFDM) to show that quantizer distortion can be corrected without going to the frequency domain.