New equivalent model of quantizer with noisy input and its application for ADC resolution determination in an uplink MIMO receiver

TL;DR

This paper introduces a new equivalent model for quantizers with noisy inputs, separating non-linear distortion from white noise, to optimize ADC resolution in MIMO receivers, supported by numerical simulations.

Contribution

The paper presents a novel model that distinguishes quantization error components, enabling precise ADC resolution determination for MIMO systems.

Findings

Model accurately predicts quantization error components.

Numerical simulations confirm the model's effectiveness.

Application to ADC resolution optimization in MIMO receivers.

Abstract

When a quantizer input signal is the sum of the desired signal and input white noise, the quantization error is a function of total input signal. Our new equivalent model splits the quantization error into two components: a non-linear distortion (NLD) that is a function of only the desired part of input signal (without noise), and an equivalent out-put white noise. This separation is important because these two terms affect MIMO system performance differently. This paper introduces our model, and applies it to determine the minimal Analog-to-Digital Converter (ADC) resolution necessary to operate a conventional MIMO receiver with negligible performance degradation. We also provide numerical simulations to confirm the theory. Broad ramifications of our model are further demonstrated in two companion papers presenting low-complexity suppression of the NLD arising from insufficient ADC resolution, and a digital dithering that significantly reduces the MIMO transmitter Digital-to-Analog Converters (DAC) resolution requirement.