Symbol-Level Precoding with Low Resolution DACs for Large-Scale Array MU-MIMO Systems

Abstract

While (Multiple Input-Multiple Output) MIMO systems based on large-scale antenna arrays are seen as the solution to the continuously increasing demands in modern wireless systems, they require high hardware complexity and power consumption. To tackle this, solutions based on low resolution Analog-to-Digital Converters (ADCs) / Digital-to-Analog Converters (DACs) have been developed in the literature where they mainly propose quantized versions of typical channel dependent linear precoding solutions. Alternatively, nonlinear Symbol level Precoding techniques have been recently proposed for downlink Multi User (MU)-MIMO systems with low resolution DACs that achieve significantly improved performance in several cases. The existing SLP approaches support only DACs of 1-bit resolution which result in significant performance degradations, especially when constellations with order greater than 4 are employed. To that end, in this work a novel SLP approach is developed that supports systems with DACs of any resolution and it is applicable for any type of constellation. As it is verified by the presented numerical results, the proposed approach exhibits significantly improved performance when constellations with order greater than 4 are employed and require reduced computational complexity, compared to the existing solutions for the 1-bit DAC case.