Machine learning for data detection in low-resolution quantization-based systems

Abstract

In the ever-evolving world of wireless commu¬nication, the demand for faster, more efficient systems has never been greater. As 5G becomes widespread and the world prepares for 6G, new wireless technologies, such as using many anten¬nas together (massive MIMO) and operating at very high frequencies like millimeter-wave and Tera¬hertz, are becoming increasingly important. These innovations promise unprecedented data rates and connectivity, but they come with a significant challenge: power consumption. At the heart of this issue lies the analog-to-digital converter (ADC), a critical component in wireless base stations that converts the received analog signals into digital signals. High-resolution ADCs, while precise, are power-hungry, consuming energy at levels that threaten the sustainability of next-generation net¬works.