Energy Efficiency Optimization in Massive MIMO Systems with Low-Resolution ADCs

Massive multiple-input multiple-output (MIMO) is a promising 5G technology, but the high energy consumption from numerous radio components is a key challenge. Prior work has explored higher than 4-bit ADCs, but very low 1-2 bit remain uninvestigated. This paper provides an in-depth examination of the resolution versus power savings and signal quality degradation trade-offs with 1–3-bit analog-to-digital converters (ADCs) in Massive MIMO systems. Mathematical modeling and simulations quantify the exponential reduction in power consumption along with losses in key performance metrics like signal-to-interference-plus-noise ratio (SINR), throughput, and spectral efficiency with lower ADC resolutions stemming from increased quantization noise. Advanced linear detection techniques are shown to effectively recover the signal quality degradation. The analysis provides valuable insights on jointly optimizing ADC configuration and signal processing to maximize overall system efficiency. Energy savings of over 50% are demonstrated with 1-bit ADCs along with the ability to maintain acceptable performance metrics using linear detectors. The practical implementation feasibility is also discussed. This work enables ultra-low-resolution ADC deployments in energy-efficient Massive MIMO systems.