Fluid Antenna System Meets Low-Resolution ADCs in Energy-Efficient Cell-Free Massive MIMO

2026-05-27

AI Summary

This work addresses the trade-off between spectral efficiency loss and hardware power consumption caused by low-resolution analog-to-digital converters (ADCs) by integrating fluid antenna systems (FAS) into cell-free massive MIMO architectures, thereby enabling, for the first time, a co-design of spatially reconfigurable antennas and low-precision ADCs. The authors propose an energy-efficiency-driven joint optimization framework that employs the Dinkelbach algorithm to handle fractional programming-based power control and devises an accelerated projected gradient ascent (APGA) algorithm to simultaneously optimize continuous antenna positions and discrete ADC bit allocation. This approach significantly reduces hardware power consumption while effectively compensating for quantization-induced performance loss, markedly enhancing system energy efficiency and outperforming conventional fixed-antenna schemes, thus offering a highly energy-efficient and robust communication paradigm for 6G networks.

Abstract

This paper proposes a novel fluid antenna system (FAS)-enabled architecture to improve energy efficiency (EE) without sacrificing capacity. Specifically, we integrate FAS into cell-free massive MIMO systems to counteract low-resolution ADCs. We establish a comprehensive uplink transmission model and derive analytical expressions for SE and EE. These expressions explicitly capture the quantization error under slow fluid antenna multiple access and quantify the benefits of low-resolution ADCs on EE. Furthermore, we formulate a joint optimization problem to maximize EE performance. To solve this, we develop an efficient alternating optimization framework. This framework leverages the Dinkelbach algorithm-based fractional programming for power control, alongside novel accelerated projected gradient ascent (APGA) algorithms to optimize both continuous FAS positions and discrete ADC bit allocations. Numerical results reveal that low-resolution ADCs aggressively compress signals to save hardware power, which inevitably degrades SE but maintains EE. However, FASs can recover this SE loss thanks to their spatial flexibility and significantly boost EE by improving the received signal prior to destructive quantization. Furthermore, optimized power control can prevent quantization-induced multi-user interference, while efficient bit allocation can reduce exponential hardware power. Ultimately, our proposed FAS-enabled system, coupled with efficient power control and bit allocation, effectively improves system performance and outperforms traditional fixed-position antennas. It establishes a highly robust and energy-efficient paradigm for 6G networks.

Problem

• Fluid Antenna System
• Low-Resolution ADCs
• Energy Efficiency
• Cell-Free Massive MIMO
• Quantization Error

Innovation

• Fluid Antenna System
• Low-Resolution ADCs
• Energy Efficiency
• Cell-Free Massive MIMO
• Alternating Optimization