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.

翻译：本文提出一种新型流体天线系统（FAS）架构，旨在不牺牲容量的前提下提升能量效率（EE）。具体而言，我们将FAS集成到无蜂窝大规模MIMO系统中，以抵消低分辨率ADC的不利影响。我们建立了完整的上行传输模型，并推导了频谱效率（SE）与能量效率（EE）的解析表达式。这些表达式明确刻画了慢速流体天线多址接入下的量化误差，并量化了低分辨率ADC对EE的增益。进一步地，我们构建了一个联合优化问题以最大化EE性能。为求解该问题，我们开发了一种高效的交替优化框架，该框架融合了基于Dinkelbach算法的分数规划用于功率控制，以及新型加速投影梯度上升（APGA）算法用于优化连续FAS位置与离散ADC比特分配。数值结果表明，低分辨率ADC虽通过激进压缩信号降低硬件功耗，不可避免导致SE下降，但能维持EE稳定。而FAS凭借空间灵活性可弥补SE损失，并通过在破坏性量化前改善接收信号显著提升EE。此外，优化功率控制可抑制量化引发的多用户干扰，高效比特分配则能降低指数级增长的硬件功耗。最终，我们所提出的FAS系统结合高效的功率控制与比特分配，有效提升了系统性能，并超越传统固定位置天线，为6G网络建立了高度鲁棒且高能效的范例。