Enormous fluid antenna systems (E-FAS) have recently emerged as a new wireless architecture in which intelligent metasurfaces act as guided electromagnetic interfaces, enabling surface-wave (SW) propagation with much lower attenuation and more control than conventional space-wave transmission. While prior work has reported substantial power gains under perfect channel state information (CSI), the impact of practical channel acquisition on E-FAS performance remains largely unexplored. This paper presents the first comprehensive analysis of E-FAS-assisted downlink transmission under pilot-based channel estimation. We develop an estimation framework for the equivalent end-to-end channel and derive closed-form expressions for the statistics of the minimum mean-square-error (MMSE) channel estimate and its estimation error. Building on these results, we analyze both single-user and multiuser operation while explicitly accounting for the training overhead. For the single-user case, we characterize the outage probability and achievable rate with imperfect CSI, and reveal an inherent signal-to-noise ratio (SNR) saturation phenomenon caused by residual self-interference. For the multiuser case, we study zero-forcing (ZF) precoding based on imperfect channel estimates and show that the system becomes interference-limited in the high SNR regime because of residual inter-user interference. Furthermore, we quantify the trade-off between spatial multiplexing gains and pilot overhead when the number of users increases. Analytical findings are validated via Monte Carlo simulations and benchmarked against least-squares (LS) estimation and conventional non-E-FAS transmission. The results reveal that despite CSI imperfections and training costs, E-FAS retains substantial performance advantages and provides robustness enabled by its amplified large-scale channel gain.

翻译：超大规模流体天线系统（E-FAS）作为一种新型无线架构近期兴起，其通过智能超表面作为引导式电磁接口，能够实现比传统空间波传输衰减更低、控制性更强的表面波传播。尽管已有研究在完美信道状态信息（CSI）条件下报告了显著的功率增益，但实际信道获取对E-FAS性能的影响在很大程度上仍未得到探索。本文首次对基于导频的信道估计下的E-FAS辅助下行链路传输进行了全面分析。我们建立了等效端到端信道的估计框架，并推导了最小均方误差（MMSE）信道估计值及其估计误差统计量的闭式表达式。基于这些结果，我们分析了单用户和多用户操作，并明确考虑了训练开销。针对单用户场景，我们刻画了非完美CSI下的中断概率和可达速率，并揭示了由残余自干扰引起的固有信噪比（SNR）饱和现象。对于多用户场景，我们研究了基于非完美信道估计的迫零（ZF）预编码，并证明由于残余用户间干扰，系统在高SNR区域会变为干扰受限。此外，当用户数量增加时，我们量化了空间复用增益与导频开销之间的权衡关系。分析结果通过蒙特卡洛仿真进行了验证，并与最小二乘（LS）估计及传统非E-FAS传输方案进行了对比。结果表明，尽管存在CSI不完美性和训练成本，E-FAS仍能保持显著的性能优势，并凭借其放大的大规模信道增益提供鲁棒性。