Enormous Fluid Antenna Systems (E-FAS)--Part II: Channel Estimation
2026-02-23 • Information Theory
Information Theory
AI summaryⓘ
The authors study a new wireless system called enormous fluid antenna systems (E-FAS), which uses special surfaces to guide signals more efficiently than usual wireless methods. They analyze how real-world conditions for measuring the signal (called channel estimation) affect the system's performance, both for one user and multiple users. They find that estimation errors cause limits on signal quality and interference, especially when serving many users. However, their results show that even with these imperfections, E-FAS still offers significant advantages over traditional systems. Their findings are supported by simulations and comparisons to other estimation methods.
enormous fluid antenna systemsmetasurfacessurface-wave propagationchannel state informationchannel estimationminimum mean-square-errorzero-forcing precodingsignal-to-noise ratiospatial multiplexingpilot overhead
Authors
Farshad Rostami Ghadi, Kai-Kit Wong, Masoud Kaveh, Hao Xu, Baiyang Liu, Kin-Fai Tong, Chan-Byoung Chae
Abstract
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.