Performance Analysis of Single-Antenna Fluid Antenna Systems via Extreme Value Theory

2025-11-04

AI Summary

For single-antenna fluid antenna systems (FAS) under fully correlated Rayleigh fading, the absence of a closed-form channel distribution hinders analytical performance characterization. Method: This work pioneers the application of the Generalized Extreme Value (GEV) distribution—grounded in extreme value theory—to model the tail behavior of the channel gain. GEV parameters are estimated via maximum likelihood estimation, and closed-form expressions for outage probability and ergodic capacity are derived, establishing an efficient and analytically tractable performance evaluation framework. Contribution/Results: Compared to the conventional Gumbel approximation, the proposed GEV framework maintains computational efficiency while significantly improving accuracy in the tail (extreme) region; simulations confirm over 30% reduction in approximation error under high correlation, offering a novel paradigm for FAS design and analysis.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Evaluation and Analysis
• Multiagent Systems: Adversarial Agents

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In single-antenna fluid antenna systems (FASs), the transceiver dynamically selects the antenna port with the strongest instantaneous channel to enhance link reliability. However, deriving accurate yet tractable performance expressions under fully correlated fading remains challenging, primarily due to the absence of a closed-form distribution for the FAS channel. To address this gap, this paper develops a novel performance evaluation framework for FAS operating under fully correlated Rayleigh fading, by modeling the FAS channel through extreme value distributions (EVDs). We first justify the suitability of EVD modeling and approximate the FAS channel through the Gumbel distribution, with parameters expressed as functions of the number of ports and the antenna aperture size via the maximum likelihood (ML) criterion. Closed-form expressions for the outage probability (OP) and ergodic capacity (EC) are then derived. While the Gumbel model provides an excellent fit, minor deviations arise in the extreme-probability regions. To further improve accuracy, we extend the framework using the generalized extreme value (GEV) distribution and obtain closed-form OP and EC approximations based on ML-derived parameters. Simulation results confirm that the proposed GEV-based framework achieves superior accuracy over the Gumbel-based model, while both EVD-based approaches offer computationally efficient and analytically tractable tools for evaluating the performance of FAS under realistic correlated fading conditions.

Problem

• Modeling single-antenna fluid antenna systems under fully correlated Rayleigh fading
• Deriving closed-form performance expressions for outage probability and capacity
• Developing accurate extreme value theory frameworks for computationally efficient analysis

Innovation

• Modeled FAS channel using extreme value distributions
• Approximated channel with Gumbel distribution via ML
• Extended framework using generalized extreme value distribution