Slow FAMA under Nakagami-m fading channels

IF 2.9 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Digital Signal Processing Pub Date : 2025-04-02 DOI:10.1016/j.dsp.2025.105208

Paulo R. de Moura , Hugerles S. Silva , Ugo S. Dias , Higo T.P. Silva , Osamah S. Badarneh , Rausley A.A. de Souza

引用次数: 0

Abstract

This article investigates slow fluid antenna multiple access (FAMA) under the effect of Nakagami-m fading. Exact expressions for the outage probability (OP) based on signal-to-interference ratio (SIR) and signal-to-interference plus noise ratio (SINR) are presented. An upper bound for SIR-based OP and an approximate expression for the SNIR-based OP are derived using the Gauss-Laguerre quadrature approach. Bounds for the multiplexing gain are also deduced. In addition to showing that lower values of the fading parameter have a beneficial effect on the overall mean performance, this work also illustrates several important conclusions concerning the system performance as a function of system parameters. Monte Carlo simulations validate the exact and approximate expressions.

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慢FAMA在nakagami衰落频道下

本文研究了中上米衰落影响下的慢速流体天线多址（FAMA）。给出了基于信干扰比（SIR）和信干扰加噪声比（SINR）的中断概率（OP）的精确表达式。利用Gauss-Laguerre正交法导出了基于sir的OP的上界和基于snir的OP的近似表达式。还推导了复用增益的边界。除了表明较低的衰落参数值对总体平均性能有有益的影响外，这项工作还说明了几个关于系统性能作为系统参数函数的重要结论。蒙特卡罗模拟验证了精确和近似表达式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Digital Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

17.20%

发文量

435

审稿时长

66 days

期刊介绍： Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,