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Novel Expressions for the Outage Probability and Diversity Gains in Fluid Antenna System
Univ Las Amer, Ecuador.
Escuela Politec Nacl, Ecuador.
Escuela Politec Nacl, Ecuador.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Univ Oulu, Finland.ORCID iD: 0000-0001-8858-9646
2024 (English)In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 13, no 2, p. 372-376Article in journal (Refereed) Published
Abstract [en]

The flexibility and reconfigurability at the radio frequency (RF) front-end offered by the fluid antenna system (FAS) make this technology promising for providing remarkable diversity gains in networks with small and constrained devices. Toward this direction, this letter compares the outage probability (OP) performance of non-diversity and diversity FAS receivers undergoing spatially correlated Nakagami- ${m}$ fading channels. Although the system properties of FAS incur in complex analysis, we derive a simple yet accurate closed-form approximation by relying on a novel asymptotic matching method for the OP of a maximum-gain combining-FAS (MGC-FAS). The approximation is performed in two stages, the approximation of the cumulative density function (CDF) of each MGC-FAS branch, and then the approximation of the end-to-end CDF of the MGC-FAS scheme. With these results, closed-form expressions for the OP and the asymptotic OP are derived. Finally, numerical results validate our approximation of the MGC-FAS scheme and demonstrate its accuracy under different diversity FAS scenarios.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2024. Vol. 13, no 2, p. 372-376
Keywords [en]
Fading channels; Antennas; Signal to noise ratio; Diversity reception; Probability; Power system reliability; Electron tubes; Asymptotic matching; maximum-gain combining-FAS (MGC-FAS); Nakagami-m fading; spatial correlation; outage probability
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-202949DOI: 10.1109/LWC.2023.3329780ISI: 001167560000025OAI: oai:DiVA.org:liu-202949DiVA, id: diva2:1853782
Note

Funding Agencies|Escuela Politcnica Nacional

Available from: 2024-04-23 Created: 2024-04-23 Last updated: 2024-04-23

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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