Firefly algorithm for movable antenna arrays

Article


Kha, H., Le, T., Thuc, K., Luyen, T., Yang, X. and Ng, D. 2024. Firefly algorithm for movable antenna arrays. IEEE Wireless Communications Letters. https://doi.org/10.1109/LWC.2024.3456899
TypeArticle
TitleFirefly algorithm for movable antenna arrays
AuthorsKha, H., Le, T., Thuc, K., Luyen, T., Yang, X. and Ng, D.
Abstract

This letter addresses a multivariate optimization problem for linear movable antenna arrays (MAAs). Particularly, the position and beamforming vectors of the under-investigated MAA are optimized simultaneously to maximize the minimum beamforming gain across several intended directions, while ensuring interference levels at various unintended directions remain below specified thresholds. To this end, a swarm-intelligence-based firefly algorithm (FA) is introduced to acquire an effective solution to the optimization problem. Simulation results reveal the superior performance of the proposed FA approach compared to the state-of-the-art approach employing alternating optimization and successive convex approximation. This is attributed to the FA's effectiveness in handling non-convex multivariate and multimodal optimization problems without resorting approximations.

KeywordsFirefly algorithm; nature-inspired optimization; movable antenna arrays
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeSustainability
Research GroupDepartment of Design Engineering & Mathematics
PublisherIEEE
JournalIEEE Wireless Communications Letters
ISSN
Electronic2162-2345
Publication dates
Online10 Sep 2024
Publication process dates
Accepted05 Sep 2024
Deposited11 Sep 2024
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

This paper was accepted for publication in IEEE Wireless Communications Letters on September 05, 2024. ©2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Digital Object Identifier (DOI)https://doi.org/10.1109/LWC.2024.3456899
LanguageEnglish
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Random walks, Lévy flights, Markov chains and metaheuristic optimization
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Benchmark problems in structural optimization
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Efficiency analysis of swarm intelligence and randomization techniques
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Modelling of a pulsating heat pipe and start up asymptotics
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Yang, X. and Deb, S. 2012. Two-stage eagle strategy with differential evolution. International Journal of Bio-Inspired Computation. 4 (1), pp. 1-5. https://doi.org/10.1504/IJBIC.2012.044932
Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect
Yang, X., Hosseini, S. and Gandomi, A. 2012. Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect. Applied Soft Computing. 12 (3), pp. 1180-1186. https://doi.org/10.1016/j.asoc.2011.09.017
User position aware multicell beamforming for a distributed antenna system
Le, T. and Nakhai, M. 2011. User position aware multicell beamforming for a distributed antenna system. IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications. Toronto, ON, Canada 11 - 14 Sep 2011 IEEE. pp. 1423-1427 https://doi.org/10.1109/PIMRC.2011.6139736
An iterative algorithm for downlink multi-cell beam-forming
Le, T. and Nakhai, M. 2011. An iterative algorithm for downlink multi-cell beam-forming. 2011 IEEE Global Telecommunications Conference. Houston, TX, USA 05 - 09 Dec 2011 IEEE. pp. 1-6 https://doi.org/10.1109/GLOCOM.2011.6133913
Throughput analysis of network coding enabled wireless backhauls
Le, T. and Nakhai, M. 2011. Throughput analysis of network coding enabled wireless backhauls. IET Communications. 5 (10), pp. 1318-1327. https://doi.org/10.1049/iet-com.2010.0223
Green radio: radio techniques to enable energy-efficient wireless networks
Han, C., Harrold, T., Armour, S., Krikidis, I., Videv, S., Grant, P., Haas, H., Thompson, J., Ku, I., Wang, C., Le, T., Nakhai, M., Zhang, J. and Hanzo, L. 2011. Green radio: radio techniques to enable energy-efficient wireless networks. IEEE Communications Magazine. 49 (6), pp. 46-54. https://doi.org/10.1109/MCOM.2011.5783984
Power-efficient downlink transmission in multicell networks with limited wireless backhaul
Le, T., Nasseri, S., Zarrebini-Esfahani, A., Nakhai, M. and Mills, A. 2011. Power-efficient downlink transmission in multicell networks with limited wireless backhaul. IEEE Wireless Communications. 18 (5), pp. 82-88. https://doi.org/10.1109/MWC.2011.6056696
Accelerated particle swarm optimization and support vector machine for business optimization and applications
Yang, X., Deb, S. and Fong, S. 2011. Accelerated particle swarm optimization and support vector machine for business optimization and applications. Fong, S. (ed.) NDT 2011: International Conference on Networked Digital Technologies. Macau, China 11 - 13 Jul 2011 Springer. pp. 53-66 https://doi.org/10.1007/978-3-642-22185-9_6
Bat algorithm for multi-objective optimisation
Yang, X. 2011. Bat algorithm for multi-objective optimisation. International Journal of Bio-Inspired Computation. 3 (5), pp. 267-274. https://doi.org/10.1504/IJBIC.2011.042259
Mixed variable structural optimization using Firefly Algorithm
Gandomi, A., Yang, X. and Alavi, A. 2011. Mixed variable structural optimization using Firefly Algorithm. Computers and Structures. 89 (23-24), pp. 2325-2336. https://doi.org/10.1016/j.compstruc.2011.08.002
Possible power-saving gains by dividing a cell into tiers of smaller cells
Le, T. and Nakhai, M. 2010. Possible power-saving gains by dividing a cell into tiers of smaller cells. Electronics Letters. 46 (16), pp. 1163-1165. https://doi.org/10.1049/el.2010.1509
A new metaheuristic bat-inspired algorithm
Yang, X. 2010. A new metaheuristic bat-inspired algorithm. in: González, J., Pelta, D., Cruz, C., Terrazas, G. and Krasnogor, N. (ed.) Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) Berlin Springer.
Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization
Yang, X. and Deb, S. 2010. Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization. in: González, J., Pelta, D, Cruz, C., Terrazas, G. and Krasnogor, N. (ed.) Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) Springer. pp. 101-111
Optimization and data mining for fracture prediction in geosciences
Shi, G. and Yang, X. 2010. Optimization and data mining for fracture prediction in geosciences. Procedia Computer Science. 1 (1), pp. 1359-1366. https://doi.org/10.1016/j.procs.2010.04.151
Firefly algorithm, stochastic test functions and design optimisation
Yang, X. 2010. Firefly algorithm, stochastic test functions and design optimisation. International Journal of Bio-Inspired Computation. 2 (2), pp. 78-84. https://doi.org/10.1504/IJBIC.2010.032124
Oil and gas assessment of the Kuqa depression of Tarim Basin in western China by simple fluid flow models of primary and secondary migrations of hydrocarbons
Shi, G., Zhang, Q., Yang, X. and Mi, S. 2010. Oil and gas assessment of the Kuqa depression of Tarim Basin in western China by simple fluid flow models of primary and secondary migrations of hydrocarbons. Journal of Petroleum Science and Engineering. 75 (1-2), pp. 77-90. https://doi.org/10.1016/j.petrol.2010.10.009
Firefly algorithms for multimodal optimization
Yang, X. 2009. Firefly algorithms for multimodal optimization. in: Stochastic Algorithms: Foundations and Applications; 5th International Symposium, SAGA 2009, Sapporo, Japan, October 26-28, 2009. Proceedings Springer.
Cuckoo search via Lévy flights
Yang, X. and Deb, S. 2009. Cuckoo search via Lévy flights. in: World Congress on Nature & Biologically Inspired Computing (NaBIC 2009) IEEE Publications. pp. 210-214