An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems
Abstract The past ten years have seen notable research activity and significant advancements in multiuser multiple-input multiple-output (MU-MIMO) antennas. An MU-MIMO antenna system must accommodate many subscribers without additional bandwidth or energy. User scheduling becomes a critical strategy...
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Nature Portfolio
2025-05-01
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| Online Access: | https://doi.org/10.1038/s41598-025-00772-2 |
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| author | A. Sasikumar Logesh Ravi Malathi Devarajan Abdulaziz S. Almazyad Shuvodeep De Guojiang Xiong Seyed Jalaleddin Mousavirad Ali Wagdy Mohamed |
| author_facet | A. Sasikumar Logesh Ravi Malathi Devarajan Abdulaziz S. Almazyad Shuvodeep De Guojiang Xiong Seyed Jalaleddin Mousavirad Ali Wagdy Mohamed |
| author_sort | A. Sasikumar |
| collection | DOAJ |
| description | Abstract The past ten years have seen notable research activity and significant advancements in multiuser multiple-input multiple-output (MU-MIMO) antennas. An MU-MIMO antenna system must accommodate many subscribers without additional bandwidth or energy. User scheduling becomes a critical strategy to take advantage of multiuser heterogeneity and acquire maximum gain in systems where the total number of recipients exceeds the number of transmitting antennas. Due to their high computational cost, many user selection methods currently in use, such as greedy algorithms and exhaustive search are unsuitable for MU-MIMO systems. A suitable scheduling mechanism is essential for the various users in an MU-MIMO system to utilise bandwidth and enhance the system’s total rate effectively. In this article, we proposed a user and antenna scheduling with a population-based meta-heuristic approach, namely the binary salp swarm algorithm (binary SSA), to increase the system sum rate with low computing complexity. We specifically used a population-based meta-heuristics optimisation technique to simulate the user scheduling problem in MU-MIMO systems, characterising complicated issues with binary decisions. Additionally, binary SSA significantly outperforms existing population-based models, such as the binary bat algorithm (binary BA), PSO, SSA, FPA and binary flower pollination algorithm (binary FPA), regarding system throughput/sum rate. The proposed binary SSA technique also effectively achieves a system sum rate compared to a random search scheme and other existing suboptimal scheduling methods. Compared to binary BA and binary FPA approaches, the binary SSA has a higher convergence rate and superior searching capabilities. The simulation outcomes show the proposed binary SSA-based scheduling scheme delivers noticeable performance benefits. |
| format | Article |
| id | doaj-art-8a8aaf742cd84ba5b62d7811b8c203e0 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-8a8aaf742cd84ba5b62d7811b8c203e02025-08-20T02:32:04ZengNature PortfolioScientific Reports2045-23222025-05-0115111710.1038/s41598-025-00772-2An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systemsA. Sasikumar0Logesh Ravi1Malathi Devarajan2Abdulaziz S. Almazyad3Shuvodeep De4Guojiang Xiong5Seyed Jalaleddin Mousavirad6Ali Wagdy Mohamed7Department of Data Science and Business Systems, Faculty of Engineering and Technology, SRM Institute of Science and TechnologyCentre for Advanced Data ScienceSchool of Computer Science and Engineering, Vellore Institute of TechnologyDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud UniversityVirginia TechGuizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou UniversityDepartment of Computer and Electrical Engineering, Mid Sweden UniversityOperations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo UniversityAbstract The past ten years have seen notable research activity and significant advancements in multiuser multiple-input multiple-output (MU-MIMO) antennas. An MU-MIMO antenna system must accommodate many subscribers without additional bandwidth or energy. User scheduling becomes a critical strategy to take advantage of multiuser heterogeneity and acquire maximum gain in systems where the total number of recipients exceeds the number of transmitting antennas. Due to their high computational cost, many user selection methods currently in use, such as greedy algorithms and exhaustive search are unsuitable for MU-MIMO systems. A suitable scheduling mechanism is essential for the various users in an MU-MIMO system to utilise bandwidth and enhance the system’s total rate effectively. In this article, we proposed a user and antenna scheduling with a population-based meta-heuristic approach, namely the binary salp swarm algorithm (binary SSA), to increase the system sum rate with low computing complexity. We specifically used a population-based meta-heuristics optimisation technique to simulate the user scheduling problem in MU-MIMO systems, characterising complicated issues with binary decisions. Additionally, binary SSA significantly outperforms existing population-based models, such as the binary bat algorithm (binary BA), PSO, SSA, FPA and binary flower pollination algorithm (binary FPA), regarding system throughput/sum rate. The proposed binary SSA technique also effectively achieves a system sum rate compared to a random search scheme and other existing suboptimal scheduling methods. Compared to binary BA and binary FPA approaches, the binary SSA has a higher convergence rate and superior searching capabilities. The simulation outcomes show the proposed binary SSA-based scheduling scheme delivers noticeable performance benefits.https://doi.org/10.1038/s41598-025-00772-2Multiuser MIMOUser schedulingBinary salp swarm algorithmMetaheuristics optimizationAntenna |
| spellingShingle | A. Sasikumar Logesh Ravi Malathi Devarajan Abdulaziz S. Almazyad Shuvodeep De Guojiang Xiong Seyed Jalaleddin Mousavirad Ali Wagdy Mohamed An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems Scientific Reports Multiuser MIMO User scheduling Binary salp swarm algorithm Metaheuristics optimization Antenna |
| title | An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems |
| title_full | An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems |
| title_fullStr | An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems |
| title_full_unstemmed | An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems |
| title_short | An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems |
| title_sort | efficient binary salp swarm algorithm for user selection in multiuser mimo antenna systems |
| topic | Multiuser MIMO User scheduling Binary salp swarm algorithm Metaheuristics optimization Antenna |
| url | https://doi.org/10.1038/s41598-025-00772-2 |
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