{"title":"ECapRO-SEM: Enhanced Capuchin Route Optimizer for Spectral Efficiency Maximization in Wireless Networks","authors":"Ahmed M. Khedr;Dilna Vijayan;Mohamed Saad","doi":"10.1109/JSEN.2024.3510547","DOIUrl":null,"url":null,"abstract":"The progress made in self-interference (SI) revocation and suppression techniques for wireless communication has significantly enhanced the viability of employing full-duplex (FD) transmission abilities. Compared to half-duplex (HD) transmission, these capabilities notably enhance the end-to-end spectral efficiency (SE), leading to significant advantages for multihop routing in wireless communication scenarios. There has recently been an increase in interest in discovering paths in multihop wireless communication scenarios that exhibit higher SE. It has been proved that solving for higher SE paths within multihop wireless communication scenarios cannot be solved polynomially in networks employing FD interference-constrained systems. This study introduces ECapRO-SEM, an innovative route optimization algorithm called the enhanced capuchin route optimizer for SE maximization (ECapRO-SEM) for wireless network communication. Its goal is to improve the end-to-end SE of wireless communication networks. The algorithm begins by formulating an optimization problem to maximize end-to-end SE in FD forwarding across specified paths while effectively accounting for interference. Subsequently, the algorithm employs an enhanced nature-inspired metaheuristic optimization technique to precisely identify the routing path that yields the utmost end-to-end SE. Nature-inspired optimization methods, exemplified by the capuchin search algorithm (CSA), have emerged as potent metaheuristic tools for approximating optimal solutions. We enhance the CSA by integrating it with the genetic algorithm (GA). The novel ECapRO-SEM algorithm demonstrates its superiority in achieving peak end-to-end SE for wireless network routing, outperforming existing methodologies in extensive simulations. Simulation results show that ECapRO outperforms Mod-Dijkstras, Pruned-HC, and CapRO by 33.53%, 5.17%, and 3.40%, respectively, at different signal-to-noise ratios (SNRs). Furthermore, with various SI cancellation (SIC) factors, ECapRO outperforms Mod-Dijkstras, Pruned-HC, and CapRO by 210.33%, 5.25%, and 2.14%, respectively.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 2","pages":"3659-3671"},"PeriodicalIF":4.3000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10786379/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
The progress made in self-interference (SI) revocation and suppression techniques for wireless communication has significantly enhanced the viability of employing full-duplex (FD) transmission abilities. Compared to half-duplex (HD) transmission, these capabilities notably enhance the end-to-end spectral efficiency (SE), leading to significant advantages for multihop routing in wireless communication scenarios. There has recently been an increase in interest in discovering paths in multihop wireless communication scenarios that exhibit higher SE. It has been proved that solving for higher SE paths within multihop wireless communication scenarios cannot be solved polynomially in networks employing FD interference-constrained systems. This study introduces ECapRO-SEM, an innovative route optimization algorithm called the enhanced capuchin route optimizer for SE maximization (ECapRO-SEM) for wireless network communication. Its goal is to improve the end-to-end SE of wireless communication networks. The algorithm begins by formulating an optimization problem to maximize end-to-end SE in FD forwarding across specified paths while effectively accounting for interference. Subsequently, the algorithm employs an enhanced nature-inspired metaheuristic optimization technique to precisely identify the routing path that yields the utmost end-to-end SE. Nature-inspired optimization methods, exemplified by the capuchin search algorithm (CSA), have emerged as potent metaheuristic tools for approximating optimal solutions. We enhance the CSA by integrating it with the genetic algorithm (GA). The novel ECapRO-SEM algorithm demonstrates its superiority in achieving peak end-to-end SE for wireless network routing, outperforming existing methodologies in extensive simulations. Simulation results show that ECapRO outperforms Mod-Dijkstras, Pruned-HC, and CapRO by 33.53%, 5.17%, and 3.40%, respectively, at different signal-to-noise ratios (SNRs). Furthermore, with various SI cancellation (SIC) factors, ECapRO outperforms Mod-Dijkstras, Pruned-HC, and CapRO by 210.33%, 5.25%, and 2.14%, respectively.
期刊介绍:
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