{"title":"MH-SIA: multi-objective handover using swarm intelligence algorithm for future wireless communication system","authors":"","doi":"10.1007/s11276-024-03661-0","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Heterogeneous networks are needed to meet user demands as wireless network demand rises. Network mobility management is crucial. Mobility management challenges are related to handover solutions to decrease call/packet losses in such networks. The handover is one of the most critical parts of mobility management in the Long-Term Evolution of Advanced (LTE-A) system, which relies on handover procedures to improve quality, coverage, and service in the existing network. The LTE-A future wireless communication networks consist of various femtocells, microcells, and macrocells. Therefore, designing the appropriate mechanism to perform handovers among different cells is a challenging research problem. We propose a novel handover mechanism called multi-objective handover using swarm intelligence algorithm (MH-SIA) for the future wireless communication system. MH-SIA is made of two novel features multi-objective handover and SIA for handover process optimization. The multi-objective trust parameters of each User's Equipment are computed to perform the handover decision-making and target cell selection using the SIA. The computed trust parameters are utilized as the modified fitness function in Differential Evolution (DE) optimization technique. Due to the fast convergence of DE, it performs computationally efficient handover operations. The multi-objective trust parameters are utilized in handover decision-making and target cell selection to improve network performances with minimum handover latency. The experimental result of MH-SIA reveals the efficient performance compared to underlying methods.</p>","PeriodicalId":23750,"journal":{"name":"Wireless Networks","volume":"25 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wireless Networks","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11276-024-03661-0","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Heterogeneous networks are needed to meet user demands as wireless network demand rises. Network mobility management is crucial. Mobility management challenges are related to handover solutions to decrease call/packet losses in such networks. The handover is one of the most critical parts of mobility management in the Long-Term Evolution of Advanced (LTE-A) system, which relies on handover procedures to improve quality, coverage, and service in the existing network. The LTE-A future wireless communication networks consist of various femtocells, microcells, and macrocells. Therefore, designing the appropriate mechanism to perform handovers among different cells is a challenging research problem. We propose a novel handover mechanism called multi-objective handover using swarm intelligence algorithm (MH-SIA) for the future wireless communication system. MH-SIA is made of two novel features multi-objective handover and SIA for handover process optimization. The multi-objective trust parameters of each User's Equipment are computed to perform the handover decision-making and target cell selection using the SIA. The computed trust parameters are utilized as the modified fitness function in Differential Evolution (DE) optimization technique. Due to the fast convergence of DE, it performs computationally efficient handover operations. The multi-objective trust parameters are utilized in handover decision-making and target cell selection to improve network performances with minimum handover latency. The experimental result of MH-SIA reveals the efficient performance compared to underlying methods.
摘要 随着无线网络需求的增加，需要异构网络来满足用户需求。网络移动性管理至关重要。移动性管理面临的挑战与减少此类网络中呼叫/数据包丢失的切换解决方案有关。在高级长期演进（LTE-A）系统中，切换是移动性管理中最关键的部分之一，它依赖于切换程序来提高现有网络的质量、覆盖范围和服务。LTE-A 未来的无线通信网络由各种毫微微蜂窝、微微蜂窝和宏蜂窝组成。因此，设计适当的机制来执行不同小区之间的切换是一个具有挑战性的研究问题。我们为未来的无线通信系统提出了一种名为 "多目标切换群智能算法（MH-SIA）"的新型切换机制。MH-SIA 由多目标切换和用于切换过程优化的 SIA 两项新功能组成。通过计算每个用户设备的多目标信任参数，利用 SIA 进行切换决策和目标小区选择。计算出的信任参数被用作差分进化（DE）优化技术中的修正适应度函数。由于差分进化的快速收敛性，它能执行计算效率高的切换操作。多目标信任参数被用于切换决策和目标小区选择，从而以最小的切换延迟提高网络性能。MH-SIA 的实验结果表明，与基础方法相比，它具有高效的性能。
期刊介绍：
The wireless communication revolution is bringing fundamental changes to data networking, telecommunication, and is making integrated networks a reality. By freeing the user from the cord, personal communications networks, wireless LAN''s, mobile radio networks and cellular systems, harbor the promise of fully distributed mobile computing and communications, any time, anywhere.
Focusing on the networking and user aspects of the field, Wireless Networks provides a global forum for archival value contributions documenting these fast growing areas of interest. The journal publishes refereed articles dealing with research, experience and management issues of wireless networks. Its aim is to allow the reader to benefit from experience, problems and solutions described.
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