光通信增强型 IDMBOC 可最大限度地提高回程效果并保持最佳的小区规模

Q3 Engineering
K. Mankar, S. Varade
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引用次数: 0

摘要

光通信网络对高数据传输速率和低延迟的需求日益增长,因此需要创新的解决方案来提高系统效率。随着数据需求的持续增长和 5G 网络中各种应用的出现,在保持最佳小区规模的同时最大限度地降低回程效应已成为一个巨大的障碍。现有方法无法实现网络参数的全面优化,导致性能指标下降。为了解决这些制约因素,我们提出的方法将光通信基础设施集成到 IDMBOC 系统中,从而最大限度地提高回程效应,并保持最佳的小区规模。这项工作的主要动机是,面对不断增长的数据流量,需要提高 5G 网络的效率和质量。现有方法往往难以同时优化 5G 网络的多个方面,如载波聚合、动态频谱共享、数据包优先级、网络功能虚拟化、频率规划、HetNets 部署和网络切片过程。因此,这些方法无法提供稳健且可扩展的解决方案。为了解决这些问题,我们提出了一种迭代双元启发式方法,它以协同的方式将蚁狮优化(ALO)和灰狼优化(GWO)结合起来,用于 5G 部署。所提出的方法在功能上优于现有模型。通过利用 ALO 和 GWO 的优势,我们的方法在最大化回程效果和保持最佳小区规模方面与最近提出的方法相比实现了更优越的性能指标。初步结果显示,误码率 (BER) 明显降低了 8.3%,能耗降低了 4.9%,吞吐量提高了 8.5%,通信延迟降低了 4.5%。所取得的成果证明了我们的 5G 网络优化方法具有革命性的潜力,并为该领域未来针对不同场景的研究和进步铺平了道路。这些改进将彻底改变光通信网络,以适应 5G、物联网和其他当代应用的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optical communication enhanced IDMBOC for maximizing backhaul-effect & maintaining optimum cell sizes
The increasing need for high data rates and low latency in optical communication networks necessitates innovative solution for system efficiency enhancements. With the persistent increase in data demand and the emergence of diverse applications in 5G networks, minimizing the backhaul-effect while maintaining optimal cell sizes has become a formidable obstacle. Existing methods are incapable of achieving a comprehensive optimization of network parameters, resulting in degraded performance metrics. To address these constraints, our proposed approach integrates optical communication infrastructure into IDMBOC systems which maximizes backhaul-effect and preserves optimal cell sizes. This work is primarily motivated by the need to improve the efficiency and quality of 5G networks in the face of rising data traffic. Existing methods frequently struggle to optimize concurrently multiple 5G network aspects, such as carrier aggregation, dynamic spectrum sharing, packet prioritization, network function virtualization, frequency planning, HetNets deployments, and network slicing process. As a result, these methods are incapable of delivering robust and scalable solutions. To solve these issues, we present an Iterative dual metaheuristic method that combines ant lion optimization (ALO) and grey wolf optimization (GWO) in a synergistic manner for 5G deployments. The proposed method is functionally superior to existing models. By capitalizing on the strengths of both ALO and GWO, our approach achieves superior performance metrics in comparison to recently proposed methods for maximizing backhaul-effect and maintaining optimal cell sizes. The preliminary results reveal a remarkable 8.3 % reduction in bit error rate (BER), 4.9 % reduction in energy consumption, 8.5 % increase in throughput, and 4.5 % reduction in communication delay. The achieved results demonstrate the revolutionary potential of our 5G network optimization approach and pave the way for future research and advancements in the field for different scenarios. These enhancements will revolutionize optical communication networks in order to accommodate the requirements of 5G, IoT, and other contemporary applications.
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来源期刊
Journal of Optical Communications
Journal of Optical Communications Engineering-Electrical and Electronic Engineering
CiteScore
2.90
自引率
0.00%
发文量
86
期刊介绍: This is the journal for all scientists working in optical communications. Journal of Optical Communications was the first international publication covering all fields of optical communications with guided waves. It is the aim of the journal to serve all scientists engaged in optical communications as a comprehensive journal tailored to their needs and as a forum for their publications. The journal focuses on the main fields in optical communications
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