Optical communication enhanced IDMBOC for maximizing backhaul-effect & maintaining optimum cell sizes

Kanchan Mankar; Suchita Varade

doi:10.1515/joc-2024-0035

Article

Optical communication enhanced IDMBOC for maximizing backhaul-effect & maintaining optimum cell sizes

Kanchan Mankar and Suchita Varade

Published/Copyright: March 18, 2024

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From the journal Journal of Optical Communications Volume 46 Issue 2

Abstract

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.

Keywords: optical communication; 5G networks; backhaul-effect maximization; metaheuristic optimization; ant lion optimization; grey wolf optimization

Corresponding author: Kanchan Mankar, 210930 Priyadarshini College of Engineering , Nagpur, MS, India, E-mail: kanchankhope@gmail.com

Research ethics: This article does not contain any studies with human participants or animals performed by any of the author.
Author contributions: All authors contributed equally.
Competing interests: The authors have no relevant financial or nonfinancial interests to disclose. They declare no conflicts of interest in relation to this article.
Research funding: Not declared.
Data availability: Data sharing is not applicable to this article as no new data were created or analysed in this study.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/joc-2024-0035).

Received: 2024-01-31

Accepted: 2024-02-24

Published Online: 2024-03-18

Published in Print: 2025-04-28

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Supplementary Material

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Keywords for this article

optical communication; 5G networks; backhaul-effect maximization; metaheuristic optimization; ant lion optimization; grey wolf optimization