A proportional fair scheduling strategy using multiobjective gradient‐based African buffalo optimization algorithm for effective resource allocation and interference minimization. (25th October 2021)

• Record Type: Journal Article
• Authors: Kesavan, Dhivya; Periyathambi, Ezhumalai; Chokkalingam, Arun
• Other Names: Souri Alireza guestEditor.; Piuri Vincenzo guestEditor.; Shojafar Mohammad guestEditor.; Al‐Masri Eyhab guestEditor.; Kumari Saru guestEditor.
• Is Part Of: International journal of communication systems. Volume 35:Number 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-25
• Subjects: African buffalo optimizer -- D2D -- fairness -- gradient‐based optimizer -- interference -- resource blocks -- user equipment; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.5003
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: The increased usage of Internet of Things (IoT) applications in several areas, like healthcare, agriculture, and business, has aggravated mobile traffic issues to a large extent. The deployment of 5G technology has resulted in increased traffic globally. These coherent devices, on the other hand, use the internet to fine‐tune the quality of service in order to provide scalability, anonymity, and accessibility. Despite its numerous virtues, it is bound to encounter issues with interference management, fairness, throughput, and computational complexities. In this paper, a novel Multi‐Objective Gradient‐based African Buffalo Optimization (MOGABO) algorithm is developed to handle proportional fairness scheduling, improve interference management, increase throughput, and reduce computational complexities in cellular communication systems, particularly device‐to‐device (D2D) communication. The simulation analysis is done against other approaches such as the Hungarian technique, DDDPG technique, heuristic technique, and SC‐FDMA technique demonstrates that this method has improved system fairness over the existing approaches. Our method maximizes throughput, and for 500 UE, the throughput is 10.4 Mbps, with an average queuing delay of 24 ms. As a result, when compared to the existing method, MOGABO method offers a 1.2% increase in throughput. Thus, our method offers better coverage and throughput for D2D cellular communication with the reduction of computational complexities. Abstract : The main aim of this proposed technique is to address the computational challenges that arise as a result of D2D communication in a cellular network. The multiobjective gradient‐based optimization algorithm used in this paper deals with the fair scheduling and interference problems associated with the 5G D2D communication network. The African buffalo optimization algorithm minimizes the real‐time traffic and provides optimal fair scheduling.