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Interference Management Based on Meta-Heuristic Algorithms in 5G Device-to-Device Communications

Authors :
Mohamed Kamel Benbraika
Okba Kraa
Yassine Himeur
Khaled Telli
Shadi Atalla
Wathiq Mansoor
Source :
Computers, Vol 13, Iss 2, p 44 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Device-to-Device (D2D) communication is an emerging technology that is vital for the future of cellular networks, including 5G and beyond. Its potential lies in enhancing system throughput, offloading the network core, and improving spectral efficiency. Therefore, optimizing resource and power allocation to reduce co-channel interference is crucial for harnessing these benefits. In this paper, we conduct a comparative study of meta-heuristic algorithms, employing Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Bee Life Algorithm (BLA), and a novel combination of matching techniques with BLA for joint channel and power allocation optimization. The simulation results highlight the effectiveness of bio-inspired algorithms in addressing these challenges. Moreover, the proposed amalgamation of the matching algorithm with BLA outperforms other meta-heuristic algorithms, namely, PSO, BLA, and GA, in terms of throughput, convergence speed, and achieving practical solutions.

Details

Language :
English
ISSN :
2073431X
Volume :
13
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Computers
Publication Type :
Academic Journal
Accession number :
edsdoj.8aa0944d1f445a5b2bb5376a5d9c749
Document Type :
article
Full Text :
https://doi.org/10.3390/computers13020044