Proposed Architecture and Mathematical Model to Enhance Interference Management in ۵G-Enabled M۲M Networks

Publish Year: 1404
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:

JR_IJIEN-5-1_003

تاریخ نمایه سازی: 11 مرداد 1404

Abstract:

The growing number of connected devices has led to a significant shift in cellular standards, particularly with the Long-Term Evolution (LTE) framework. The fifth-generation (۵G) standard supports several innovative mobile technologies, including Machine-to-Machine (M۲M) communication and Device-to-Device (D۲D) communication, enabling a vast network of interconnected intelligent devices. In Nigeria's power system, the deployment of M۲M devices within the smart grid has introduced new challenges in resource allocation and interference management. The interference caused by reduced inter-cell distances and the seamless integration of heterogeneous devices into the ۵G cellular network leads to a decline in Quality of Service (QoS) and overall network performance. In this paper, we propose an interference-aware architecture for Machine-to-Machine (M۲M) communication within a smart grid. This architecture aims to mitigate the interference caused by the localization of M۲M devices on the grid. Additionally, we will mathematically model the proposed interference mitigation scheme as a multi-objective particle swarm optimization problem, taking into account the complexity of the fitness function and the trade-offs between different particles. As a result of this approach, the interference generated by M۲M devices will decrease significantly. Consequently, we expect to achieve a balance between the optimal separation distance of M۲M devices and improved network performance.The growing number of connected devices has led to a significant shift in cellular standards, particularly with the Long-Term Evolution (LTE) framework. The fifth-generation (۵G) standard supports several innovative mobile technologies, including Machine-to-Machine (M۲M) communication and Device-to-Device (D۲D) communication, enabling a vast network of interconnected intelligent devices. In Nigeria's power system, the deployment of M۲M devices within the smart grid has introduced new challenges in resource allocation and interference management. The interference caused by reduced inter-cell distances and the seamless integration of heterogeneous devices into the ۵G cellular network leads to a decline in Quality of Service (QoS) and overall network performance. In this paper, we propose an interference-aware architecture for Machine-to-Machine (M۲M) communication within a smart grid. This architecture aims to mitigate the interference caused by the localization of M۲M devices on the grid. Additionally, we will mathematically model the proposed interference mitigation scheme as a multi-objective particle swarm optimization problem, taking into account the complexity of the fitness function and the trade-offs between different particles. As a result of this approach, the interference generated by M۲M devices will decrease significantly. Consequently, we expect to achieve a balance between the optimal separation distance of M۲M devices and improved network performance.

Keywords:

۵G Network , SINR , , Throughput , Interference Mitigation , Machine-to-Machine (M۲M) , Multi-Objective Particle Swarm Optimisation (MOPSO) , Smart Grid

Authors

Ahmed Danasabe Suleiman *

Department of Computer Engineering, Federal Polytechnic Ilaro, Ogun State. Nigeria

Mohammed Abubakar Sadiq

Department of Telecommunications Engineering, Federal University of Technology Minna, Niger State Nigeria

Salihu Bala Alhaji

Department of Computer Engineering, Federal University of Technology Minna, Niger State Nigeria

Micheal David

Department of Telecommunications Engineering, Federal University of Technology Minna, Niger State Nigeria

Ibrahim Abdullahi

Department of Computer Engineering, Federal University of Technology Minna, Niger State Nigeria

Emphraim Micheal

Department of Research and Development, Aeronautics and Aerial Vehicle Development Institute. Kaduna State Nigeria

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