# An enhanced performance analysis of load based resource sharing framework for MIMO systems in 5G communication systems

## TL;DR

This paper introduces a new load-based resource-sharing framework for 5G MIMO systems to improve network performance and reduce traffic congestion.

## Contribution

The paper proposes a novel load-based resource-sharing framework for multi-cell MIMO systems in 5G networks.

## Key findings

- The proposed framework achieved high performance metrics like 90.91% delta-P and 91.27% Mathew’s correlation coefficient at terminal access.
- At resource transmission, the system recorded 92.10% delta-P and 92.18% prevalence threshold, showing effective dynamic resource sharing.
- Simulation results confirm the framework significantly enhances network performance in 5G systems.

## Abstract

Resource sharing serves as a cost-effective and dynamically adjustable method for alleviating traffic congestion in wireless networks. Advancements in multi-input multi-output (MIMO) technologies for 5G communication systems have led to the exploration of resource sharing across various cells or sectors. This approach aims to optimise network performance, focussing on coverage, capacity, and quality of service. This document presents a new load-based resource-sharing framework designed for multi-cell MIMO systems. The proposed framework utilises channel-loading data from local base stations and dynamically allocates available resources among adjacent base stations. The proposed framework facilitates dynamic resource sharing, effectively addressing traffic overload in 5G networks. The proposed LBRS achieved a delta-P value of 90.91%, a prevalence threshold value of 89.84%, a critical success index value of 91.01%, and a Mathew’s correlation coefficient value of 91.27% at the terminal access. At the resource transmission, the system recorded a delta-P value of 92.10%, a prevalence threshold value of 92.18%, a critical success index value of 91.65%, and a Mathew’s correlation coefficient value of 88.31%. The simulation results indicate that the proposed framework effectively enhances dynamic resource sharing, resulting in a notable improvement in network performance.