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

Area of Science:

• Wireless communication networks
• 5G technology
• Multi-input Multi-output (MIMO) systems

Background:

• Resource sharing is crucial for managing traffic congestion in wireless networks.
• Multi-input Multi-output (MIMO) advancements in 5G necessitate efficient resource allocation across cells.
• Optimizing network coverage, capacity, and quality of service is a key challenge.

Purpose of the Study:

• To present a novel load-based resource-sharing framework for multi-cell MIMO systems.
• To dynamically allocate network resources based on channel-loading data.
• To effectively address traffic overload in 5G networks.

Main Methods:

• Development of a load-based resource-sharing (LBRS) framework.
• Utilizing channel-loading data from local base stations.
• Dynamic resource allocation among adjacent base stations.

Main Results:

• The LBRS framework achieved high performance metrics: delta-P (90.91%-92.10%), prevalence threshold (89.84%-92.18%), CSI (91.01%-91.65%), and MCC (88.31%-91.27%).
• Demonstrated effective dynamic resource sharing capabilities.
• Significantly improved overall network performance.

Conclusions:

• The proposed load-based resource-sharing framework effectively enhances dynamic resource allocation in multi-cell MIMO 5G networks.
• The framework successfully alleviates traffic congestion and optimizes network performance.
• This approach offers a cost-effective solution for managing wireless network resources.