Distributed uplink cache for improved energy and spectral efficiency in B5G small cell network.

Area of Science:

• Wireless communication networks
• Data caching strategies
• 5G and beyond (B5G) network architecture

Background:

• Exponential data growth in content-centric and Small Cell Networks (SCN) strains backhaul links.
• Data caching is a key solution for network congestion but faces challenges in distributed B5G uplink scenarios.
• Existing methods struggle with duplicate content, mobile station unawareness, and large file storage.

Purpose of the Study:

• To propose an efficient cache framework for uplink data transmission in distributed B5G SCNs.
• To address challenges of duplicate content, mobile station unawareness, and large content storage.
• To enhance energy and spectrum efficiency in B5G networks.

Main Methods:

• A cache framework that aggregates cache content lists from all Small Base Stations (SBSs) to eliminate duplicates.
• Content matching performed at the Mobile Station (MS) instead of the SBS.
• Segmentation of large content files and distributed storage of fractions to boost cache hit ratio.

Main Results:

• The proposed framework significantly improves energy and spectrum efficiency for both access and core networks.
• Achieved a 41.28% improvement in access network energy efficiency and 15.58% in spectrum efficiency.
• Enhanced cache hit ratio by 9% and throughput by 40.00% compared to existing schemes.

Conclusions:

• The developed cache framework effectively tackles uplink transmission challenges in distributed B5G SCNs.
• The framework offers substantial improvements in network efficiency, cache performance, and throughput.
• This approach provides a viable solution for managing data traffic in next-generation wireless networks.