Citation

Pauzi, Muhammad Zaim Mohd and Thiagarajah, Siva Priya and Nila, Farzana Sharmin and Dwijaksara, Made Harta (2025) An Enhanced Load-Adaptive Greedy-Based Algorithm for Carrier Selection Efficiency in 5G-NR/4G-LTE Hetnets. In: 17th IEEE Malaysia International Conference on Communication, MICC 2025, 27 August 2025 - 28 August 2025, Melaka, Malaysia.

Text An Enhanced Load-Adaptive Greedy-Based Algorithm for Carrier Selection Efficiency in 5G-NR_4G-LTE Hetnets.pdf - Published Version Restricted to Repository staff only Download (403kB)

Abstract

This paper proposes a demand-aware component carrier selection (CCS) algorithm, called Load-Adaptive Carrier Selection (LACS), for 5G-NR/4G-LTE heterogeneous networks. LACS integrates greedy optimization with a lightweight neural network structure to allocate carriers based on individual user throughput requirements. Unlike traditional data rate-greedy approaches that maximize throughput without considering user demand, LACS ensures fair, efficient, and scalable resource allocation across users. In evaluations, LACS achieved 100% user satisfaction across both 4G and 5G scenarios, compared to 71.67% and 76.67% respectively using baseline strategies. Additionally, it reduced the average throughput overshoot by approximately 10 Mbps (4G) and nearly 90 Mbps (5G) compared to data rate-greedy (DRG) allocation, thus minimizing resource waste. These findings highlight LACS as a suitable CCS method for dense network deployments and mission-critical applications

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Neural network-based optimization, resource allocation
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	22 Dec 2025 02:12
Last Modified:	26 Dec 2025 03:00
URII:	http://shdl.mmu.edu.my/id/eprint/15082

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