Caecilia Vashti Faustina
Telkom University

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Auction-based Radio Resource Allocation Algorithm Using Clustering Method Zahra Amanda; Caecilia Vashti Faustina; Jestisa Okviana Reban; Linda Meylani; Vinsensius Sigit Widhi Prabowo
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 5 No 02 (2026): November 2026
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v5i02.9215

Abstract

Telecommunication technology has advanced significantly in terms of device connectivity and data transmission speeds. However, the increasing number of subscribers is expected to strain service quality, leading to communication traffic congestion. The aim of this research is to allocate resource blocks using auction algorithms within the K-Means clustering model. Additionally, this research aims to evaluate the performance of K-Means clustering in enhancing Energy Efficiency (EE) and Quality of Service (QoS). In the comparison between auction and round-robin algorithms, the auction algorithm excels in various parameters compared to round-robin. The auction algorithm, which considers user bids for resource allocation, achieves a more balanced and efficient distribution than round-robin. The Auction K-Means Clustering algorithm demonstrates the best performance in resource block (RB) allocation in telecommunication networks. The Auction K-Means Clustering algorithm achieves an average user capacity of bps, total capacity of bps, power efficiency of bps/Watt, and fairness with a score of 52.69%. These advantages make Auction K-Means Clustering more effective in maximizing overall system performance.