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Journal : Journal of Computer Engineering: Progress, Application and Technology

Resource Block Allocation: Performance Comparison of Auction, Greedy, and Round Robin Algorithms Kahyangan, Fortuna; Fakhrudin, Muhammad Harits; Furqan, Revin Abyan; Meylani, Linda; Prabowo, Vinsensius Sigit Widhi
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 5 No 01 (2026): May 2026
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v3i02.8025

Abstract

Heterogeneous Networks (HetNets) that integrate Wi-Fi, 4G, and 5G technologies present significant challenges in resource management and power allocation. This study evaluates the performance of resource block (RB) allocation in a two-level HetNet model consisting of one macro cell base station (MBS) and four small cell base stations (SBS). Utilizing K-Medoids clustering, allocations are analyzed under various conditions using Greedy, Auction, and round robin algorithms. Simulations reveal that the Greedy algorithm outperforms the Auction and round robin algorithms in optimizing data rate, sum rate, spectral efficiency, power efficiency, and fairness. Specifically, the Greedy algorithm achieves an average data rate of 1.642 bps, an average sum rate rate of 1.218 bps, an average spectral efficiency of 3.046 bps/Hz, an average power efficiency of 1.650 bps/W, and an average fairness of 0.329, indicating its effectiveness in improving HetNet performance.
Performance Optimization of Greedy and FIFO Algorithm In Vehicle to Vehicle (V2V) Communication Dharmawan, Muhammad Raditya 'Aisy; Cahaya, Muhammad Satrio Dwi; Winata, Raffie Ilham; Meylani, Linda; Prabowo, Vinsensius Sighit Widhi
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 5 No 01 (2026): May 2026
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v3i02.8031

Abstract

In the era of autonomous vehicles, Vehicle-to-Vehicle (V2V) communicationis crucial for enhancing traffic efficiency. This study adheres to the standardsof 3GPP TS 22.185, TS 22.186, TS 22.885, and TS 22.886 to support V2Xcommunication in 5G networks. We evaluated the resource allocationalgorithms FIFO and Greedy, using both clustering and non-clusteringapproaches. The test results indicate that the Greedy algorithm withclustering outperforms FIFO. In the first scenario, Greedy with clusteringimproves the Total Data Rate by 8.97%, the Average Data Rate by 10.08%,and the Spectral Efficiency by 9.09%. In the second scenario, there is anincrease in the Total Data Rate by 11.07%, the Average Data Rate by 7.91%,and the Spectral Efficiency by 10.57%. This study recommends using theGreedy algorithm with clustering for optimizing radio resource allocationperformance in V2V communication, as it demonstrates higher values andperformance improvements compared to the FIFO algorithm with clustering.