Performance Optimization of Greedy and FIFO Algorithm In Vehicle to Vehicle (V2V) Communication
DOI:
https://doi.org/10.25124/cepat.v3i02.8031Abstract
In the era of autonomous vehicles, Vehicle-to-Vehicle (V2V) communication
is crucial for enhancing traffic efficiency. This study adheres to the standards
of 3GPP TS 22.185, TS 22.186, TS 22.885, and TS 22.886 to support V2X
communication in 5G networks. We evaluated the resource allocation
algorithms FIFO and Greedy, using both clustering and non-clustering
approaches. The test results indicate that the Greedy algorithm with
clustering outperforms FIFO. In the first scenario, Greedy with clustering
improves 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 an
increase 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 the
Greedy algorithm with clustering for optimizing radio resource allocation
performance in V2V communication, as it demonstrates higher values and
performance improvements compared to the FIFO algorithm with clustering.
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Copyright (c) 2025 Muhammad Raditya 'Aisy Dharmawan, Muhammad Satrio Dwi Cahaya, Raffie Ilham Winata, Linda Meylani, Vinsensius Sighit Widhi Prabowo
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