Performance Optimization of Greedy and FIFO Algorithm In Vehicle to Vehicle (V2V) Communication

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.