Effectiveness of Vehicular Communication Using NP-CSMA with Bernoulli-Based Gaussian Interpolation Function

Abstract

The objective is to investigate the effectiveness of Gaussian arrival and its effect on vehicular communication compared to Bernoulli's arrival. MATLAB simulation covers three different levels of slot probability: low, medium, and high. The goal behind such simulation is to establish the importance of an adaptive function such as Gaussian interpolation resulting in smoother control of vehicular communication with better channel performance when compared to Bernoulli. This work shows that at low slot probability (Pslot), Gaussian arrival results in a much higher throughput (S) compared to Bernoulli, with a gradual reduction in throughput as Gaussian spread (γ) increases. The decrease in S as γ increases is due to the Gaussian interpolation, which performs control and results in higher channel stability. At mid probability, the simulation and analysis show a convergence between Gaussian results and Bernoulli, with differences in buffered frames (Btotal) as a function of γ. At a high Pslot value, Bernoulli produces higher S than Gaussian, with the closest Gaussian values at γ=2. However, the number of buffered frames using Bernoulli arrival is much higher than Gaussian. The exceedingly high Btotal can result in more collisions, which Gaussian arrival controls very well with a small sacrifice in throughput. The shape function for Bernoulli is shown to be different from Gaussian, except for specific values of γ, where there is a match. The obtained results show the adaptability and smoothness in which Gaussian arrival can optimize channel communication using Non-Persistent CSMA, which enables intelligent vehicular communication.