Abstract

The performance of a DVBT2 system is affected by a set of parameters, and choosing these parameters is very difficult for anyone, even an expert. In this paper, Genetic algorithm is used to find the optimal set of parameters which is: constellation, No. of forward error correction FEC blocks, code rate, samples per frame and signal to noise ratio SNR for different types of fading channels. The number of Generations and individuals is 100. The goal of this work is to enhance the system performance by achieving a trade of between BER and throughput with the lowest possible SNR and iterations. An online supercomputer platform was used to run the MATLAB simulation of the suggested system, which was conducted using MATLAB R2021a. The results shows a clear improvement of the system performance and a BER of less than 10-5 is obtained. The influence of population size on the GA performance is also investigated, population sizes between 50 and 200 are tested. The results shows that reaching the optimal solution with the least possible number of iterations is achieved when the population size is 200 while poor results are obtained when the population size is 50. Thus, we have a system capable of finding the optimal set of parameters that most affected on it by using genetic algorithm GA and the population size of 200 with the least possible number of iterations.