Modeling Intelligent Wireless Communication Channel for 5G and Beyond using Advanced Machine Learning Techniques

In this world of intelligent technologies era, every application of technologies uses artificial intelligence. A new generation of wireless communication is exploring a lot of use cases for continuing the effective transmission of information through the noisy wireless channel. For that, channel modeling is essential to study the characteristics of propagation of signal. But, the present 5G and next generation wireless communication channel is to operate in very high frequencies for higher bandwidth to transmit vast amount of data for a real time experience. Existing channel models will not be valid, hence there is a need for an accurate radio propagation model with fast computation of channel parameters. In the 3GPP channel modeling requirements, the new channel model must support large antenna arrays and be suitable for multi-band operations. Also, it must help large channel bandwidth with mobility for different scenarios. So, the only way is to include the intelligence using advanced machine learning techniques with the data sets of the particular channel environment. In the learning process, using the available data, it can be trained up to understand the environment and available data type by extracting features. In this research work, the gaussian channel is simulated to predict the transmitted data with high accuracy. It is compared with the different machine learning algorithms to find the suitable channel model for a particular propagation path.