Neural network based receiver diversity combination for high-fadng channels

Abstract

In today’s modern world, many improvements and developments in Wireless Networks have brought changes in the convenience of people’s life. In this paper, we are proposing a new method on the topic of receiver diversity combining. Selection diversity, maximal ratio combining, equal gain combining, and switched diversity are existing methods for space diversity techniques. We have used various neural network models to predict the received message based on the received signals in multi-receiver environments, therefore, proposing a new method for space diversity combination. Comparisons with the existing methods are done in Python through simulations