Kalman-Based MIMO Receivers Using Gaussian Sum Approximations

Abstract

This paper proposes a new multiple input multiple output receiver based on the Kalman filtering algorithm. The Kalman filtering algorithm is based on the Gaussian assumption of the input signal. However, the assumption is not appropriate for the digital communication system which has non-Gaussian input signal. The proposed receiver overcomes the problem by using multiple Kalman filters and its output is obtained using the weighted sum of the outputs of the Kalman filters by the Gaussian sum approximation method to make the data signal approximately Gaussian. Simulation results show that the bit error rate (BER) performance of the proposed receiver is better than the previous Kalman-based receivers and its BER performance is close to the maximum likelihood (ML) receiver with lower computational complexity than the ML receiver.