Robust Signal Detection in Complex Noise and Interference Environment Based on MoG Modeling

The signal detection is a key issue in the Multi-Input Multi-Output (MIMO) system. For the noise and interference environment with Gaussian distribution, many effective signal detection methods have been proposed. In the 5th generation New Radio (5G-NR) system, its high density, high frequency and large bandwidth features may lead to a complex environment (including noise and interference), whose distribution is non-Gaussian. Therefore, the robust signal detection methods in a complex environment need to be studied. The mixture of Gaussian (MoG) distribution has been proven to be able to model the complex environment with any continuous distribution. In this paper, many effective signal detection methods are extended from the assumption of Gaussian distribution to MoG distribution and can better deal with the complex environment. The numerical results confirm the superiorities of our proposed methods.