Performance evaluation of MIMO systems in a mixture of Gaussian noise and impulsive noise

Most of the analyses of multiple-input multiple-output (MIMO) systems so far have been based on the ideal Gaussian noise model. In this paper, performance analysis of MIMO systems is performed in a mixture of Gaussian noise and impulsive noise modeled as a symmetric alpha stable process. Three typical MIMO systems are considered: 1) zero-forcing (ZF) system, 2) maximum likelihood (ML) system and 3) space time block coding (STBC) system. The symbol-error-rates (SER) or the upper bound of SER of each system is derived. Simulations are performed in the mixed noise with different impulsive intensity and impulsive level and the results show that the performances of all the systems are degraded greatly in the mixed noise and STBC has no performance gain over ZF and ML when high impulsive noise appears.