Robust Maximum Likelihood Algorithm-based Mitigation technique for impulsive noise in MIMO-OFDM systems

Abstract

Non-Gaussian impulsive noise impacts the equalizers and signal detectors directly in the wireless system. The major problem in the multiple-input multiple-output (MIMO)-related applications is the blind source equalization and separation, where the users transmit multiple digital signals in a linear channel that is received using the array of antennas. The noise in the received signals is impulsive in nature, which is mitigated in the research by implementing the Robust Maximum Likelihood Algorithm (RMLA) for handling the degradation of the performance in the wireless system. The constant modulus cost function formulated using RMLA is used for modeling the equalizer to adaptively suppress the influence of the impulsive noise. The effectiveness of the proposed RMLA based impulse noise mitigation is evaluated based on the evaluation metrics, such as Bit Error Rate (BER), Mean Square Error (MSE), and Symbol Error Rate (SER) corresponding to the Signal-to-Noise Ratio (SNR) and dissimilar antenna array size. The proposed RMLA based BE method provided minimum BER values of 0.0021, 0.0044, 0.0142, and minimum MSE value of 0.0006, 0.0012, and 0.0037 with the Rayleigh channel, minimum BER values of 0.0006, 0.0012, and 0.0013, and minimum MSE value of 0.0003 with the Rician channel.