Control Factor Based Two Step LMS Algorithm for Channel Tracking and Impulse Noise Mitigation

• Published in: 2021 5th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT) pp. 1 - 6
• Main Authors: Kumar, Mithun, Yasmin, Rubaiyat
• Format: Conference Proceeding
• Language: English
• Published: IEEE 18.11.2021
• Subjects: Adaptive algorithms; Adaptive Filter; AWGN Channel; Convergence; Filtering; Filtering algorithms; GLMS; Impulse Noise; Mean square error methods; MGLMS; MSE; Noise reduction; Order Statistics; Signal processing algorithms; Wireless communication
• DOI: 10.1109/ICEEICT53905.2021.9667869

Fast deployment of wireless communication addresses various aspects of digital signal processing issues for noise reduction. Adaptive filtering is an efficient technique to reduce noise for both the stationary and time-varying environment. In this paper, we consider the design of an adaptive algorithm where the goal is to improve the performance of the conventional LMS based modified adaptive algorithms. The performance of the LMS algorithm is good enough for a stationary environment but not for the nonstationary environment. We tried to propose an adaptive algorithm which can achieve faster convergence, minimum MSE and suitable in both the stationary and time-varying environment. We introduce a new parameter termed as control factor for the MGLMS algorithm that controls the convergence and provides minimum mean square error as well as the stability of the algorithm. The variable step size adjustment approach with control factor that improves the performance of MGLMS algorithm. Simulation results outperform the conventional LMS and MGLMS algorithm. Results show that the convergence and MSE level is better. We concentrated on impulse noise mitigation also. We proposed Order Statistics based method to mitigate impulse noise very effectively. Our simulated result shows that the method provides better performance for impulse noise suppression.