MSE Analysis of Bi-scale LMS Used for Narrowband Interference Cancellation

• Published in: 2020 IEEE Latin-American Conference on Communications (LATINCOM) pp. 1 - 6
• Main Authors: Roy, Tamoghna, Ikuma, Takeshi, Louis Beex, A. A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 18.11.2020
• Subjects: Bi-scale NLMS algorithm; Equalizers; Interference Mitigation; Least Mean Square Algorithm; Mean Square Error Estimate; Mean square error methods; Narrowband; Non-Wiener Characteristics; Prediction algorithms; Predictive models; Simulation; Wiener filters
• DOI: 10.1109/LATINCOM50620.2020.9282346

Adaptive LMS (Least Mean Square) equalizers are widely used in digital communication systems for their simplicity of implementation. Conventional adaptive filtering theory suggests that the upper bound on performance of such an equalizer is determined by the performance of a Wiener filter of the same structure. However, in the presence of a narrowband interferer the performance of the (normalized) LMS equalizer can be better than that of its Wiener counterpart. The Bi-scale NLMS (BLMS) algorithm enhances this NLMS (Normalized LMS) characteristic by simultaneously using two instantiations of NLMS that run at very different time scales. In this paper, the derivation of a predictive model for the MSE (Mean Square Error) performance of the BLMS equalizer as narrowband interference canceler is shown. The predictive model can be used to adjust canceler parameters on the fly without the delay needed for time-consuming simulations. Simulation results validate the proposed MSE model, which is shown to predict performance of the BLMS equalizer over a wide range of parameters.