Hardware Reduction in Cascaded LMS Adaptive Filter for Noise Cancellation Using Feedback

The present work investigates the innovative concept of adaptive noise cancellation (ANC) using feedback connection of least-mean-square (LMS) adaptive filters for the sake of hardware reduction. The concept of cascading and feedback for real-time LMS-ANC are also described. The simulation model gives variation in the distinct signals of LMS-ANC like error signal, output signal and weights at various LMS filter parameters. An attempt has been made to provide solution in order to improve the performance of cascaded LMS adaptive noise canceller in terms of filter parameters. The results are obtained with the help of adaptive algorithm and feedback structure algorithm of LMS-ANC with different filter lengths and step sizes which provide high convergence speed of error signal. The signal-to-noise ratio for closed-loop LMS-ANC was found to be higher than single LMS-ANC system and equivalent to cascaded LMS-ANC. The novelty of the proposed model lies in reduction in hardware and low instantaneous power consumption making the model cost-effective as well as less complicated as compare to cascaded LMS-ANC.