Implementation Least Means Square Algorithm for Real-Time Active Noise Cancellation on FPGA

Noise cancellation is a common practice in audio signal processing that involves adaptive digital filter to achieve a clean audio signal. This paper presents the implementation of Least Means Squared (LMS) algorithm for real-time Active Noise Cancellation (ANC) by considering the surrounding sound signal that contains noise. This method was chosen to improve the output sound without damaging original sound using LMS adaptive digital filter by decreasing noise in decibel value. This work has been accomplished by the design and analyzes of LMS adaptive filter implemented on both MATLAB and Field Programmable Gate Array (FPGA). The design approach is done by developing the algorithm in MATLAB Simulink, then applied on FPGA hardware platform, Cyclone IV EP4CE115F29C7 board using Intel Quartus Prime development platform for simulation. Three major demonstrable hardware applications presented in this work are the real-time sound filter, ANC and sound measurement in decibel. Based on the standard sound level, 85dB(A) and not more than 115dB(A) was chosen for result analysis between filtered and unfiltered sound. In a comparison of three genre songs implementing the real-time ANC system containing LMS filter, the hardware implementation able to reduce the sound level at the range of 15.56% to 20.58%.