Hardware Co-Simulation of Adaptive Noise Cancellation System using LMS and Leaky LMS Algorithms

• Published in: 2019 4th International Conference on Internet of Things Smart Innovation and Usages (IoT SIU) pp. 1 - 6
• Main Authors: Gupta, Deepak Kumar, Gupta, Vjiay Kumar, Chandra, Mahesh, Mishra, A. N., Srivastava, Praween Kumar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2019
• Subjects: Adaptive Filter; Adaptive filters; Adaptive Noise Cancellation (ANC); Convergence; Field Programmable Gate Array (FPGA); Filtering algorithms; Hardware; Least Mean Square (LMS); Mathematical model; Mean Square Error (MSE); Noise cancellation; Signal to noise ratio; Signal to Noise Ratio (SNR); Xilinx System Generator (XSG)
• DOI: 10.1109/IoT-SIU.2019.8777658

This paper presents the Adaptive filtering technique used for audio quality enhancement by minimizing noise present into the speech signal. Here, the adaptive noise cancellation system is implemented on FPGA using Xilinx system generator (XSG). The two basic adaptive algorithms least mean square (LMS) and Leaky least mean square (LLMS) has been implemented to minimize the noise present into the speech signal. Various performance parameters used in ANC system design have been analyzed and compared. These parameters are SNR improvement, Mean Square Error (MSE), convergence behavior and hardware resources utilization. Result shows that LLMS algorithm performed best compared to LMS algorithm at the cost of hardware resource utilization.