Title: Convergence analysis of adaptive MSFs used for acoustic echo cancellation

Authors: Alaka Barik; Mihir Narayan Mohanty; Kunal Das

Addresses: Department of Electronics Communication Engineering, ITER, Siksha 'O' Anusandhan University, Bhubaneswar, India ' Department of Electronics Communication Engineering, ITER, Siksha 'O' Anusandhan University, Bhubaneswar, India ' R&D Team, NVIDIA Graphics, Pune, India

Abstract: In the modern era of communication echo cancellation is a major problem. Cancellation of acoustic echo from loudspeaker and microphone coupling is an essential as well as challenging task. Mostly the adaptive filters are used to cancel the echo in the present scenario and many researchers are still working on this area. The LMS algorithm design is used extensively in communication networks to correct for the echoes created by line impedance mismatches and is useful to compensate for the imperfection in telephony networks. This paper shows how the LMS algorithm through multiple sub filter (MSF) is useful to solve echo problems. A large amount of coefficients is required for acoustic echo cancellation for a long path. Similarly lengthy filter results slow convergence. This paper comprises this trade-off using LMS algorithm for the echo cancellation purpose. The proposed algorithm is based upon decomposing a long adaptive filter into smaller sub filters. Simulations results show that the decomposed algorithm shows better than the long adaptive filter.

Keywords: echo cancellation; adaptive algorithm; convergence; mean error; common error; composite error.

DOI: 10.1504/IJICT.2018.090557

International Journal of Information and Communication Technology, 2018 Vol.13 No.2, pp.196 - 207

Received: 06 Dec 2014
Accepted: 17 Jun 2015
Published online: 22 Mar 2018 *

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