High-Performance Hardware Design of Block LMS Adaptive Noise Canceller for In-Ear Headphones

Mohd Tasleem Khan, Rafi Ahamed Shaik

Research output: Contribution to specialist publicationArticle

11 Citations (Scopus)

Abstract

This article presents a high-performance hardware design of block least mean square adaptive noise canceller (ANC) for in-ear headphones applications. It is based on distributed arithmetic, which stores filter partial products in look-up table (LUT). The proposed technique splits LUTs into two smaller LUTs and stores the filter partial products in offset-binary-coding form. Furthermore, the splitted LUTs are shared to compute the filter output and coefficient-increment terms. A novel strategy is also presented to update LUT contents. Compared with the best existing design, the proposed ANC for 32nd filter order requires 50% less LUT words, 5.31% less adders, 28.57% high-throughput, and relatively less critical path-delay. From the implementation results, it is found that the logic utilization of the proposed design is significantly reduced while achieving better noise cancelling performance. For example, the proposed ANC for 32nd filter order provides noise reduction of about 6-20 dB and utilizes 1.80 times less LUTs and 1.71 times less flip-flops over the best existing design.

Original languageEnglish
Pages105-113
Number of pages9
Volume9
No.3
Specialist publicationIEEE Consumer Electronics Magazine
DOIs
Publication statusPublished - May 2020

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'High-Performance Hardware Design of Block LMS Adaptive Noise Canceller for In-Ear Headphones'. Together they form a unique fingerprint.

Cite this