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

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.