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Distributed Multichannel Active Noise Control with Asynchronous Communication

Junwei Ji, Dongyuan Shi, Boxiang Wang, Ziyi Yang, Haowen Li, Woon-Seng Gan

TL;DR

The paper tackles the high communication burden in distributed multichannel active noise control by introducing an asynchronous framework (ACDMCANC) where each node runs a weight-constrained FxLMS and exchanges weight differences only when local performance degrades. ACDMCANC uses a center point and a mixed weight difference fusion to integrate information asynchronously, improving scalability in heterogeneous networks. The approach combines weight-constrained updates with on-demand inter-node communication and compensation filters, achieving a favorable balance between noise reduction performance and communication load, as demonstrated by broadband and real-noise simulations. This yields a robust, scalable DMCANC paradigm suitable for practical deployments with variable network conditions, and code is provided for reproducibility.

Abstract

Distributed multichannel active noise control (DMCANC) offers effective noise reduction across large spatial areas by distributing the computational load of centralized control to multiple low-cost nodes. Conventional DMCANC methods, however, typically assume synchronous communication and require frequent data exchange, resulting in high communication overhead. To enhance efficiency and adaptability, this work proposes an asynchronous communication strategy where each node executes a weight-constrained filtered-x LMS (WCFxLMS) algorithm and independently requests communication only when its local noise reduction performance degrades. Upon request, other nodes transmit the weight difference between their local control filter and the center point in WCFxLMS, which are then integrated to update both the control filter and the center point. This design enables nodes to operate asynchronously while preserving cooperative behavior. Simulation results demonstrate that the proposed asynchronous communication DMCANC (ACDMCANC) system maintains effective noise reduction with significantly reduced communication load, offering improved scalability for heterogeneous networks.

Distributed Multichannel Active Noise Control with Asynchronous Communication

TL;DR

The paper tackles the high communication burden in distributed multichannel active noise control by introducing an asynchronous framework (ACDMCANC) where each node runs a weight-constrained FxLMS and exchanges weight differences only when local performance degrades. ACDMCANC uses a center point and a mixed weight difference fusion to integrate information asynchronously, improving scalability in heterogeneous networks. The approach combines weight-constrained updates with on-demand inter-node communication and compensation filters, achieving a favorable balance between noise reduction performance and communication load, as demonstrated by broadband and real-noise simulations. This yields a robust, scalable DMCANC paradigm suitable for practical deployments with variable network conditions, and code is provided for reproducibility.

Abstract

Distributed multichannel active noise control (DMCANC) offers effective noise reduction across large spatial areas by distributing the computational load of centralized control to multiple low-cost nodes. Conventional DMCANC methods, however, typically assume synchronous communication and require frequent data exchange, resulting in high communication overhead. To enhance efficiency and adaptability, this work proposes an asynchronous communication strategy where each node executes a weight-constrained filtered-x LMS (WCFxLMS) algorithm and independently requests communication only when its local noise reduction performance degrades. Upon request, other nodes transmit the weight difference between their local control filter and the center point in WCFxLMS, which are then integrated to update both the control filter and the center point. This design enables nodes to operate asynchronously while preserving cooperative behavior. Simulation results demonstrate that the proposed asynchronous communication DMCANC (ACDMCANC) system maintains effective noise reduction with significantly reduced communication load, offering improved scalability for heterogeneous networks.
Paper Structure (9 sections, 15 equations, 4 figures)

This paper contains 9 sections, 15 equations, 4 figures.

Table of Contents

  1. Introduction
  2. Distributed MCANC System
  3. Asynchronous communication DMCANC
  4. Weight-constrained FxLMS
  5. Asynchronous communication strategy
  6. Numerical simulations
  7. Broadband noise reduction performance
  8. Real recorded noise reduction performance
  9. Conclusion

Figures (4)

  • Figure 1: A DMCANC network, where each node consists of a secondary source, an error microphone, and an ANC controller for communication and processing, and shares one reference microphone.
  • Figure 2: The block diagram of the $k$th node for the proposed ACDMCANC system, where $P_k(z)$ represents the primary path. $\gamma_k(n)$ is the interference caused by the other nodes, resulting in crosstalk between nodes Ji2025SBWCFXLMS.
  • Figure 3: Noise reduction performance for broadband noise using different algorithms: (a). ANSE comparison of various MCANC algorithms. (b) illustrate the communication instances of Node 1 and Node 2 in the ACDMCANC system, respectively, where “Off” indicates no communication and “On” denotes a communication request.
  • Figure 4: Noise reduction performance for real recorded compressor noise using different algorithms: (a). ANSE comparison of various MCANC algorithms; (b) Power spectrum comparison of various MCANC algorithms