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Active noise control incorporating external wireless acoustic sensors
De Hu1, Yanrong He1, Qingying Zhao1
1College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia 010021, China.
The Journal of the Acoustical Society of America
|August 11, 2026
Summary
This study introduces active noise control (ANC) using wireless acoustic sensors (WASs). The method accounts for communication delays, enabling real-time noise reduction and selecting optimal sensors for improved performance.
Area of Science:
- Acoustics
- Signal Processing
- Wireless Communications
Background:
- Ubiquitous wireless devices with acoustic sensors offer potential for enhanced spatial sampling in active noise control (ANC).
- Conventional ANC systems often neglect communication and propagation delays inherent in external sensor networks.
- Integrating wireless acoustic sensors (WASs) into ANC requires novel filter designs that address these temporal discrepancies.
Purpose of the Study:
- To introduce and validate an ANC system that effectively utilizes external WASs.
- To develop filter design methodologies that explicitly account for communication delays in WAS signals.
- To analyze the impact of delays on WAS contribution and identify optimal sensor selection strategies for computational efficiency.
Main Methods:
- Design of ANC filters considering communication delays, minimizing error signal power while zeroing out-of-time coefficients.
- Derivation of both optimal filters (theoretical performance bounds) and adaptive filters (real-time application).
- Analysis of theoretical performance gain from WASs, including the effects of communication and acoustic propagation delays, to select the most informative sensors.
Main Results:
- The proposed method enables real-time noise reduction by incorporating WASs into ANC systems.
- Optimal and adaptive filters were derived, demonstrating theoretical performance limits and practical noise reduction capabilities.
- Identification of informative WASs based on delay analysis improved computational efficiency and system performance.
- Simulations and real-world experiments confirmed the validity of the developed methods.
Conclusions:
- The integration of WASs with novel delay-aware filter designs significantly enhances ANC capabilities.
- The proposed approach provides a robust framework for real-time noise control using distributed wireless sensors.
- Sensor selection based on delay analysis is crucial for maximizing performance and computational efficiency in WAS-based ANC systems.