Visible to the public Distributed Adaptive Acoustic Contrast Control for Node-specific Sound Zoning in a Wireless Acoustic Sensor and Actuator Network

TitleDistributed Adaptive Acoustic Contrast Control for Node-specific Sound Zoning in a Wireless Acoustic Sensor and Actuator Network
Publication TypeConference Paper
Year of Publication2021
AuthorsVan Rompaey, Robbe, Moonen, Marc
Conference Name2020 28th European Signal Processing Conference (EUSIPCO)
Date Publishedjan
KeywordsAcoustic Contrast Control, acoustic coupling, Acoustics, actuators, Computer simulation, Eigenvalues and eigenfunctions, Generalized Eigenvalue Decomposition (GEVD), Human Behavior, pubcrawl, Resiliency, Scalability, Signal processing algorithms, Sound Zoning, Wireless communication, Wireless Sensor and Actuator Network (WASAN), Wireless Sensor Network, Wireless sensor networks
AbstractThis paper presents a distributed adaptive algorithm for node-specific sound zoning in a wireless acoustic sensor and actuator network (WASAN), based on a network-wide acoustic contrast control (ACC) method. The goal of the ACC method is to simultaneously create node-specific zones with high signal power (bright zones) while minimizing power leakage in other node-specific zones (dark zones). To obtain this, a network-wide objective involving the acoustic coupling between all the loudspeakers and microphones in the WASAN is proposed where the optimal solution is based on a centralized generalized eigenvalue decomposition (GEVD). To allow for distributed processing, a gradient based GEVD algorithm is first proposed that minimizes the same objective. This algorithm can then be modified to allow for a fully distributed implementation, involving in-network summations and simple local processing. The algorithm is referred to as the distributed adaptive gradient based ACC algorithm (DAGACC). The proposed algorithm outperforms the non-cooperative distributed solution after only a few iterations and converges to the centralized solution, as illustrated by computer simulations.
DOI10.23919/Eusipco47968.2020.9287771
Citation Keyvan_rompaey_distributed_2021