Distributed pressure matching strategy using diffusion adaptation

TL;DR

This paper introduces a distributed pressure-matching strategy using diffusion adaptation to reduce computational complexity in personal sound zone systems, enabling decentralized processing based on local information exchange.

Contribution

It proposes a novel distributed pressure-matching method with diffusion adaptation for PSZ systems, reducing reliance on centralized acoustic transfer function processing.

Findings

The distributed method achieves comparable performance to centralized approaches.

Simulation results demonstrate reduced computational complexity.

The approach effectively spreads the computational load across nodes.

Abstract

Personal sound zone (PSZ) systems, which aim to create listening (bright) and silent (dark) zones in neighboring regions of space, are often based on time-varying acoustics. Conventional adaptive-based methods for handling PSZ tasks suffer from the collection and processing of acoustic transfer functions~(ATFs) between all the matching microphones and all the loudspeakers in a centralized manner, resulting in high calculation complexity and costly accuracy requirements. This paper presents a distributed pressure-matching (PM) method relying on diffusion adaptation (DPM-D) to spread the computational load amongst nodes in order to overcome these issues. The global PM problem is defined as a sum of local costs, and the diffusion adaption approach is then used to create a distributed solution that just needs local information exchanges. Simulations over multi-frequency bins and a computational complexity analysis are conducted to evaluate the properties of the algorithm and to compare it with centralized counterparts.