WINC: A Wireless IoT Network for Multi-Noise Source Cancellation - Janveja, Ishani; Wang, Jiaming; Guan, Junfeng; Jog, Suraj; Hassanieh, Haitham (IPSN'23, 2023)
This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noisecanceling headphones. The IoT microphones forward ambient noise to the headphone over the wireless link which travels a million times faster than sound and gives the headphone a future lookahead into the incoming noise. While leveraging wireless lookahead has been explored in past work, prior systems are limited to a single noise source. WINC, however, can simultaneously cancel multiple noise sources by using a network of IoT nodes. Scaling wireless lookahead aware noise cancellation is non-trivial because the computational and protocol delays can defeat the purpose of leveraging wireless lookahead. WINC introduces a novel algorithm that operates in the frequency domain to efficiently cancel multiple noise sources. We implement and evaluate WINC to show that it can cancel three noise sources and outperforms past work and state-of-the-art headphones without requiring completely blocking the users’ ears.