PRK-Based Scheduling for Predictable Link Reliability in Wireless Networked Sensing and Control

Predictable wireless communication is required for closed-loop sensing and control in many networked cyber-physical systems, yet co-channel interference remains a major source of uncertainty in wireless communication. Integrating the protocol model’s locality and the physical model’s high fi-delity, the physical-ratio-K (PRK) interference model is ex-pected to serve as a foundation for distributed, predictable in-terference control. To realize the potential of the PRKmodel, we design protocol PRKS that addresses the challenges of model instantiation and protocol signaling in PRK-based scheduling. In particular, PRKS uses a control-theoretic ap-proach to instantiating the PRK model, it uses local signal maps to address the challenges of large interference range and anisotropic, asymmetric wireless communication, and it leverages the different timescales of PRK model adapta-tion and data transmission to decouple protocol signaling from data transmission. Through testbed-based measure-ment study, we observe that, unlike existing scheduling pro-tocols where link reliability is unpredictable and the ratio of links whose reliability meets application requirements can be as low as 0%, PRKS enables predictably high link reliabil-ity (e.g., 95%) for all the links in different network and en-vironmental conditions without a priori knowledge of these conditions. Through local distributed coordination, PRKS also achieves a channel spatial reuse very close to what is enabled by the state-of-the-art centralized scheduler while ensuring the required link reliability. Ensuring the required link reliability in PRKS also reduces communication delay and improves network throughput. 1