Joint Interference-Aware Backoff and Load Control for Multi-Channel LPWANs

초록

Low Power Wide Area Networks (LPWANs) operating over unlicensed spectrum are widely used for large-scale Internet of Things (IoT) deployments. However, coexistence with heterogeneous external wireless systems introduces frequency-dependent interference that distorts channel observation, degrades throughput efficiency, and causes severe service unfairness across channels. This paper proposes the Joint Online Backoff and Interference-aware Load Control (JOB-ILC) framework for multi-channel unslotted ALOHA LPWANs. By leveraging correlation-based preamble detection, JOB-ILC enables channel observation under external interference and performs interference-aware backlog estimation. Based on these observation-driven estimates, the gateway jointly regulates the backoff rate and probabilistically guides distributed channel transitions to maintain consistent per-device service under heterogeneous interference, without centralized scheduling. Simulation results show that JOB-ILC closely tracks the interference-limited throughput of each channel, achieves near-perfect fairness, improves throughput over energy-detection-based control, and improves both throughput and delay over random hopping. The proposed approach provides a practical and scalable solution for robust IoT connectivity in shared unlicensed spectrum. © 2014 IEEE.

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