Enabling Interference Resilience for Low-Power Wide-Area Networks through a Cross-Layer Framework

Description

Complementary to existing wireless protocols (e.g., 5G, WiFi, and Bluetooth), the recently introduced low-power wide-area networks (LPWANs) offer wireless connections with a long communication range and low energy consumption. These unique benefits empower LPWAN's rapid deployment in critical Internet of Things (IoT) applications, such as smart city, precision agriculture, and environment monitoring. Despite the demonstrated success, LPWAN in the unlicensed spectrum inevitably suffers from homogeneous interference due to LPWAN transmissions and heterogeneous interference caused by communication in other protocols. The wireless interference corrupts LPWAN's signal, leading to packet losses, increased energy consumption, and prolonged delay. These issues severely affect IoT application performance and are expected to aggravate given the explosive IoT growth. We note that there exist many interference mitigation techniques for radios with shorter ranges or higher transmission rates. However, these solutions are not applicable for LPWAN, whose unique signal characteristics and inherent natures, e.g., extremely low signal-to-noise ratio (SNR), require dedicated mitigation solutions. Recently, researchers have started to recognize the importance of interference resilience for LPWAN, but they commonly focus on designs at either the Physical layer or the Link layer, still lacking a holistic framework for synergic reliability. Different from existing research, this proposal aims at a cross-layer framework for achieving synergic interference resilience. Our plan consists of Physical-layer signal analysis and Link-layer optimization. More importantly, we will integrate them together to boost the interference resilience beyond individual operations. We will begin with our Physical-layer techniques that propose to analyze the received signal while adapting to LPWAN's inherent challenges, such as low SNR and low power, for resilience improvement. Specifically, we will recover corrupted LPWAN symbols with low cost and high reliability under heterogeneous interference. To deal with homogeneous interference, our concurrent communication will examine unique signal features across different LPWAN devices. In the second part, we plan to identify the critical Physical-layer information and exploit it through Link-layer optimization to boost interference resilience. Our forward error correction will consider LPWAN's symbol reliability, estimated by our Physical layer, in the coding and decoding procedures for enhancing interference protection capability. In addition, we will elaborately schedule LPWAN transmissions to create collisions solvable by our Physical layer for improving communication reliability. By enabling interference-resilient LPWAN, this proposal is expected to offer reliable IoT application performance and prolong low-power devices' lifetime, further benefiting emerging IoT services and fostering Hong Kong's transformation into a smart city.