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The last few years have seen the proliferation of low-power wide area networks like LoRa, Sigfox and 802.11ah, each of which use a different and sometimes proprietary coding and modulation scheme, work below the noise floor and operate on the same frequency band. We introduce DeepSense, which is the first carrier sense mechanism that enables random access and coexistence for low-power wide area networks even when signals are below the noise floor. Our key insight is that any communication protocol that operates below the noise floor has to use coding at the physical layer. We show that neural networks can be used as a general algorithmic framework that can learn the coding mechanisms being employed by such protocols to identify signals that are hidden within noise. Our evaluation shows that DeepSense performs carrier sense across 26 different LPWAN protocols and configurations below the noise floor and can operate in the presence of frequency shifts as well as concurrent transmissions. Beyond carrier sense, we also show that DeepSense can support multi bit-rate LoRa networks by classifying between 21 different LoRa configurations and flexibly adapting bitrates based on signal strength. In a deployment of a multi-rate LoRa network, DeepSense improves bit rate by 4x for nearby devices and provides a 1.7x increase in the number of locations that can connect to the campus-wide network.
Recent years have witnessed the proliferation of Low-power Wide Area Networks (LPWANs) in the unlicensed band for various Internet-of-Things (IoT) applications. Due to the ultra-low transmission power and long transmission duration, LPWAN devices ine
In this paper, we deliver a discussion regarding the role of Low-Power Wide-Area Networks (LPWAN) in the cellular Internet-of-Things (IoT) infrastructure to support massive Machine-Type Communications (mMTC) in next-generation wireless systems beyond
Despite the proliferation of mobile devices in various wide-area Internet of Things applications (e.g., smart city, smart farming), current Low-Power Wide-Area Networks (LPWANs) are not designed to effectively support mobile nodes. In this paper, we
Recent advances in Low-Power Wide-Area Networks have mitigated interference by using cloud assistance. Those methods transmit the RSSI samples and corrupted packets to the cloud to restore the correct message. However, the effectiveness of those meth
Low-power wide-area (LPWA) networks are attracting extensive attention because of their abilities to offer low-cost and massive connectivity to Internet of Things (IoT) devices distributed over wide geographical areas. This article provides a brief o