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In this paper, we propose a dynamic spectrum sensing-based architecture toprovide connectivity for a massive number of Internet-of-things (IoT) objectsover the unlicensed spectrum. Specifically, the architecture relies ondeploying sensing access points (SAPs), e.g., small cells with sensingcapabilities, that aim to (i) identify a large number of narrowband channels ina wideband spectrum, as many massive IoT applications have low-raterequirements, and (ii) aggressively reuse the unlicensed channels at the SAPs'locations as IoT devices typically transmit at low power, occupying a smallspatial footprint. Instead of enforcing each SAP to sense the entire spectrum,we develop a sensing assignment scheduler that ensures each one senses a subsetof the spectrum. We then develop a distributed spatio-spectral cooperativesensing algorithm that enables each SAP to have local information about theoccupancy of the entire spectrum. We present numerical simulations to validatethe effectiveness of the proposed system in the presence of WiFi access points(APs). It is shown that the proposed system outperforms non-cooperative andcentralized schemes in terms of reliably identifying more availablespatio-spectral blocks with a lower misdetection of transmitting WiFi APs.

Distributed Wideband Spatio-Spectral Sensing for Unlicensed Massive IoT Communications