2018/12/04 by Ghaith Hattab, Hattab, Ghaith, Danijela Čabrić +1
Computer Science · Engineering · #Cognitive Radio Networks and Spectrum Sensing #Distributed Sensor Networks and Detection Algorithms #Energy Efficient Wireless Sensor Networks #FOS: Electrical engineering #Indoor and Outdoor Localization Technologies #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1812.02617
openalex publication_date 2018/12/04 · openalex created_date 2022/08/01 · openalex updated_date 2026/07/28
In this paper, we propose a dynamic spectrum sensing-based architecture to\nprovide connectivity for a massive number of Internet-of-things (IoT) objects\nover the unlicensed spectrum. Specifically, the architecture relies on\ndeploying sensing access points (SAPs), e.g., small cells with sensing\ncapabilities, that aim to (i) identify a large number of narrowband channels in\na wideband spectrum, as many massive IoT applications have low-rate\nrequirements, and (ii) aggressively reuse the unlicensed channels at the SAPs'\nlocations as IoT devices typically transmit at low power, occupying a small\nspatial footprint. Instead of enforcing each SAP to sense the entire spectrum,\nwe develop a sensing assignment scheduler that ensures each one senses a subset\nof the spectrum. We then develop a distributed spatio-spectral cooperative\nsensing algorithm that enables each SAP to have local information about the\noccupancy of the entire spectrum. We present numerical simulations to validate\nthe effectiveness of the proposed system in the presence of WiFi access points\n(APs). It is shown that the proposed system outperforms non-cooperative and\ncentralized schemes in terms of reliably identifying more available\nspatio-spectral blocks with a lower misdetection of transmitting WiFi APs.\n