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LPWAN in the TV White Spaces: A Practical Implementation and Deployment Experiences

Published:13 May 2021Publication History
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Abstract

Low-Power Wide-Area Network (LPWAN) is an enabling Internet-of-Things technology that supports long-range, low-power, and low-cost connectivity to numerous devices. To avoid the crowd in the limited ISM band (where most LPWANs operate) and cost of licensed band, the recently proposed Sensor Network over White Spaces (SNOW) is a promising LPWAN platform that operates over the TV white spaces. As it is a very recent technology and is still in its infancy, the current SNOW implementation uses the Universal Software Radio Peripheral devices as LPWAN nodes, which has high costs (≈$750 USD per device) and large form-factors, hindering its applicability in practical deployment. In this article, we implement SNOW using low-cost, low form-factor, low-power, and widely available commercial off-the-shelf (COTS) devices to enable its practical and large-scale deployment. Our choice of the COTS device (TI CC13x0: CC1310 or CC1350) consequently brings down the cost and form-factor of a SNOW node by 25× and 10×, respectively. Such implementation of SNOW on the CC13x0 devices, however, faces a number of challenges to enable link reliability and communication range. Our implementation addresses these challenges by handling peak-to-average power ratio problem, channel state information estimation, carrier frequency offset estimation, and near-far power problem. Our deployment in the city of Detroit, Michigan, demonstrates that CC13x0-based SNOW can achieve uplink and downlink throughputs of 11.2 and 4.8 kbps per node, respectively, over a distance of 1 km. Also, the overall throughput in the uplink increases linearly with the increase in the number of SNOW nodes.

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            • Published in

              cover image ACM Transactions on Embedded Computing Systems
              ACM Transactions on Embedded Computing Systems  Volume 20, Issue 4
              Special Issue on FDL2019
              July 2021
              256 pages
              ISSN:1539-9087
              EISSN:1558-3465
              DOI:10.1145/3458852
              • Editor:
              • Tulika Mitra
              Issue’s Table of Contents

              Copyright © 2021 ACM

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 13 May 2021
              • Revised: 1 January 2021
              • Accepted: 1 January 2021
              • Received: 1 August 2020
              Published in tecs Volume 20, Issue 4

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