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ACM Netw."],"published-print":{"date-parts":[[2024,6,13]]},"abstract":"<jats:p>Adaptive Data Rate (ADR) is used by multi-channel LoRaWANs to meet the demanding capacity needs of LoRa networks. The network server running ADR in each channel determines the optimum data rate and assigns the appropriate spreading factor for each LoRa device to maximize the network throughput. This in turn requires the gateway to be capable of receiving LoRa packets of all possible spreading factors. Existing gateways achieve this by using multiple RF front ends, increasing the overall cost and complexity. In this work, we propose BYOG (Bring Your Own Gateway), a LoRaWAN receiver that can receive and decode 10 channels simultaneously in real-time. Towards this pipeline, we develop self-dechirping, an SF-agnostic packet detection algorithm that also detects the spreading factor of the packet. This computationally lightweight algorithm can be implemented on any general-purpose software-defined radio, bringing down the cost and ease of LoRaWAN gateway implementations. BYOG will enable research and development in LoRaWAN ADR. Using experimental, real-world datasets, we show that the proposed algorithm can detect the spreading factor accurately and operate over a wide range of SNRs using three different SDRs (RTL-SDR, HackRF One, USRP B210). BYOG performs as well as a high-end LoRaWAN gateway in terms of network throughput.<\/jats:p>","DOI":"10.1145\/3656299","type":"journal-article","created":{"date-parts":[[2024,6,13]],"date-time":"2024-06-13T09:54:11Z","timestamp":1718272451000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["BYOG : Multi-Channel, Real-time LoRaWAN Gateway Testbed using General-purpose Software Defined Radio"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6797-1747","authenticated-orcid":false,"given":"Muhammad Osama","family":"Shahid","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6057-8159","authenticated-orcid":false,"given":"Bhuvana","family":"Krishnaswamy","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,6,13]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1707462114"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3376897.3377862"},{"key":"e_1_2_1_3_1","volume-title":"User-centric smart buildings for energy sustainable smart cities. 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Sensors, 20(7):2028, 4 2020.","journal-title":"Sensors"},{"key":"e_1_2_1_8_1","unstructured":"LoRa Vs LoRaWAN. https:\/\/lora-developers.semtech.com\/documentation\/tech-papers-and-guides\/lora-and-lorawan\/."},{"key":"e_1_2_1_9_1","unstructured":"Understanding ADR in LoRaWAN. https:\/\/lora-developers.semtech.com\/documentation\/tech-papers-and-guides\/understanding-adr\/."},{"key":"e_1_2_1_10_1","volume-title":"October 17","author":"Sornin Nicolas","year":"2017","unstructured":"Nicolas Sornin and Ludovic Champion. Signal concentrator device, October 17 2017. US Patent 9,794,095."},{"key":"e_1_2_1_11_1","unstructured":"8 Channel LoRa Gateway. https:\/\/www.adafruit.com\/product\/4327."},{"key":"e_1_2_1_12_1","unstructured":"LoRa Transceivers. https:\/\/www.thethingsnetwork.org\/docs\/lorawan\/transceivers\/."},{"key":"e_1_2_1_13_1","unstructured":"SX1276 DataSheet. https:\/\/www.semtech.com\/products\/wireless-rf\/lora-connect\/sx1276#documentation."},{"key":"e_1_2_1_14_1","unstructured":"Tektelic KONA Mega 64-Channel LoRaWAN Gateway. https:\/\/www.embeddedworks.net\/sens652\/."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.5220\/0006668400410051"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3452296.3472931"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3545571"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488695"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485730.3485928"},{"key":"e_1_2_1_20_1","first-page":"879","volume-title":"19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22)","author":"Li Chenning","year":"2022","unstructured":"Chenning Li, Xiuzhen Guo, Longfei Shangguan, Zhichao Cao, and Kyle Jamieson. {CurvingLoRa} to boost {LoRa} network throughput via concurrent transmission. 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Spreading factor detection for low-cost adaptive data rate in lorawan gateways. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, SenSys '22, page 918--924, New York, NY, USA, 2023. Association for Computing Machinery."},{"key":"e_1_2_1_31_1","first-page":"1959","volume-title":"21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)","author":"Shahid Muhammad Osama","year":"2024","unstructured":"Muhammad Osama Shahid, Daniel Koch, Jayaram Raghuram, Bhuvana Krishnaswamy, Krishna Chintalapudi, and Suman Banerjee. Cloud-LoRa: Enabling cloud radio access LoRa networks using reinforcement learning based Bandwidth-Adaptive compression. In 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24), pages 1959--1976, Santa Clara, CA, April 2024. 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