{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T18:09:48Z","timestamp":1772042988551,"version":"3.50.1"},"reference-count":19,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,15]],"date-time":"2022-11-15T00:00:00Z","timestamp":1668470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Amazon.com, Inc."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper quantifies the coverage area of Low-Power Wide-Area Networks (LPWAN) for Packet Success Rates (PSR) above 85%, where acceptable Quality of Service (QoS) can be achieved. The network consists of battery-operated end-nodes (ENs) and multiple stationary gateways (GWs). We consider asynchronous communication that uses ALOHA-based random channel access. Each transmission from the ENs can be received by multiple GWs. Such spatial diversity results in favorable Signal-to-Noise ratios (SNR). The LoRa modulation is assumed and its specific features, such as IQ inversion, further contribute to decreasing the impact of interference. An increase in the GW density improves network performance, which allows support for a larger density of end-nodes as well as increasing the coverage area. Our simulation results show that a suburban area of up to 1.44 km2 can be covered with five GWs with up to fifty end-nodes with a PSR greater than 86%.<\/jats:p>","DOI":"10.3390\/s22228831","type":"journal-article","created":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T04:39:03Z","timestamp":1668573543000},"page":"8831","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Performance of Narrow Band Wide Area Networks with Gateway Diversity"],"prefix":"10.3390","volume":"22","author":[{"given":"Ba\u015fak","family":"Can","sequence":"first","affiliation":[{"name":"Amazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3092-5499","authenticated-orcid":false,"given":"Bora","family":"Karao\u011flu","sequence":"additional","affiliation":[{"name":"Amazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Uttam","family":"Bhat","sequence":"additional","affiliation":[{"name":"Amazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5452-7516","authenticated-orcid":false,"given":"Muhammed Faruk","family":"Gencel","sequence":"additional","affiliation":[{"name":"Amazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5626-6420","authenticated-orcid":false,"given":"Thomas","family":"Chen","sequence":"additional","affiliation":[{"name":"Amazon Lab126, Ciyun Rd., East Dist., Hsinchu City 300196, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,15]]},"reference":[{"key":"ref_1","unstructured":"Cisco (2020). Cisco Annual Internet Report (2018\u20132023), White Paper; Cisco."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Jouhari, M., Amhoud, E., Saeedy, N., and Alouiniz, M. (2022). A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges. arXiv.","DOI":"10.1109\/COMST.2023.3274934"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Almuhaya, M.A.M., Jabbar, W.A., Sulaiman, N., and Abdulmalek, S. (2022). A Survey on LoRaWAN Technology: Recent Trends, Opportunities, Simulation Tools and Future Directions. 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Charm: Exploiting Geographical Diversity through Coherent Combining in Low-Power Wide-Area Networks. Proceedings of the 17th ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Porto, Portugal.","DOI":"10.1109\/IPSN.2018.00013"},{"key":"ref_16","unstructured":"Magrin, D. (2016). Network Level Performances of LoRa System. [Master\u2019s Thesis, University of Padova]."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Magrin, D., Centenaro, M., and Vangelista, L. (2017, January 21\u201325). Performance Evaluation of LoRa Networks in a Smart City Scenario. Proceedings of the IEEE International Conference on Communications (ICC), Paris, France.","DOI":"10.1109\/ICC.2017.7996384"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Capuzzo, M., Magrin, D., and Zanella, A. (2018, January 20\u201322). Confirmed Traffic in LoRaWAN: Pitfalls and Countermeasures. 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