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Sen. Netw."],"published-print":{"date-parts":[[2023,8,31]]},"abstract":"<jats:p>\n            The massive connection of LoRa brings serious collision interference. Existing collision decoding methods cannot effectively deal with the adjacent collisions that occur when the collided symbols are adjacent in the frequency spectrum. The decoding features relied on by the existing methods will be corrupted by adjacent collisions. To address these issues, we propose\n            <jats:italic>Paralign<\/jats:italic>\n            , which is the first LoRa collision decoder supporting decoding LoRa collisions with confusing symbols via parallel alignment. The key enabling technology behind\n            <jats:italic>Paralign<\/jats:italic>\n            is tha there is no spectrum leakage with periodic truncation of a chirp.\n            <jats:italic>Paralign<\/jats:italic>\n            leverages the precise spectrum obtained by aligning the de-chirped periodic signals from each packet in parallel for spectrum filtering and power filtering. To aggregate correlation peaks in different windows of the same symbol,\n            <jats:italic>Paralign<\/jats:italic>\n            matches the peaks of multiple interfering windows to the interested window based on the time offset between collided packets. Moreover, a periodic truncation method is proposed to address the multiple candidate peak problem caused by side lobes of confusing symbols. We evaluate\n            <jats:italic>Paralign<\/jats:italic>\n            using USRP N210 in a 20-node network. Experimental results demonstrate that\n            <jats:italic>Paralign<\/jats:italic>\n            can significantly improve network throughput, which is over 1.46\u00d7  higher than state-of-the-art methods.\n          <\/jats:p>","DOI":"10.1145\/3571586","type":"journal-article","created":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T15:12:31Z","timestamp":1668697951000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Decoding LoRa Collisions via Parallel Alignment"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3792-0057","authenticated-orcid":false,"given":"Yuting","family":"Wang","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6698-5709","authenticated-orcid":false,"given":"Fanhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7950-6773","authenticated-orcid":false,"given":"Xiaolong","family":"Zheng","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5040-2468","authenticated-orcid":false,"given":"Liang","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7199-5047","authenticated-orcid":false,"given":"Huadong","family":"Ma","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,3]]},"reference":[{"key":"e_1_3_1_2_2","article-title":"DSME-LoRa: Seamless long range communication between arbitrary nodes in the constrained IoT","author":"\u00c1lamos Jos\u00e9","year":"2022","unstructured":"Jos\u00e9 \u00c1lamos, Peter Kietzmann, Thomas C. 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