{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/86797"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/86797","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Optimum Receiver Design for Internet-of-Things (IoT) with LoRa Transmission Signals","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Botta, Nataraj; 0000-0003-2238-1126"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Su, Weifeng","Electrical Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-02-25T23:22:51Z","date_published":"2025-02-25T23:22:51Z","updated_at":"2026-07-27T19:05:37Z","subjects":["electrical engineering"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/86797","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Su, Weifeng","Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Botta, Nataraj; 0000-0003-2238-1126"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-02-25T23:22:51Z","2020","2020-06-09 19:58:14"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["electrical engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/86797"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","Recent advances in Internet of Things (IoT), Machine to Machine (M2M) communications have increased the demand of low power wide area networks (LPWAN) technologies. Different standards have been published to meet this requirements. LoRa (acronym for Long Range) being the leading standard amongst them has gained high research interest. LoRa is developed and patented by Semtech. This thesis focuses on the physical layer of LoRa known as LoRa PHY or simply LoRa. LoRa transmission signals are analysed in baseband domain. These signals are viewed as basis signal set and the vector model of LoRa signals is presented. The contribution of this thesis also lies on Additive White Gaussian Noise (AWGN) analysis for IoT systems. AWGN is analysed in baseband domain and a generalised expression for baseband noise correlation is derived. The baseband AWGN is further projected on to the basis signal set to get the noise vector representation for LoRa signals. The later part of this thesis focuses on the receiver of the LoRa system. An existing receiver design is reviewed and an alternative receiver design is proposed based on optimum MAP detector. Firstly, the received signal is projected onto the basis signal set to get the vector representation. Since the noise components are correlated, Multivariate Gaussian random distribution was used to obtain the noise vector distribution. The MAP detector was presented in vector domain. Efficient implementation of the proposed receiver is then presented with the help of a filter and splitter. To evaluate the performance of the proposed receiver, both existing and proposed receivers are simulated in Matlab with AWGN channel. Both correlated and uncorrelated noise are considered for simulation. Bit error rate (BER) performance comparison was carried for the 2 receivers for 10^5 symbols with varying parameters like bandwidth and spreading factor.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Optimum Receiver Design for Internet-of-Things (IoT) with LoRa Transmission Signals"]}]}],"canonical_facts":{"dc:contributor":["Su, Weifeng","Electrical Engineering"],"dc:creator":["Botta, Nataraj; 0000-0003-2238-1126"],"dc:date":["2025-02-25T23:22:51Z","2020","2020-06-09 19:58:14"],"dc:description":["M.S.","Recent advances in Internet of Things (IoT), Machine to Machine (M2M) communications have increased the demand of low power wide area networks (LPWAN) technologies. Different standards have been published to meet this requirements. LoRa (acronym for Long Range) being the leading standard amongst them has gained high research interest. LoRa is developed and patented by Semtech. This thesis focuses on the physical layer of LoRa known as LoRa PHY or simply LoRa. LoRa transmission signals are analysed in baseband domain. These signals are viewed as basis signal set and the vector model of LoRa signals is presented. The contribution of this thesis also lies on Additive White Gaussian Noise (AWGN) analysis for IoT systems. AWGN is analysed in baseband domain and a generalised expression for baseband noise correlation is derived. The baseband AWGN is further projected on to the basis signal set to get the noise vector representation for LoRa signals. The later part of this thesis focuses on the receiver of the LoRa system. An existing receiver design is reviewed and an alternative receiver design is proposed based on optimum MAP detector. Firstly, the received signal is projected onto the basis signal set to get the vector representation. Since the noise components are correlated, Multivariate Gaussian random distribution was used to obtain the noise vector distribution. The MAP detector was presented in vector domain. Efficient implementation of the proposed receiver is then presented with the help of a filter and splitter. To evaluate the performance of the proposed receiver, both existing and proposed receivers are simulated in Matlab with AWGN channel. Both correlated and uncorrelated noise are considered for simulation. Bit error rate (BER) performance comparison was carried for the 2 receivers for 10^5 symbols with varying parameters like bandwidth and spreading factor.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/86797"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["electrical engineering"],"dc:title":["Optimum Receiver Design for Internet-of-Things (IoT) with LoRa Transmission Signals"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:37Z"}