Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162552
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dc.contributor.authorShang, Pengfeien_US
dc.date.accessioned2022-10-31T05:34:33Z-
dc.date.available2022-10-31T05:34:33Z-
dc.date.issued2022-
dc.identifier.citationShang, P. (2022). Reference signal received power (RSRP)-based localisation using 5G signals. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162552en_US
dc.identifier.urihttps://hdl.handle.net/10356/162552-
dc.description.abstractWith the development of wireless communication technology and Internet of Things, the demand for location-based services is increasing. Location-based service has been used in warehouse for asset localization, intelligent city construction, fire and earthquake disaster area emergency personnel positioning and so on. However, due to the occlusion of buildings and other reasons, GPS signals cannot achieve high-precision positioning, especially in indoor environment. Therefore high-precision positioning system and positioning scheme have become a research hotspot in the field of location services. The fifth generation (5G) wireless network allows not only for a tremendous increase in capacity for communication but also opens new opportunities for high accuracy positioning of user equipment. Reference Signal Received Power (RSRP) measurements are one of the supported positioning methods for 5G Orthogonal Frequency Division Multiplexing (OFDM) system. In this dissertation, a RSRP-based positioning method will be investigated and developed. The designed positioning method is based on fingerprint which uses a database-based mapping solution and build up a signal propagation model to characterize the relations between transmission distance and received signal strength.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineering::Wireless communication systemsen_US
dc.titleReference signal received power (RSRP)-based localisation using 5G signalsen_US
dc.typeThesis-Master by Courseworken_US
dc.contributor.supervisorLing Keck Voonen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Communications Engineering)en_US
dc.contributor.supervisoremailEKVLING@ntu.edu.sgen_US
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