In a future perspective, the need of mapping an unknown indoor environment, of localizing and retrieving information from objects with zero costs and efforts could be satisfied by the adoption of next 5G technologies. Thanks to the mix of mmW and massive arrays technologies, it will be possible to achieve a higher indoor localization accuracy without relying on a dedicated infrastructure for localization but exploiting that designed for communication purposes. Besides users localization and navigation objectives, mapping and thus, the capability of reconstructing indoor scenarios, will be an important field of research with the possibility of sharing environmental information via crowd-sourcing mechanisms between users. Finally, in the Internet of Things vision, it is expected that people, objects and devices will be interconnected to each other with the possibility of exchanging the acquired and estimated data including those regarding objects identification, positioning and mapping contents. To this end, the merge of RFID, WSN and UWB technologies has demonstrated to be a promising solution. Stimulated by this framework, this work describes different technological and signal processing approaches to ameliorate the localization capabilities and the user awareness about the environment. From one side, it has been focused on the study of the localization and mapping capabilities of multi-antenna systems based on 5G technologies considering different technological issues, as for example those related to the existing available massive arrays. From the other side, UWB-RFID systems relying on passive communication schemes have been investigated in terms of localization coverage and by developing different techniques to improve the accuracy even in presence of NLOS conditions.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:7554 |
| Date | 05 May 2016 |
| Creators | Guerra, Anna <1987> |
| Contributors | Dardari, Davide |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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