{"title":"用于太赫兹频率6G系统的无线电SLAM:设计和实验验证","authors":"Marina Lotti;Gianni Pasolini;Anna Guerra;Francesco Guidi;Raffaele D'Errico;Davide Dardari","doi":"10.1109/JSTSP.2023.3285101","DOIUrl":null,"url":null,"abstract":"Next-generation wireless networks will see the convergence of communication and sensing, also exploiting the availability of large bandwidths in the THz spectrum and electrically large antenna arrays on handheld devices. In particular, it is envisaged that user devices will be able to automatically scan their surroundings by steering a very narrow antenna beam and collecting echoes reflected by objects and walls. These data will be utilized to derive a map of the surrounding indoor environment and infer users' trajectories using simultaneous localization and mapping (SLAM) techniques. In this article, we address this scenario by proposing original radio-SLAM (R-SLAM) algorithms, derived from image processing techniques, to map the environment and pinpoint the device position in the map starting from measurements sensed by a mobile THz radar. Initially, to fully understand the THz backscattering phenomenon, we provide an experimental characterization of the THz backscattering channel in indoor environments. Then, the performance of the proposed algorithms is assessed using real-world THz radar measurements and is compared with state-of-the-art SLAM techniques, demonstrating the superiority of the proposed approaches.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"17 4","pages":"834-849"},"PeriodicalIF":8.7000,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4200690/10284021/10148622.pdf","citationCount":"1","resultStr":"{\"title\":\"Radio SLAM for 6G Systems at THz Frequencies: Design and Experimental Validation\",\"authors\":\"Marina Lotti;Gianni Pasolini;Anna Guerra;Francesco Guidi;Raffaele D'Errico;Davide Dardari\",\"doi\":\"10.1109/JSTSP.2023.3285101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Next-generation wireless networks will see the convergence of communication and sensing, also exploiting the availability of large bandwidths in the THz spectrum and electrically large antenna arrays on handheld devices. In particular, it is envisaged that user devices will be able to automatically scan their surroundings by steering a very narrow antenna beam and collecting echoes reflected by objects and walls. These data will be utilized to derive a map of the surrounding indoor environment and infer users' trajectories using simultaneous localization and mapping (SLAM) techniques. In this article, we address this scenario by proposing original radio-SLAM (R-SLAM) algorithms, derived from image processing techniques, to map the environment and pinpoint the device position in the map starting from measurements sensed by a mobile THz radar. Initially, to fully understand the THz backscattering phenomenon, we provide an experimental characterization of the THz backscattering channel in indoor environments. Then, the performance of the proposed algorithms is assessed using real-world THz radar measurements and is compared with state-of-the-art SLAM techniques, demonstrating the superiority of the proposed approaches.\",\"PeriodicalId\":13038,\"journal\":{\"name\":\"IEEE Journal of Selected Topics in Signal Processing\",\"volume\":\"17 4\",\"pages\":\"834-849\"},\"PeriodicalIF\":8.7000,\"publicationDate\":\"2023-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/iel7/4200690/10284021/10148622.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Selected Topics in Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10148622/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10148622/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Radio SLAM for 6G Systems at THz Frequencies: Design and Experimental Validation
Next-generation wireless networks will see the convergence of communication and sensing, also exploiting the availability of large bandwidths in the THz spectrum and electrically large antenna arrays on handheld devices. In particular, it is envisaged that user devices will be able to automatically scan their surroundings by steering a very narrow antenna beam and collecting echoes reflected by objects and walls. These data will be utilized to derive a map of the surrounding indoor environment and infer users' trajectories using simultaneous localization and mapping (SLAM) techniques. In this article, we address this scenario by proposing original radio-SLAM (R-SLAM) algorithms, derived from image processing techniques, to map the environment and pinpoint the device position in the map starting from measurements sensed by a mobile THz radar. Initially, to fully understand the THz backscattering phenomenon, we provide an experimental characterization of the THz backscattering channel in indoor environments. Then, the performance of the proposed algorithms is assessed using real-world THz radar measurements and is compared with state-of-the-art SLAM techniques, demonstrating the superiority of the proposed approaches.
期刊介绍:
The IEEE Journal of Selected Topics in Signal Processing (JSTSP) focuses on the Field of Interest of the IEEE Signal Processing Society, which encompasses the theory and application of various signal processing techniques. These techniques include filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals using digital or analog devices. The term "signal" covers a wide range of data types, including audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and others.
The journal format allows for in-depth exploration of signal processing topics, enabling the Society to cover both established and emerging areas. This includes interdisciplinary fields such as biomedical engineering and language processing, as well as areas not traditionally associated with engineering.