Environment Mapping with Millimeter-Wave Massive Arrays: System Design and Performance

Francesco Guidi 1, 2 Anna Guerra 3 Davide Dardari 3 Antonio Clemente 1, 2 Raffaele d'Errico 1, 2
1 CEA-LETI - Laboratoire d'Electronique et des Technologies de l'Information
2 UGA - Université Grenoble Alpes
3 DEI - Dipartimento di Ingegneria dell'Energia elettrica e dell'Informazione
Abstract : Recently, several studies have been moving towards the idea to adopt massive arrays for localization and mapping applications thanks to the high scanning resolution achievable. In this framework, this paper investigates the impact of different design parameters in order to maximize the mapping performance while keeping the receiver architecture as simple as possible when a Bayesian approach is used. To this end, thresholding strategies to filter out unwanted received signal components (cleaning operation before soft mapping), e.g. thermal noise, are analyzed together with other design parameters that can operate directly on raw data. Considerations about possible system design configurations are then drawn inspired by results obtained using measured data, which showed a more pronounced impact of the cleaning approach for 1 GHz bandwidth with respect to 3 GHz.
Keywords : Millimeter-waves massive antenna arrays indoor mapping personal radar
Document type :
Conference papers
Complete list of metadatas

Cited literature [14 references]  Display  Hide  Download
https://hal-cea.archives-ouvertes.fr/cea-01559366
Contributor : Raffaele d'Errico <>
Submitted on : Monday, July 10, 2017 - 4:13:10 PM
Last modification on : Monday, February 25, 2019 - 4:34:20 PM
Long-term archiving on : Wednesday, January 24, 2018 - 4:19:23 PM

File

Globecom2016-Radar.pdf
Files produced by the author(s)

Identifiers

Collections

CEA | DRT | LETI | CEA-GRE

Citation

Francesco Guidi, Anna Guerra, Davide Dardari, Antonio Clemente, Raffaele d'Errico. Environment Mapping with Millimeter-Wave Massive Arrays: System Design and Performance. Globecom Workshops (GC Wkshps), 2016 IEEE, Dec 2016, Washington, DC, United States. ⟨10.1109/GLOCOMW.2016.7848895⟩. ⟨cea-01559366⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

117

Files downloads

350

Contact

CCSD