Reference : Localization Performance of 1-Bit Passive Radars in NB-IoT Applications
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/41866
Localization Performance of 1-Bit Passive Radars in NB-IoT Applications
English
Sedighi, Saeid mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Mishra, Kumar Vijay mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
Shankar, Bhavani mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
14-Dec-2019
Localization Performance of 1-Bit Passive Radars in NB-IoT Applications
Sedighi, Saeid mailto
Mishra, Kumar Vijay mailto
Shankar, Bhavani mailto
Ottersten, Björn mailto
IEEE
Yes
CA, USA
2019 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019)
14-11-2019 to 19-11-2019
IEEE
Guadeloupe
French West Indies
[en] Fractional optimization, one-bit quantization ; narrowband internet-of-things ; passive radar
[en] Location-based services form an important use-case in emerging narrowband Internet-of-Things (NB-IoT) networks. Critical to this offering is an accurate estimation of the location without overlaying the network with additional active sensors. The massive number of devices, low power requirement, and low bandwidths restrict the sampling rates of NB-IoT receivers. In this paper, we propose a novel low-complexity approach for NB-IoT target delay estimation in cases where one-bit analog-to-digital-converters (ADCs) are employed to sample the received radar signal instead of high-resolution ADCs. This problem has potential applications in the design of inexpensive NB-IoT radar and sensing devices. We formulate the target estimation as a multivariate fractional optimization problem and solve it via Lasserre's semi-definite program relaxation. Numerical experiments suggest feasibility of the proposed approach yielding high localization accuracy with a very low number of 1-bit samples.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/41866
FnR ; FNR11228830 > Saeid Sedighi > > Compressive Sensing for Ranging and Detection in Automotive Applications > 15/02/2017 > 14/02/2021 > 2016

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
CAMSAP_2019.pdfAuthor preprint316.62 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.