Framework for a Perceptive Mobile Network Using Joint Communication and Radar Sensing

In this paper, we develop a framework for a novel perceptive mobile/cellular network that integrates radar sensing function into the mobile communication network. We propose a unified system platform that enables downlink and uplink sensing, sharing the same transmitted signals with communications....

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Bibliographic Details
Published inIEEE transactions on aerospace and electronic systems Vol. 56; no. 3; pp. 1926 - 1941
Main Authors Rahman, Md. Lushanur, Zhang, J. Andrew, Huang, Xiaojing, Guo, Y. Jay, Heath, Robert W.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Cellular communication
Clutter
clutter suppression
Communication
Compressive sensing
Computer simulation
Detection
Downlink
Frequency division multiple access
joint communication and radar sensing
MIMO communication
Mobile communication
Mobile communication systems
mobile networks
OFDM
Parameter estimation
Radar
RadCom
Recursive methods
Sensors
Subtraction
Wireless networks
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Summary:In this paper, we develop a framework for a novel perceptive mobile/cellular network that integrates radar sensing function into the mobile communication network. We propose a unified system platform that enables downlink and uplink sensing, sharing the same transmitted signals with communications. We aim to tackle the fundamental sensing parameter estimation problem in perceptive mobile networks, by addressing two key challenges associated with sophisticated mobile signals and rich multipath in mobile networks. To extract sensing parameters from orthogonal frequency division multiple access and spatial division multiple access communication signals, we propose two approaches to formulate it to problems that can be solved by compressive sensing techniques. Most sensing algorithms have limits on the number of multipath signals for their inputs. To reduce the multipath signals, as well as removing unwanted clutter signals, we propose a background subtraction method based on simple recursive computation, and provide a closed-form expression for performance characterization. The effectiveness of these methods is validated in simulations.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2019.2939611