Toward Millimeter-Wave Joint Radar Communications: A signal processing perspective

Kumar Vijay Mishra; M. R. Bhavani Shankar; Visa Koivunen; Bjorn Ottersten; Sergiy A. Vorobyov

doi:10.1109/MSP.2019.2913173

Toward Millimeter-Wave Joint Radar Communications: A signal processing perspective

Kumar Vijay Mishra
, M. R. Bhavani Shankar
, Visa Koivunen
, Bjorn Ottersten
, Sergiy A. Vorobyov

United States Army Research Laboratory
University of Luxembourg
Hertzwell

Tutkimustuotos: Lehtiartikkeli › Review Article › vertaisarvioitu

520 Sitaatiot (Scopus)

Abstrakti

Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave (mmwave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade off between communications and radar functionalities. Novel multiple-input, multiple-output (MIMO) signal processing techniques are required because mm-wave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mm-wave JRC systems with an emphasis on waveform design.

Alkuperäiskieli	Englanti
Artikkeli	8828030
Sivut	100-114
Sivumäärä	15
Julkaisu	IEEE Signal Processing Magazine
Vuosikerta	36
Numero	5
DOI - pysyväislinkit	https://doi.org/10.1109/MSP.2019.2913173
Tila	Julkaistu - 1 syysk. 2019
OKM-julkaisutyyppi	A2 Katsausartikkeli tieteellisessä aikakauslehdessä

Rahoitus

This work is partially funded by the European Research Council grant Actively Enhanced Cognition based Frame-work for Design of Complex Systems and Luxembourg National Research Fund Project Adaptive mmWave Radar Platform for Enhanced Situational Awareness: Design and Implementation. Kumar Vijay Mishra ([email protected]) received his B.Tech. degree, summa cum laude (gold medal, honors) in electronics and communications engineering from the National Institute of Technology, Hamirpur, India, in 2003, his M.S. degree in electrical and computer engineering from Colorado State University, Fort Collins, in 2012, and his Ph.D. degree in electrical and computer engineering and M.S. degree in mathematics from the University of Iowa, Iowa City, in 2015. Currently, he is the technical advisor to the automotive radar start-up Hertzwell, Singapore; a research fellow at the Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg City; and the Harry Diamond Distinguished Postdoctoral Fellow at the U.S. Army Research Laboratory, supported by the U.S. National Academies of Sciences, Engineering, and Medicine. He is a Senior Member of the IEEE. Björn Ottersten ([email protected]) received his M.S. degree in electrical engineering and applied physics from Linköping University, Sweden, in 1986 and his Ph.D. degree in electrical engineering from Stanford University, California, in 1990. Currently, he is the director for the Interdisciplinary Centre for Security, Reliability and Trust at the University of Luxembourg, Luxembourg City. He coauthored papers that received an IEEE Signal Processing Society Best Paper Award in 1993, 2001, 2006, and 2013 and eight IEEE conference papers that received best paper awards. In 1991, he became a professor of signal processing at the Royal Institute of Technology, Stockholm, Sweden. In 2011, he received the IEEE Signal Processing Society Technical Achievement Award. He received the European Research Council Advanced Research Grant twice, 2009–2013 and 2017–2021. He is a Fellow of the IEEE and of the European Association for Signal Processing.

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10.1109/MSP.2019.2913173

https://arxiv.org/abs/1905.00690

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abstract = "Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave (mmwave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade off between communications and radar functionalities. Novel multiple-input, multiple-output (MIMO) signal processing techniques are required because mm-wave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mm-wave JRC systems with an emphasis on waveform design.",

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AU - Ottersten, Bjorn

AU - Vorobyov, Sergiy A.

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Toward Millimeter-Wave Joint Radar Communications: A signal processing perspective

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