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

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Toward Millimeter-Wave Joint Radar Communications : A signal processing perspective. / Mishra, Kumar Vijay; Bhavani Shankar, M. R.; Koivunen, Visa; Ottersten, Bjorn; Vorobyov, Sergiy A.

In: IEEE Signal Processing Magazine, Vol. 36, No. 5, 8828030, 01.09.2019, p. 100-114.

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Mishra, Kumar Vijay ; Bhavani Shankar, M. R. ; Koivunen, Visa ; Ottersten, Bjorn ; Vorobyov, Sergiy A. / Toward Millimeter-Wave Joint Radar Communications : A signal processing perspective. In: IEEE Signal Processing Magazine. 2019 ; Vol. 36, No. 5. pp. 100-114.

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@article{9fe771cfd77e4d48b0cc9de1f9a98096,
title = "Toward Millimeter-Wave Joint Radar Communications: A signal processing perspective",
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.",
author = "Mishra, {Kumar Vijay} and {Bhavani Shankar}, {M. R.} and Visa Koivunen and Bjorn Ottersten and Vorobyov, {Sergiy A.}",
year = "2019",
month = "9",
day = "1",
doi = "10.1109/MSP.2019.2913173",
language = "English",
volume = "36",
pages = "100--114",
journal = "IEEE Signal Processing Magazine",
issn = "1053-5888",
number = "5",

}

RIS - Download

TY - JOUR

T1 - Toward Millimeter-Wave Joint Radar Communications

T2 - A signal processing perspective

AU - Mishra, Kumar Vijay

AU - Bhavani Shankar, M. R.

AU - Koivunen, Visa

AU - Ottersten, Bjorn

AU - Vorobyov, Sergiy A.

PY - 2019/9/1

Y1 - 2019/9/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85072215191&partnerID=8YFLogxK

U2 - 10.1109/MSP.2019.2913173

DO - 10.1109/MSP.2019.2913173

M3 - Review Article

VL - 36

SP - 100

EP - 114

JO - IEEE Signal Processing Magazine

JF - IEEE Signal Processing Magazine

SN - 1053-5888

IS - 5

M1 - 8828030

ER -

ID: 37080200