Spatial Modulation for Joint Radar-Communications Systems: Design, Analysis, and Hardware Prototype

Ma, Dingyou; Shlezinger, Nir; Huang, Tianyao; Shavit, Yariv; Namer, Moshe; Liu, Yimin; Eldar, Yonina C.

doi:10.1109/tvt.2021.3056408

Cited by 90 publications

(43 citation statements)

References 36 publications

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“…The utilization of both sensing and communications in autonomous cars stimulates the design of these functionalities in tandem [37]. Interestingly, [38] proposed a JSAC model for autonomous vehicles by embedding information in radar waveforms via index modulation (IM). Besides, [36] used sparse arrays and frequency-modulated continuous waveforms (FMCWs) to enhance the IM-based JSAC systems.…”

Section: B Intelligent Transportation Systemsmentioning

confidence: 99%

“…12, to piggyback both sensing and communication functionalities for special purposes. In [75], a hardware prototype for a spatial IM-based JSAC system was proposed with respect to two coexisting sensing and communications subsystems. It employs generalized spatial IM and distributed transceiver antenna components across sensing and communication subsystems based on the sent message, resulting in enhanced communication rates by integrating more data bits in the antenna selection indices.…”

Section: A Point-to-point Jsacmentioning

confidence: 99%

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Toward Joint Radar, Communication, Computation, Localization, and Sensing in IoT

Kim

Choi

2022

IEEE Access

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Since the 1960s, joint sensing and communication (JSAC) has been proposed as an attractive technique with advantages of enhanced spectral and hardware efficiency along with low latency. However, in those old days, complex transceiver designs hindered the massive adoption of JSAC in many applications. Nevertheless, thanks to advancing wireless technologies in recent years, JSAC has recently attracted substantial attention for a wide range of civil and military applications. In particular, JSAC enables simultaneous sensing and communication functionalities with the full cooperation of both operations in shared resources such as hardware as well as radio resources (i.e., frequency, time, space and so on). Note that sensing functionality is associated with other sub-functionalities of radio-detectionand-ranging (Radar), computation, and localization which are sporadically used terms in the literature. Thus, to generalize the concept and avoid any confusion, we use the term "sensing" in the acronym JSAC as a consistent and general term associated with the other aforementioned sub-functionalities. This paper elaborates on defining sensing and communication operations and then, provides an overview with preliminaries, key latest findings, and state-of-the-art of JSAC. It also explores both existing and emerging Internet of Things (IoT) applications of JSAC. Next, it provides a new classification of JSAC technologies by taking into account not only the existing JSAC technologies but also a diverse range of technologies that allow JSAC to be used for various types of IoT applications. Eventually, this study projects future research directions and challenges of enabling JSAC in IoT.

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Section: B Intelligent Transportation Systemsmentioning

confidence: 99%

Section: A Point-to-point Jsacmentioning

confidence: 99%

Toward Joint Radar, Communication, Computation, Localization, and Sensing in IoT

Kim

Choi

2022

IEEE Access

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“…This problem is from (15) with the target function being the sum rate. Since the SINR constraint is non-convex, sum rate maximization is non-convex and hard to solve.…”

Section: S Dpcmentioning

confidence: 99%

“…including multi-functional waveform design [4]- [9], information embedding [10]- [15], joint transmit beamforming [2], [6], [8], [16], [17] and so on.…”

mentioning

confidence: 99%

Transmit Design for Joint MIMO Radar and Multiuser Communications with Transmit Covariance Constraint

Liu¹,

Huang²,

Liu³

2021

Preprint

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In this paper, we consider the design of a multiple-input multiple-output (MIMO) transmitter which simultaneously functions as a MIMO radar and a base station for downlink multiuser communications.In addition to a power constraint, we require the covariance of the transmit waveform be equal to a given optimal covariance for MIMO radar, to guarantee the radar performance. With this constraint, we formulate and solve the signal-to-interference-plus-noise ratio (SINR) balancing problem for multiuser transmit beamforming via convex optimization. Considering that the interference cannot be completely eliminated with this constraint, we introduce dirty paper coding (DPC) to further cancel the interference, and formulate the SINR balancing and sum rate maximization problem in the DPC regime. Although both of the two problems are non-convex, we show that they can be reformulated to convex optimizations via the Lagrange and downlink-uplink duality. In addition, we propose gradient projection based algorithms to solve the equivalent dual problem of SINR balancing, in both transmit beamforming and DPC regimes. The simulation results demonstrate significant performance improvement of DPC over transmit beamforming, and also indicate that the degrees of freedom for the communication transmitter is restricted by the rank of the covariance. I. I Joint radar and communications on a single platform is an emerging technique which can reduce the cost of the platform, achieve spectrum sharing, and enhance the performance via the cooperation of radar and communications [1]-[3]. Because of these promising advantages, numerous schemes are proposed in recent years to implement joint radar and communications,

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“…As for the DFRC systems, where the radar is regarded as the primary function and communication is regarded as the secondary function, many signal embedding strategies, such Jifa Zhang is with the School of Electronic and Information Engineering, Beihang University, Beijing 100191, China, E-mail: (jifazhang@yeah.net) as complex beampattern modulation (CBM) [13], [14], index modulation (IM) [15], [16], spatial modulation (SM) [17], fast time modulation [18], have been proposed. The essence of CBM is to steer the mainlobe towards the targets of interest while changing the complex beampattern towards the communication receiver according to the random communication symbols.…”

Section: Introductionmentioning

confidence: 99%

Joint Range and Doppler Adaptive Processing for CBM based DFRC systems

Zhang¹

2021

Preprint

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Recently, dual-function radar communication (DFRC) systems have been proposed to integrate radar and communication into one platform for spectrum sharing. Various signalling strategies have been proposed to embed communication information into the radar transmitted waveforms. Among these, complex beampattern modulation (CBM) embeds communication information into the complex transmit beampattens via changing the amplitude and phase of the beampatterns towards the communication receiver. The embedding of random communication information causes the clutter modulation and high range-Doppler sidelobe. What's more, transmitting different waveforms on a pulse to pulse basis degrades the radar target detection capacity when traditional sequential pulse compression (SPC) and moving-target detection (MTD) is utilized. In this paper, a minimum mean square error (MMSE) based filter, denoted as joint range and Doppler adaptive processing (JRDAP) is proposed. The proposed method estimates the targets' impulse response coefficients at each range-Doppler cell adaptively to suppress high range-Doppler sidelobe and clutter modulation. The performance of proposed method is very close to the full-dimension adaptive multiple pulses compression (AMPC) while reducing computational complexity greatly.

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Spatial Modulation for Joint Radar-Communications Systems: Design, Analysis, and Hardware Prototype

Cited by 90 publications

References 36 publications

Toward Joint Radar, Communication, Computation, Localization, and Sensing in IoT

Toward Joint Radar, Communication, Computation, Localization, and Sensing in IoT

Transmit Design for Joint MIMO Radar and Multiuser Communications with Transmit Covariance Constraint

Joint Range and Doppler Adaptive Processing for CBM based DFRC systems

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