An Indoor mmWave Joint Radar and Communication System with Active Channel Perception

Jiao, Chunxu; Zhang, Zhaoyang; Zhong, Caijun; Feng, Zhiyong

doi:10.1109/icc.2018.8422132

Cited by 21 publications

(10 citation statements)

References 15 publications

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“…Such kind of environment sensing has long been accomplished by traditional Radar technology which has been re-garded as a related but separate field from communication. However, the channel state information (CSI) obtained during the communication process usually contains certain knowledge of the environment [6], [7], and likewise, the environment sensing result also helps improve the accuracy of channel estimation and enhance the performance of communication [8], [9]. As the wireless network operates in higher frequency with wider bandwidth and deploys denser base stations with a larger amount of antennas, its longly-neglected sensing capability inherited from the intrinsic nature of electromagnetic wave propagation becomes even more explorable.…”

Section: A Motivationmentioning

confidence: 99%

Joint Multi-User Communication and Sensing Exploiting Both Signal and Environment Sparsity

Tong,

Zhang,

Wang

et al. 2021

Preprint

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As a potential technology feature for 6G wireless networks, the idea of sensing-communication integration requires the system not only to complete reliable multi-user communication but also to achieve accurate environment sensing. In this paper, we consider such a joint communication and sensing (JCAS) scenario, in which multiple users use the sparse code multiple access (SCMA) scheme to communicate with the wireless access point (AP). Part of the user signals are scattered by the environment object and reflected by an intelligent reflective surface (IRS) before they arrive at the AP. We exploit the sparsity of both the structured user signals and the unstructured environment and propose an iterative and incremental joint multiuser communication and environment sensing scheme, in which the two processes, i.e., multi-user information detection and environment object detection, interweave with each other thanks to their intrinsic mutual dependence. The proposed algorithm is sliding-window based and also graph based, which can keep on sensing the environment as long as there are illuminating user signals. The trade-off relationship between the key system parameters is analyzed, and the simulation result validates the convergence and effectiveness of the proposed algorithm.

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Section: A Motivationmentioning

confidence: 99%

Joint Multi-User Communication and Sensing Exploiting Both Signal and Environment Sparsity

Tong,

Zhang,

Wang

et al. 2021

Preprint

Self Cite

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“…Pickering emulsions can be stabilized by polysaccharide-based particles [64,65,69,70] that can provide strong steric stabilization, but lack as emulsifiers. Protein-based particles have been also adopted to stabilize the Pickering emulsions [71][72][73][74], even though a structural dissociation can be noticed when adsorbed at the interface. The protein-polysaccharide conjunction can provide both good emulsification performance and strong steric stabilization as demonstrated by recent works [55*, [75][76][77][78][79].…”

Section: Stabilizing Pickering Emulsionsmentioning

confidence: 99%

Protein–polysaccharide interactions and aggregates in food formulations

Gentile

2020

Current Opinion in Colloid & Interface Science

153

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“…There exist research outputs on reconstructing cluster sparse signals in general, for example, through periodic compressive support [28], model‐based CS [29], variational Bayes approach [30], and block Bayesian method [31]. In [32], a millimetre‐wave joint radar and communication system for indoor scenarios is developed, using estimated radar channel coefficients. However, there is only very limited work on how a cluster sparsity structure can be exploited in JCAS systems such as perceptive mobile networks that involve OFDMA and multiuser‐MIMO.…”

Section: Introductionmentioning

confidence: 99%

Joint communication and radar sensing in 5G mobile network by compressive sensing

et al. 2020

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Radio sensing can be integrated with communication in what the authors call future perceptive mobile networks. Due to the complicated signal structure, it is challenging to estimate sensing parameters such as delay, angle of arrival, and Doppler when joint communication and radar/radio sensing is applied in perceptive mobile networks. Radio sensing with signals compatible with a fifth-generation (5G) new radio standard using one-dimension (1D) to 3D compressive sensing (CS) techniques under 5G channel conditions is studied. In the case of 1D-3D CS techniques, they formulate the parameter estimation as a sparse signal recovery problem. These algorithms demonstrate respective advantages, but also show shortcomings in dealing with clustered channels. To effectively exploit the cluster structure in multipath channels, they also propose a 2D cluster Kronecker CS algorithm for significantly improved sensing parameter estimation via introducing a prior probability distribution. Simulation results are provided and they focus the respective advantages and disadvantages of these techniques that validate the effectiveness of the proposed algorithms.

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An Indoor mmWave Joint Radar and Communication System with Active Channel Perception

Cited by 21 publications

References 15 publications

Joint Multi-User Communication and Sensing Exploiting Both Signal and Environment Sparsity

Joint Multi-User Communication and Sensing Exploiting Both Signal and Environment Sparsity

Protein–polysaccharide interactions and aggregates in food formulations

Joint communication and radar sensing in 5G mobile network by compressive sensing

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