Performance of Joint Sensing-Communication Cooperative Sensing UAV Network

Chen, Xu; Feng, Zhiyong; Wei, Zhiqing; Gao, Feifei; Yuan, Xin

doi:10.1109/tvt.2020.3042466

Cited by 69 publications

(30 citation statements)

References 21 publications

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“…However, inter-user and sensing interference is crucial to be re-assessed in this JSAC model because of the radar performance degradation compared to the original radaronly systems. Furthermore, within the context of large-scale monitoring areas for applications such as smart farming, the authors in [84] evaluated a coordinated sensing coverage of a large-scale unmanned aerial vehicles (UAV) communication network based on the average perceptual interference of UAVs and the communication capacity limits. Another large-scale sensory network was proposed in [85] which uses grant-free non-orthogonal multiple-accessing (NOMA) as an emerging JSAC technique in massive M2M communications for reducing signaling overhead.…”

Section: B Large-scale Multi-user Jsacmentioning

confidence: 99%

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 Large-scale Multi-user Jsacmentioning

confidence: 99%

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

Kim

Choi

2022

IEEE Access

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“…Second, in addition to shared spectrum, when the hardware is shared, the integration of communication and sensing is achieved at a higher level in the dual-functional communication-sensing systems [6]. A direct way to implement such a system is to design a timesharing scheme [17] or a beam-sharing scheme [18], which reduces the cost, size and weight of the system. Alternatively, a common transmitted waveform can be jointly designed and used for communication and sensing, including integrating communication information into radar [19] and realizing sensing in communication systems [20]- [23].…”

Section: A Related Workmentioning

confidence: 99%

Sensing Integrated DFT-Spread OFDM Waveform and Deep Learning-powered Receiver Design for Terahertz Integrated Sensing and Communication Systems

Wu¹,

Lemić²,

Han³

et al. 2021

Preprint

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Terahertz (THz) communications are envisioned as a key technology of next-generation wireless systems due to its ultra-broad bandwidth. One step forward, THz integrated sensing and communication (ISAC) system can realize both unprecedented data rates and millimeter-level accurate sensing. However, THz ISAC meets stringent challenges on waveform and receiver design, to fully exploit the peculiarities of THz channel and transceivers. In this work, a sensing integrated discrete Fourier transform spread orthogonal frequency division multiplexing (SI-DFT-s-OFDM) system is proposed for THz ISAC, which can provide lower peak-to-average power ratio than OFDM and is adaptive to flexible delay spread of the THz channel. Without compromising communication capabilities, the proposed SI-DFT-s-OFDM realizes millimeter-level range estimation and decimeter-per-second-level velocity estimation accuracy.In addition, the bit error rate (BER) performance is improved by 5 dB gain at the 10 -3 BER level compared with OFDM. At the receiver, a two-level multi-task neural network based ISAC detector is developed to jointly recover transmitted data and estimate target range and velocity, while mitigating the imperfections and non-linearities of THz systems. Extensive simulation results demonstrate that the

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“…In [25], the authors used the orthogonal frequency division multiplexing communication waveform as a radar signal to achieve joint communication and environment sensing between vehicles. As an illustration of joint sensing and communication signaling, the authors in [26] designed a cooperative sensing unmanned aerial vehicle network (CSUN) with joint sensing and communication beams based on a common transceiver device. Considering the nonideal factors of the channel, [27] analyzed the communication channel capacity under the joint effect of Gaussian random noise and non-Gaussian radar sensing interference.…”

Section: B Related Workmentioning

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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Performance of Joint Sensing-Communication Cooperative Sensing UAV Network

Cited by 69 publications

References 21 publications

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

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

Sensing Integrated DFT-Spread OFDM Waveform and Deep Learning-powered Receiver Design for Terahertz Integrated Sensing and Communication Systems

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

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