Integrated Sensing and Communication-assisted Orthogonal Time Frequency Space Transmission for Vehicular Networks

Yuan, Weijie; Wei, Zhiqiang; Li, Shuangyang; Yuan, Jinhong; Ng, Derrick Wing Kwan

doi:10.48550/arxiv.2105.03125

Cited by 5 publications

(8 citation statements)

References 38 publications

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“…Each component in ( 16) is a unitary DFT of the corresponding component given in (13). Thus, with reference to the proof of Lemma 1 established in Appendix A, we can readily show the white Gaussian nature of the four components in (16). The details are suppressed for brevity.…”

Section: B Proof Of Lemmamentioning

confidence: 93%

“…Third, using sensing results to assist communications can further enhance the energy-efficiency of JCAS. A recent work [16] shows the benefit of doing so in the vehicular network. More studies are necessary to account for the unique needs/features of IIoT applications.…”

Section: Conclusion and Remarksmentioning

confidence: 99%

“…The channel matrices are generated based on pre-selected delay-Doppler grids. In [16] and [17], matched filtering is performed for OTFS sensing, where the filter coefficients are constructed on pre-defined delay-Doppler grids. Different from the above works [15]- [17] focusing on the delay-Doppler domain, the work [13] develops a generalized likelihood ratio test (GLRT) detector in the time domain, where the inter-carrier interference (ICI) and inter-symbol interference (ISI) are used to surpass the ambiguity barrier.…”

Section: Introductionmentioning

confidence: 99%

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OTFS-Based Joint Communication and Sensing for Future Industrial IoT

Wu¹,

Zhang²,

Huang³

et al. 2021

Preprint

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Effective wireless communications are increasingly important in maintaining the successful closed-loop operation of mission-critical industrial Internet-of-Things (IIoT) applications. To meet the ever-increasing demands on better wireless communications for IIoT, we propose an orthogonal time-frequency space (OTFS) waveform-based joint communication and radio sensing (JCAS) scheme -an energy-efficient solution for not only reliable communications but also high-accuracy sensing. OTFS has been demonstrated to have higher reliability and energy efficiency than the currently popular IIoT communication waveforms. JCAS has also been highly recommended for IIoT, since it saves cost, power and spectrum compared to having two separate radio frequency systems. Performing JCAS based on OTFS, however, can be hindered by a lack of effective OTFS sensing. This paper is dedicated to filling this technology gap. We first design a series of echo pre-processing methods that successfully remove the impact of communication data symbols in the timefrequency domain, where major challenges, like inter-carrier and inter-symbol interference and noise amplification, are addressed. Then, we provide a comprehensive analysis of the signal-tointerference-plus-noise ratio (SINR) for sensing and optimize a key parameter of the proposed method to maximize the SINR. Extensive simulations show that the proposed sensing method approaches the maximum likelihood estimator with respect to the estimation accuracy of target parameters and manifests applicability to wide ranges of key system parameters. Notably, the complexity of the proposed method is only dominated by a two-dimensional Fourier transform.Index Terms-Internet-of-Things (IoT), industrial IoT (IIoT), orthogonal time-frequency space (OTFS), joint communication and radar/radio sensing (JCAS), range/velocity estimation.

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Section: B Proof Of Lemmamentioning

confidence: 93%

Section: Conclusion and Remarksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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OTFS-Based Joint Communication and Sensing for Future Industrial IoT

Wu¹,

Zhang²,

Huang³

et al. 2021

Preprint

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“…To meet the high demands of future 6G systems in terms of both communication and sensing, the concept of smart radio environment has been recently proposed [9], which essentially leverages the digitally-controlled metasurface, termed intelligent reflecting surface (IRS) (or reconfigurable intelligent surface (RIS) equivalently), to reconfigure the wireless propagation environment in favor of both wireless communication and radar sensing [10]- [14]. In particular, by dynamically controlling phase shifts via a large number low-cost reflecting elements, IRS is able to realize many desired functions, such as bypassing environment obstacles, reshaping channel realizations/distributions, and increasing the multi-antenna/MIMO channel rank.…”

Section: Introductionmentioning

confidence: 99%

Target Sensing with Intelligent Reflecting Surface: Architecture and Performance

Shao¹,

You²,

Ma³

et al. 2022

Preprint

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Intelligent reflecting surface (IRS) has emerged as a promising technology to reconfigure the radio propagation environment by dynamically controlling wireless signal's amplitude and/or phase via a large number of reflecting elements. In contrast to the vast literature on studying IRS's performance gains in wireless communications, we study in this paper a new application of IRS for sensing/localizing targets in wireless networks. Specifically, we propose a new self-sensing IRS architecture where the IRS controller is capable of transmitting probing signals that are not only directly reflected by the target (referred to as the direct echo link), but also consecutively reflected by the IRS and then the target (referred to as the IRSreflected echo link). Moreover, dedicated sensors are installed at the IRS for receiving both the direct and IRS-reflected echo signals from the target, such that the IRS can sense the direction of its nearby target by applying a customized multiple signal classification (MUSIC) algorithm. However, since the angle estimation mean square error (MSE) by the MUSIC algorithm is intractable, we propose to optimize the IRS passive reflection for maximizing the average echo signals' total power at the IRS sensors and derive the resultant Cramer-Rao bound (CRB) of the angle estimation MSE. Last, numerical results are presented to show the effectiveness of the proposed new IRS sensing architecture and algorithm, as compared to other benchmark sensing systems/algorithms.

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“…In the case of a single target, solving an MLD can be done through a matching filter. This is performed in [23] and [24]. In [25], an MLD problem for RCP-OTFS sensing is formulated in the time domain which, as claimed therein, provides more insight compared with the MLD in the delay-Doppler domain.…”

Section: Introductionmentioning

confidence: 99%

Integrating Low-Complexity and Flexible Sensing into Communication Systems

Wu¹,

Zhang²,

Huang³

et al. 2021

Preprint

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Integrating sensing into standardized communication systems can potentially benefit many consumer applications that require both radio frequency functions. However, without an effective sensing method, such integration may not achieve the expected gains of cost and energy efficiency. Existing sensing methods, which use communication payload signals, either have limited sensing performance or suffer from high complexity. In this paper, we develop a novel and flexible sensing framework which has a complexity only dominated by a Fourier transform and also provides the flexibility in adapting for different sensing needs. We propose to segment a whole block of echo signal evenly into sub-blocks; adjacent ones are allowed to overlap. We design a virtual cyclic prefix (VCP) for each sub-block that allows us to employ two common ways of removing communication data symbols and generate two types of range-Doppler maps (RDMs) for sensing. We perform a comprehensive analysis of the signal components in the RDMs, proving that their interferenceplus-noise (IN) terms are approximately Gaussian distributed. The statistical properties of the distributions are derived, which leads to the analytical comparisons between the two RDMs as well as between the prior and our sensing methods. Moreover, the impact of the lengths of sub-block, VCP and overlapping signal on sensing performance is analyzed. Criteria for designing these lengths for better sensing performance are also provided. Extensive simulations validate the superiority of the proposed sensing framework over prior methods in terms of signal-to-IN ratios in RDMs, detecting performance and flexibility.

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Integrated Sensing and Communication-assisted Orthogonal Time Frequency Space Transmission for Vehicular Networks

Cited by 5 publications

References 38 publications

OTFS-Based Joint Communication and Sensing for Future Industrial IoT

OTFS-Based Joint Communication and Sensing for Future Industrial IoT

Target Sensing with Intelligent Reflecting Surface: Architecture and Performance

Integrating Low-Complexity and Flexible Sensing into Communication Systems

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