Target Sensing With Intelligent Reflecting Surface: Architecture and Performance

Shao, Xiaodan; You, Changsheng; Ma, Wenyan; Chen, Xiaoming; Zhang, Rui

doi:10.1109/jsac.2022.3155546

Cited by 150 publications

(40 citation statements)

References 45 publications

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“…Furthermore, multipaths due to wider band create an environment in which the first arriving paths do not contain the maximum energy. An IRS could be employed as a self-sensing architecture that could help determine the departure and arrival angles by employing the MUSIC, ESPIRIT, maximum likelihood, etc., algorithms [ 43 , 44 ]. An IRS-aided localization for indoor communications could resolve the object within centimetres which is not currently possible with BLE or WiFi standards.…”

Section: Conclusion Future Work and Limitationmentioning

confidence: 99%

“…Therefore, this survey provides a more detailed discussion on IRS technology and covers historical concepts, nomenclature, system architecture and design, an IRS-aided wireless network deployment and performance, smart radio channels with an an IRS and the limitations of the existing works and key future research directions. Furthermore, this survey covers several recent research advancements such as IRS-assisted UAV or UAV-satellite systems [ 38 , 39 ], an IRS aided for mobile edge computing [ 40 , 41 ], IRS-aided multiuser communication [ 42 ], IRS-aided localization [ 43 , 44 ], IRS-aided vehicular communications [ 45 ] and IRS-aided power transfer [ 46 , 47 ]. Finally, this survey discusses the current research gaps/opportunities and the possible solutions.…”

Section: Introductionmentioning

confidence: 99%

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Design and Application of Intelligent Reflecting Surface (IRS) for Beyond 5G Wireless Networks: A Review

Okogbaa

Ahmed

Khan

et al. 2022

Sensors

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The existing sub-6 GHz band is insufficient to support the bandwidth requirement of emerging data-rate-hungry applications and Internet of Things devices, requiring ultrareliable low latency communication (URLLC), thus making the migration to millimeter-wave (mmWave) bands inevitable. A notable disadvantage of a mmWave band is the significant losses suffered at higher frequencies that may not be overcome by novel optimization algorithms at the transmitter and receiver and thus result in a performance degradation. To address this, Intelligent Reflecting Surface (IRS) is a new technology capable of transforming the wireless channel from a highly probabilistic to a highly deterministic channel and as a result, overcome the significant losses experienced in the mmWave band. This paper aims to survey the design and applications of an IRS, a 2-dimensional (2D) passive metasurface with the ability to control the wireless propagation channel and thus achieve better spectral efficiency (SE) and energy efficiency (EE) to aid the fifth and beyond generation to deliver the required data rate to support current and emerging technologies. It is imperative that the future wireless technology evolves toward an intelligent software paradigm, and the IRS is expected to be a key enabler in achieving this task. This work provides a detailed survey of the IRS technology, limitations in the current research, and the related research opportunities and possible solutions.

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Section: Conclusion Future Work and Limitationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and Application of Intelligent Reflecting Surface (IRS) for Beyond 5G Wireless Networks: A Review

Okogbaa

Ahmed

Khan

et al. 2022

Sensors

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“…In this section, we propose to jointly optimize the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the CRLB for DoA estimation in (8) or (11), subject to the maximum transmit power constraint at the AP. Note that in order to implement the joint beamforming design, we assume that the AP roughly knows the information of θ, which is practically valid for a target tracking scenario.…”

Section: Joint Beamforming Design For Crlb Minimizationmentioning

confidence: 99%

“…First, we optimize the transmit beamformer R x in problem (P1) under any given reflective beamformer v, in which the CRLB formula in (8)…”

Section: A Transmit Beamforming Optimizationmentioning

confidence: 99%

“…For instance, the work [7] presented the NLoS radar equation based on the AP-IRS-target-IRS-AP link and evaluated the resultant sensing performance in terms of signal-to-noise ratio (SNR) and signal-to-clutter ratio (SCR). In [8], the authors considered an IRS-enabled bi-static target estimation, where dedicated sensors were installed at the IRS for estimating the direction of its nearby target through the AP-IRS-targetsensors link. Under this setup, the authors optimized the IRS's reflective beamforming to maximize the average received signal power at the sensors and applied the multiple signal classification (MUSIC) algorithm for estimating targets.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound Optimization

Song¹,

Xu²,

Liu³

et al. 2022

Preprint

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This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is dedicatedly deployed to assist an access point (AP) to sense a target at its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. The AP aims to estimate the target's direction-of-arrival (DoA) with respect to the IRS based on the echo signal from the AP-IRS-target-IRS-AP link. Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the DoA estimation error in terms of Cramér-Rao lower bound (CRLB). Towards this end, we first obtain the closed-form expression of CRLB for DoA estimation. Next, we optimize the joint beamforming design to minimize the obtained CRLB, via alternating optimization, semi-definite relaxation, and successive convex approximation. Finally, numerical results show that the proposed design based on CRLB minimization achieves improved sensing performance in terms of lower estimation mean squared error (MSE), as compared to the traditional schemes with signalto-noise ratio maximization and separate beamforming designs.

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RIS‐Aided Low Complexity Waveform Design for Joint Sensing and Communications

Tsinos,

Dash,

Kaushik

et al. 2024

Intelligent Spectrum Management

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Target Sensing With Intelligent Reflecting Surface: Architecture and Performance

Cited by 150 publications

References 45 publications

Design and Application of Intelligent Reflecting Surface (IRS) for Beyond 5G Wireless Networks: A Review

Design and Application of Intelligent Reflecting Surface (IRS) for Beyond 5G Wireless Networks: A Review

Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound Optimization

RIS‐Aided Low Complexity Waveform Design for Joint Sensing and Communications

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