Joint Communication and Radar Sensing with Reconfigurable Intelligent Surfaces

Sankar, R. S. Prasobh; Deepak, Battu; Chepuri, Sundeep Prabhakar

doi:10.1109/spawc51858.2021.9593143

Cited by 48 publications

(24 citation statements)

References 12 publications

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“…■ Proposition 5 shows that the CRB for the TRM estimation does not rely on the design of the IRS reflective beamforming. By comparing (25) and (44) presented in Proposition 1 and Proposition 5, one can observe that the CRB increases with σ 2 R and decreases with T under both cases. Moreover, it can be seen that more sensors degrade the sensing performance under the extended target case, whereas it results in a lower CRB under the point target case, which is explained in Section III.…”

Section: A Estimation Performance Evaluation Via Crbmentioning

confidence: 90%

“…Proposition 1: Under the point target case, the CRB for the DoA estimation is expressed in (25) on the top of this page.…”

Section: Crb Analysis and Optimization For Point Target Casementioning

confidence: 99%

“…In [24], IRS was deployed to control the echoes by tuning its phase shifts for enhancing the signal-to-noise ratio (SNR). In [25], [26], a codebook design was proposed to minimize the localization error probability while meeting the users' quality-of-service requirement. [27] investigated an intelligent omni-surface-enabled ISAC system, where the minimum SNR was maximized for sensing while accounting for communication requirements.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent Reflecting Surface Enabled Multi-Target Sensing

Meng

Schober³

et al. 2022

IEEE Trans. Commun.

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Intelligent reflecting surface (IRS) has garnered growing interest and attention due to its potential for facilitating and supporting wireless communications and sensing. This paper studies a semi-passive IRS-enabled sensing system, where an IRS consists of both passive reflecting elements and active sensors. Our goal is to minimize the Cramér-Rao bound (CRB) for parameter estimation under both point and extended target cases. Towards this goal, we begin by deriving the CRB for the direction-of-arrival (DoA) estimation in closed-form and then theoretically analyze the IRS reflecting elements and sensors allocation design based on the CRB under the point target case with a single-antenna base station (BS). To efficiently solve the corresponding optimization problem for the case with a multi-antenna BS, we propose an efficient algorithm by jointly optimizing the IRS phase shifts and the BS beamformers. Under the extended target case, the CRB for the target response matrix (TRM) estimation is minimized via the optimization of the BS transmit beamformers. Moreover, we explore the influence of various system parameters on the CRB and compare these effects to those observed under the point target case. Simulation results show the effectiveness of the semi-passive IRS and our proposed beamforming design for improving the performance of the sensing system.

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Section: A Estimation Performance Evaluation Via Crbmentioning

confidence: 90%

“…Proposition 1: Under the point target case, the CRB for the DoA estimation is expressed in (25) on the top of this page.…”

Section: Crb Analysis and Optimization For Point Target Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Intelligent Reflecting Surface Enabled Multi-Target Sensing

Meng

Schober³

et al. 2022

IEEE Trans. Commun.

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“…The achievable rate and MSE exhibit different variations versus the IRS beam scanning time. As the time of beam scanning increases, the IRS beamforming gain (14) in the case of δ u = 1 L increases at the expense of reduced data transmission time, leading to an initial increase and subsequent decrease in the achievable rate. In the case of δ u = 0, the IRS beamforming gain already reaches its peak when L = M .…”

Section: A Communication and Sensing Trade-off In Phase Imentioning

confidence: 99%

Performance Analysis of Agile-Beam NOMA in Millimeter Wave Networks

Jing

Zhang

et al. 2020

IEEE Access

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We propose an agile-beam non-orthogonal multiple access (NOMA) scheme for millimeter wave (mmWave) communication networks. The agile-beam NOMA scheme flexibly switches between the single/multi-beam NOMA depending on the user pairing results. In particular, a novel user pairing strategy employing both distance and angle information is designed to facilitate the agile-beam NOMA transmission. More specifically, the base station first selects one user from the far user group randomly and then pairs it with the user that has the minimum angle difference in the near user group. This pairing strategy efficiently exploits the channel sparsity in user domain while supporting flexible mmWave transmission with agilebeam NOMA. Then an in-depth performance analysis is carried out to reveal the interplay between the key system parameters and the coverage probability of the proposed agile-beam NOMA by using the tool of stochastic geometry. Moreover, numerical results demonstrate the superiority of the proposed agile-beam NOMA over the conventional NOMA and orthogonal multiple access (OMA) in mmWave communication networks. INDEX TERMS Millimeter wave (mmWave) communication, non-orthogonal multiple access (NOMA), user pairing.

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“…To enable the co-existence of radar and communication functions, the authors of [38] propose to use RISs to minimize the interference between communication and radar functions; the authors of [39] propose to deploy two RISs near the transmitter and receiver to enhance the communication signals and suppress the mutual interference. As for the design of ISAC signals, the authors of [36] show that RISs can either increase or maintain the data rate, and can offer accurate users localization and tracking performance; the authors of [40] design a low-complexity codebook which can achieve a desired localization probability of error; the authors of [41] propose to use RISs to enhance the detection performance of ISAC systems in crowded areas, while satisfying the communication signal-noise ratio (SNR) constraints; the authors of [42] point out that the degrees-of-freedom of transmit beamforming are limited when synthesizing the desired transmit beampattern and proposes to use RISs to minimize the multi-user interference. Additionally, the authors of [43] explore the performance of ISAC systems in the terahertz (THz) band.…”

mentioning

confidence: 99%

Joint Beamforming for RIS-Assisted Integrated Sensing and Communication Systems

Xu¹,

Li²,

Andrew³

et al. 2023

Preprint

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Integrated sensing and communications (ISAC) is emerging as a critical technique for next-generation communication systems. Reconfigurable intelligent surface (RIS) can simultaneously enhance the performance of communication and sensing by introducing new degrees-of-freedom for beamforming in ISAC systems. This paper proposes two optimization techniques for joint beamforming in RIS-assisted ISAC systems. We first aim to maximize the radar mutual information (MI) by imposing constraints on communication rate, transmit power, and unit modulus reflection coefficients at the RIS. An alternating optimization (AO) algorithm based on the semidefinite relaxation (SDR) method is proposed to solve the optimization problem by introducing a convergence-accelerating method. To achieve lower computational complexity and better reliability, we then formulate a new optimization problem for maximizing the weighted ISAC performance metrics under fewer constraints. An AO algorithm based on the Riemannian gradient (RG) method is proposed to solve this problem. This is achieved by reformulating the transmit and RIS beamforming on the complex hypersphere manifold and complex circle manifold, respectively.Numerical results show that the proposed algorithms can enhance the radar MI and the weighted communication rate simultaneously. The AO algorithm based on RG exhibits better performance than the SDR-based method. I. INTRODUCTION Many emerging applications for future networks, such as vehicle-to-everything and smart homes, require high-quality communication performance and demand accurate sensing capabilities [1], [2]. The communication and sensing functionality can be simultaneously realized in a unified platform due to their similar hardware architecture and signal processing algorithms. Y. Xu and Y. Li are with the

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Joint Communication and Radar Sensing with Reconfigurable Intelligent Surfaces

Cited by 48 publications

References 12 publications

Intelligent Reflecting Surface Enabled Multi-Target Sensing

Intelligent Reflecting Surface Enabled Multi-Target Sensing

Performance Analysis of Agile-Beam NOMA in Millimeter Wave Networks

Joint Beamforming for RIS-Assisted Integrated Sensing and Communication Systems

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