Compressive Near-Field Localization for Multipath RIS-Aided Environments

Rinchi, Omar; Elzanaty, Ahmed; Alouini, Mohamed‐Slim

doi:10.1109/lcomm.2022.3151036

Cited by 47 publications

(37 citation statements)

References 20 publications

(26 reference statements)

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“…In the considered setting, the BS broadcasts a narrowband signal s t over T transmissions under the constraint of E{|s t | 2 } = E s . For simplicity, we assume that s t = √ E s for any t. Assuming LoS blockage [17], [29] and the absence of uncontrolled multipath, the signal received by the UE involves only reflections from the RIS and can be expressed at transmission t as where α is the unknown channel gain, w t = [w t,1 . .…”

Section: A Geometry and Signal Modelmentioning

confidence: 99%

“…Most studies on RIS localization have considered ideal phase shifters (e.g. [17], [26]- [29], [31], [39]), omitting the listed impairments. How these proposed localization approaches fare under these impairments is both unknown and important.…”

mentioning

confidence: 99%

“…In this manuscript, we investigate the problem of RIS-aided geometric near-field localization of a single-antenna UE served by a single-antenna BS under LoS blockage [17], [29], [31], [40], considering a realistic RIS amplitude model [36], which relies on equivalent circuit models of individual reflecting elements. Specifically, we quantify degradation in localization performance due to mismatch between an ideal model with unit-amplitude RIS element responses and a realistic model with phase-dependent amplitude variations [36], [41], by resorting to the MCRB analysis [42].…”

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confidence: 99%

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RIS-aided Near-Field Localization under Phase-Dependent Amplitude Variations

Ozturk¹,

Keskin²,

Wymeersch³

et al. 2022

Preprint

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We investigate the problem of reconfigurable intelligent surface (RIS)-aided near-field localization of a user equipment (UE) served by a base station (BS) under phasedependent amplitude variations at each RIS element. Through a misspecified Cramér-Rao bound (MCRB) analysis and a resulting lower bound (LB) on localization, we show that when the UE is unaware of amplitude variations (i.e., assumes unit-amplitude responses), severe performance penalties can arise, especially at high signal-to-noise ratios (SNRs). Leveraging Jacobi-Anger expansion to decouple range-azimuth-elevation dimensions, we develop a low-complexity approximated mismatched maximum likelihood (AMML) estimator, which is asymptotically tight to the LB. To mitigate performance loss due to model mismatch, we propose to jointly estimate the UE location and the RIS amplitude model parameters. The corresponding Cramér-Rao bound (CRB) is derived, as well as an iterative refinement algorithm, which employs the AMML method as a subroutine and alternatingly updates individual parameters of the RIS amplitude model. Simulation results indicate fast convergence and performance close to the CRB. The proposed method can successfully recover the performance loss of the AMML under a wide range of RIS parameters and effectively calibrate the RIS amplitude model online with the help of a user that has an a-priori unknown location.

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Section: A Geometry and Signal Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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RIS-aided Near-Field Localization under Phase-Dependent Amplitude Variations

Ozturk¹,

Keskin²,

Wymeersch³

et al. 2022

Preprint

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“…Remark 2 (Practical estimators): While our analysis is limited to performance bounds, it is expected that practical algorithms can achieve these bounds, when operating in a high SNR regime. Low-complexity NF localization methods were for instance discussed in [6], [24]. We also note that the proposed RIS phase profile designs involve only limited signaling or control overhead, since only the current user location needs to be provided to the RIS controller.…”

Section: A Simulation Parametersmentioning

confidence: 99%

Constrained RIS Phase Profile Optimization and Time Sharing for Near-field Localization

Rahal¹,

Denis²,

Keykhosravi³

et al. 2022

Preprint

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The rising concept of reconfigurable intelligent surface (RIS) has promising potential for Beyond 5G localization applications. We herein investigate different phase profile designs at a reflective RIS, which enable non-line-of-sight positioning in nearfield from downlink single antenna transmissions. We first derive the closed-form expressions of the corresponding Fisher information matrix (FIM) and position error bound (PEB). Accordingly, we then propose a new localization-optimal phase profile design, assuming prior knowledge of the user equipment location. Numerical simulations in a canonical scenario show that our proposal outperforms conventional RIS random and directional beam codebook designs in terms of PEB. We also illustrate the four beams allocated at the RIS (i.e., one directional beam, along with its derivatives with respect to space dimensions) and show how their relative weights according to the optimal solution can be practically implemented through time sharing (i.e., considering feasible beams sequentially).

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“…With this development, the RIS-based localization methods have also been exploited recently. In [15], a near-field localization method is addressed using compressed sensing (CS), and authors of [16] proposed a JCR system with RIS.…”

Section: Introductionmentioning

confidence: 99%

A RIS-Based Passive DOA Estimation Method for Integrated Sensing and Communication System

Chen¹,

Chen²,

Wang³

2022

Preprint

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Integrated sensing and communication (ISAC) system has received growing attention, especially in the context of B5G/6G development. Combining the reconfigurable intelligent surface (RIS) with wireless communication process, a novel passive sensing technique is formulated in this paper to estimate the direction of arrival (DOA) of the targets, where the control matrix of the RIS is used to to realize the multiple measurements with only one full-functional receiving channel. Unlike the existing methods, the interference signals introduced by wireless communication are also considered. To improve the DOA estimation, a novel atomic norm-based method is proposed to remove the interference signals by the sparse reconstruction. The DOA is estimated after the interference removal by a novel Hankel-based multiple signal classification (MUSIC) method. Then, an optimization method is also developed for the measurement matrix to reduce the power interference signals and keep the measurement matrix's randomness, which guarantees the performance of the sparse reconstruction. Finally, we derive the theoretical Cramér-Rao lower bound (CRLB) for the proposed system on the DOA estimation. Simulation results show that the proposed method outperforms the existing methods in the DOA estimation and shows the corresponding CRLB with different distributions of the sensing node. The code about the proposed method is available online https://github.com/chenpengseu/ PassiveDOA-ISAC-RIS.git.

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Compressive Near-Field Localization for Multipath RIS-Aided Environments

Cited by 47 publications

References 20 publications

RIS-aided Near-Field Localization under Phase-Dependent Amplitude Variations

RIS-aided Near-Field Localization under Phase-Dependent Amplitude Variations

Constrained RIS Phase Profile Optimization and Time Sharing for Near-field Localization

A RIS-Based Passive DOA Estimation Method for Integrated Sensing and Communication System

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