RIS-aided User Tracking in Near-Field MIMO Systems: Joint Precoding Design and RIS Optimization

Palmucci, Silvia; Guerra, Anna; Abrardo, Andrea; Dardari, Davide

doi:10.48550/arxiv.2212.07333

Cited by 3 publications

(4 citation statements)

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“…Focusing on the specific case of NF localization, many other RIS optimization schemes have been put forward, such as SNR maximization in [25] and [26] and DFT matrices in [27]. On the other hand, a traditional randomized RIS phase design was considered in [28] to achieve bi-static localization of the RIS.…”

Section: Related State Of the Artmentioning

confidence: 99%

Performance of RIS-Aided Nearfield Localization under Beams Approximation from Real Hardware Characterization

RAHAL

Denis

Keykhosravi

et al. 2023

Preprint

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The technology of reconfigurable intelligent surfaces (RIS) has been showing promising potential in a variety of applications relying on Beyond-5G networks. Reconfigurable intelligent surface (RIS) can indeed provide fine channel flexibility to improve communication quality of service (QoS) or restore localization capabilities in challenging operating conditions, while conventional approaches fail (e.g., due to insufficient infrastructure, severe radio obstructions). In this paper, we tackle a general low-complexity approach for optimizing the precoders that control such reflective surfaces under hardware constraints. More specifically, it allows the approximation of any desired beam pattern using a pre-characterized look-up table of feasible complex reflection coefficients for each RIS element. The proposed method is first evaluated in terms of beam fidelity for several examples of RIS hardware prototypes. Then, by means of a theoretical bounds analysis, we examine the impact of RIS beams approximation on the performance of near-field downlink positioning in non-line-of-sight conditions, while considering several RIS phase profiles (incl. directional, random and localization-optimal designs). Simulation results in a canonical scenario illustrate how the introduced RIS profile optimization scheme can reliably produce the desired RIS beams under realistic hardware limitations. They also highlight its sensitivity to both the underlying hardware characteristics and the required beam kinds in relation to the specificity of RIS-aided localization applications. First part title: Text for this section. Second part title: Text for this section.

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Section: Related State Of the Artmentioning

confidence: 99%

Performance of RIS-Aided Nearfield Localization under Beams Approximation from Real Hardware Characterization

RAHAL

Denis

Keykhosravi

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Focusing on the specific case of NF localization, many other RIS optimization schemes have been put forward, such as SNR maximization in [25,26] and DFT matrices in [27]. On the other hand, a traditional randomized RIS phase design was considered in [28] to achieve bi-static localization of the RIS.…”

Section: Related State Of the Artmentioning

confidence: 99%

“…The paper [33] proposes the use of differential data to determine the best beam for the RIS. Furthermore, [34] explores a joint design of the reflection coefficients of multiple RISs and the precoding strategy of a single BS to optimize the tracking of the position and velocity of a single UE with an iterative block coordinate descent algorithm.…”

Section: Related State Of the Artmentioning

confidence: 99%

Performance of RIS-aided near-field localization under beams approximation from real hardware characterization

Rahal,

Denis,

Keykhosravi

et al. 2023

J Wireless Com Network

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The technology of reconfigurable intelligent surfaces (RISs) has been showing promising potential in a variety of applications relying on Beyond-5G networks. RIS can indeed provide fine channel flexibility to improve communication quality of service (QoS) or restore localization capabilities in challenging operating conditions, while conventional approaches fail (e.g., due to insufficient infrastructure, severe radio obstructions). In this paper, we tackle a general low-complexity approach for optimizing the precoders that control such reflective surfaces under hardware constraints. More specifically, it allows the approximation of any desired beam pattern using a pre-characterized lookup table of feasible complex reflection coefficients for each RIS element. The proposed method is first evaluated in terms of beam fidelity for several examples of RIS hardware prototypes. Then, by means of a theoretical bounds analysis, we examine the impact of RIS beams approximation on the performance of near-field downlink positioning in non-line-of-sight conditions, while considering several RIS phase profiles (including directional, random and localization-optimal designs). Simulation results in a canonical scenario illustrate how the introduced RIS profile optimization scheme can reliably produce the desired RIS beams under realistic hardware limitations. They also highlight its sensitivity to both the underlying hardware characteristics and the required beam kinds in relation to the specificity of RIS-aided localization applications.

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“…In (3), the path to and from the RIS appear together, so that without suitable processing, up to 2L + 1 path will be present. To avoid this, we propose a method to separate the UE-SP-RIS-UE paths (second term in (3)) from the UE-RIS-SP-UE paths (first term in (3)), by designing the precoder and combiner at the UE, inspired by the approach from [19]. In particular, we divide up the T /2 available transmissions into T 1 transmissions towards the RIS, with fk, t = a * U (θ k,0 )/∥a U (θ)∥ and T 2 = T /2 − T 1 transmissions with a null towards the RIS, i.e., with f H k, ta U (θ k,0 ) = 0.…”

Section: B Separation Of the Ris Signalsmentioning

confidence: 99%

RIS-Aided Monostatic Sensing and Object Detection with Single and Double Bounce Multipath

Kim,

Fascista,

Chen

et al. 2023

2023 IEEE International Conference on Communications Workshops (ICC Workshops)

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We propose a framework for monostatic sensing by a user equipment (UE), aided by a reconfigurable intelligent surface (RIS) in environments with single-and double-bounce signal propagation. We design appropriate UE-side precoding and combining, to facilitate signal separation. We derive the adaptive detection probabilities of the resolvable signals, based on the geometric channel parameters of the links. Then, we estimate the passive objects using both the double-bounce signals via passive RIS (i.e., RIS-sensing) and the single-bounce multipath direct to the objects (i.e., non-RIS-sensing), based on a mapping filter. Finally, we provide numerical results to demonstrate that effective sensing can be achieved through the proposed framework.

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RIS-aided User Tracking in Near-Field MIMO Systems: Joint Precoding Design and RIS Optimization

Cited by 3 publications

References 0 publications

Performance of RIS-Aided Nearfield Localization under Beams Approximation from Real Hardware Characterization

Performance of RIS-Aided Nearfield Localization under Beams Approximation from Real Hardware Characterization

Performance of RIS-aided near-field localization under beams approximation from real hardware characterization

RIS-Aided Monostatic Sensing and Object Detection with Single and Double Bounce Multipath

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