References of "Liu, Yuan 50046885"
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See detailRecursive UE Localization for a Multi-RIS-Assisted Wireless System in an Obstacle-Dense Environment
Zhao, Sibo; Liu, Yuan UL; Wu, Linlong UL et al

in 2023 17th European Conference on Antennas and Propagation (EuCAP) (2023, March)

Accurate user equipment (UE) localization in an obstacle-dense environment is quite challenging due to the insufficiency of line-of-sight (LoS) links. However, the reconfigurable intelligent surface (RIS ... [more ▼]

Accurate user equipment (UE) localization in an obstacle-dense environment is quite challenging due to the insufficiency of line-of-sight (LoS) links. However, the reconfigurable intelligent surface (RIS) has the potential for offering alternative RIS-assisted LoS links to refine the localization results. In this paper, a recursive localization scheme is proposed based on an iterative RIS selection strategy, with the help of prior knowledge of the propagation environment. And numerical results based on a geometry-based channel simulator in a typical composite urban environment exhibit the improvement of localization accuracy. [less ▲]

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See detailA 3D Indoor Localization Approach Based on Spherical Wave-front and Channel Spatial Geometry
Liu, Yuan UL; Wu, Linlong UL; Alaeekerahroodi, Mohammad UL et al

in Liu, Yuan; Wu, Linlong; Alaeekerahroodi, Mohammad (Eds.) et al 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM) (2022, June)

Because of the near-field nature of radio propagation, spherical wave-front and multipath effect are prominent in indoor scenarios, making localization even more difficult. In this paper, we propose a ... [more ▼]

Because of the near-field nature of radio propagation, spherical wave-front and multipath effect are prominent in indoor scenarios, making localization even more difficult. In this paper, we propose a three-dimensional (3D) indoor localization algorithm that takes these issues into account. Specifically, we first adopted a high-resolution channel parameter estimation method for path delays based on the Space-Alternating Generalized Expectation-maximization (SAGE), and then these path delays are adopted in the 3D localization principles based on the target-antenna geometry. The proposed algorithm is validated by numerical simulations, where the channel data is generated by the propagation graph (PG) to model the true wireless propagation closely in the testing scenarios. The results demonstrate that the proposed approach can deal with both point and non-point targets with 3D localization errors of less than 30 cm for 97% of the testing trails in a 10×20×3 m3 indoor space. [less ▲]

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