TY - GEN
T1 - Near-field Localization with Dynamic Metasurface Antennas
AU - Yang, Qianyu
AU - Guerra, Anna
AU - Guidi, Francesco
AU - Shlezinger, Nir
AU - Zhang, Haiyang
AU - Dardari, Davide
AU - Wang, Baoyun
AU - Eldar, Yonina C
N1 - This work was supported by the National Natural Science Foundation of China under (grant No. 61971238), by the EU Horizon project TIMES (Grant No. 101096307), by the EU under the Italian NRRP of NextGenerationEU partnership on Telecommunications of the Future” (PE00000001 - program “RESTART”), by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant No. 101000967), by the Israel Science Foundation (grant No. 536/22) and by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX22 0951).
PY - 2023/7
Y1 - 2023/7
N2 - Sixth generation (6G) cellular communications are expected to support enhanced wireless localization capabilities. The widespread deployment of large arrays and high-frequency bandwidths give rise to new considerations for localization applications. Emerging antenna architectures, such as dynamic metasurface antennas (DMAs), are expected to be frequently utilized thanks to the achievable high angular resolution and low hardware complexity. Further, wireless localization is likely to take place in the radiating near-field (Fresnel) region, which provides new degrees of freedom, because of the adoption of arrays with large apertures. While current studies mostly focus on the use of costly fully-digital antenna arrays, in this paper we investigate how DMAs can be applied for near-field localization of a single user. We use a direct positioning estimation method based on curvature-of-Arrival of the impinging wavefront to obtain the user location, and characterize the effects of DMA tuning on the estimation accuracy. Next, we propose an algorithm for configuring the DMA to optimize near-field localization, by first tuning the adjustable DMA coefficients to minimize the estimation error using postulated knowledge of the actual user position. Finally, we propose a sub-optimal iterative algorithm that does not rely on such knowledge. Simulation results show that the DMA-based near-field localization accuracy could approach that of fully-digital arrays at lower cost.
AB - Sixth generation (6G) cellular communications are expected to support enhanced wireless localization capabilities. The widespread deployment of large arrays and high-frequency bandwidths give rise to new considerations for localization applications. Emerging antenna architectures, such as dynamic metasurface antennas (DMAs), are expected to be frequently utilized thanks to the achievable high angular resolution and low hardware complexity. Further, wireless localization is likely to take place in the radiating near-field (Fresnel) region, which provides new degrees of freedom, because of the adoption of arrays with large apertures. While current studies mostly focus on the use of costly fully-digital antenna arrays, in this paper we investigate how DMAs can be applied for near-field localization of a single user. We use a direct positioning estimation method based on curvature-of-Arrival of the impinging wavefront to obtain the user location, and characterize the effects of DMA tuning on the estimation accuracy. Next, we propose an algorithm for configuring the DMA to optimize near-field localization, by first tuning the adjustable DMA coefficients to minimize the estimation error using postulated knowledge of the actual user position. Finally, we propose a sub-optimal iterative algorithm that does not rely on such knowledge. Simulation results show that the DMA-based near-field localization accuracy could approach that of fully-digital arrays at lower cost.
UR - http://www.scopus.com/inward/record.url?scp=85171356201&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ICASSP49357.2023.10097166
DO - https://doi.org/10.1109/ICASSP49357.2023.10097166
M3 - منشور من مؤتمر
SN - 9781728163284
BT - ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
T2 - 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023)
Y2 - 4 June 2023 through 10 June 2023
ER -