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Near-Field Wideband Localization using TTD-Based Terahertz Extremely Large-Scale Arrays

Qianyu Yang, Haiyang Zhang, Francesco Guidi, Anna Guerra, Davide Dardari, Baoyun Wang, Yonina C. Eldar

Abstract

The synergy between extremely large-scale antenna arrays and terahertz technology in sixth-generation networks establishes a near-field wideband transmission environment, enabling the generation of highly focused beams. To leverage this capability for multi-source localization, we propose a direct localization method based on the curvature-of-arrival of spherical wavefronts for estimating the positions of multiple near-field users from wideband signals. Furthermore, to overcome the spatial-wideband effect, we introduce a hybrid analog/digital array architecture with true-timedelayers (TTDs). We derive a closed-form position error bound to characterize the fundamental estimation performance and optimize the analog coefficients of array by maximizing the trace of the Fisher information matrix to minimize this bound. Furthermore, we extend this method to a sub-optimal iterative method that jointly optimizes beam focusing and localization, without requiring prior knowledge of the source positions for array design. Simulation results show that the proposed array configuration design significantly enhances the performance of near-field wideband localization, while the presence of TTDs effectively mitigates the localization performance degradation caused by spatial-wideband effects.

Near-Field Wideband Localization using TTD-Based Terahertz Extremely Large-Scale Arrays

Abstract

The synergy between extremely large-scale antenna arrays and terahertz technology in sixth-generation networks establishes a near-field wideband transmission environment, enabling the generation of highly focused beams. To leverage this capability for multi-source localization, we propose a direct localization method based on the curvature-of-arrival of spherical wavefronts for estimating the positions of multiple near-field users from wideband signals. Furthermore, to overcome the spatial-wideband effect, we introduce a hybrid analog/digital array architecture with true-timedelayers (TTDs). We derive a closed-form position error bound to characterize the fundamental estimation performance and optimize the analog coefficients of array by maximizing the trace of the Fisher information matrix to minimize this bound. Furthermore, we extend this method to a sub-optimal iterative method that jointly optimizes beam focusing and localization, without requiring prior knowledge of the source positions for array design. Simulation results show that the proposed array configuration design significantly enhances the performance of near-field wideband localization, while the presence of TTDs effectively mitigates the localization performance degradation caused by spatial-wideband effects.
Paper Structure (21 sections, 46 equations, 7 figures, 1 table, 2 algorithms)

This paper contains 21 sections, 46 equations, 7 figures, 1 table, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Received Signal Model
  4. Array Architecture
  5. Localization with Fixed Analog Combination
  6. Maximum Likelihood Localization
  7. Localization Setting
  8. Maximum Likelihood Formulation
  9. MLE Computation via Alternating Projection
  10. Cramer-Rao Bound Analysis
  11. Discussion
  12. Analog Combination Coefficient Design
  13. Problem Formulation
  14. Alternating Optimization for TTDs and PSs
  15. Phase design for given time delay
  16. ...and 6 more sections

Figures (7)

  • Figure 1: System model diagram. Left diagram: the array architectures; Right diagram: the localization scenario.
  • Figure 2: The heatmap for the CRB on user position estimate by varying user positions, SNR is fixed as -10 dB. The magenta square denotes the array position. The red point is the predetermined position that analog design focuses on.
  • Figure 3: Position estimations track map for each iteration of Algorithm \ref{['alg:AP']} and Algorithm \ref{['alg:Alternating']} with SNR $\mathsf{SNR} = -10$ dB.
  • Figure 4: Contrast of the number of iterations required for convergence via multiple contrast schemes with $\mathsf{SNR} = -5$ dB.
  • Figure 5: RMSE contrast of multiple contrast schemes under different SNR with array setting. (a) RMSE-SNR; (b) CRB-SNR
  • ...and 2 more figures