Location-awareness using wireless signals is a key enabler for numerous emerging applications. Inspired by the recently proposed soft information (SI)-based localization, this paper develops a localization algorithm based on estimates of the channel impulse response (CIR), which inherently contains position information. We propose a delay-origin uncertainty model for describing the conditional distribution of the delays in CIR given node positions. A scalable localization algorithm is designed using belief propagation (BP) on a factor graph that incorporates the uncertainty model. The performance of the developed algorithm is quantified for mmWave signals using QuaDriGa channel simulator, showing decimeter-level localiza- tion accuracy in typical indoor environments.
Localization Based on Channel Impulse Response Estimates
Andrea Conti;
2020
Abstract
Location-awareness using wireless signals is a key enabler for numerous emerging applications. Inspired by the recently proposed soft information (SI)-based localization, this paper develops a localization algorithm based on estimates of the channel impulse response (CIR), which inherently contains position information. We propose a delay-origin uncertainty model for describing the conditional distribution of the delays in CIR given node positions. A scalable localization algorithm is designed using belief propagation (BP) on a factor graph that incorporates the uncertainty model. The performance of the developed algorithm is quantified for mmWave signals using QuaDriGa channel simulator, showing decimeter-level localiza- tion accuracy in typical indoor environments.File | Dimensione | Formato | |
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