Localization Based on Channel Impulse Response Estimates

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 localization accuracy in typical indoor environments.