@inproceedings{604d94b0c49743bcb217fc036111d60c,
title = "Sampling-based tracking of time-varying channels for millimeter wave-band communications",
abstract = "In this paper, we propose a new recursive sparse channel recovery algorithm which can track time-varying support of angular domain channel response vector in mobility scenario for millimeter wave-band communications. We model the angle of departure (AoD) and the angle of arrival (AoA) using discrete state Markov random process and derive joint estimation of the time-varying support and amplitude of the angular domain channel vector. Using sequential Monte Carlo (SMC) method, the proposed channel estimation scheme tracks the support by drawing the samples from a posteriori distribution of the support indices while capturing the dynamics of time-varying amplitude using Kalman filter. Our simulation results show that the proposed algorithm yields significantly better tracking performance than the existing compressed sensing schemes.",
author = "Yoo, {Jin Hyeok} and Jisu Bae and Lim, {Sun Hong} and Sunwoo Kim and Choi, {Jun Won} and Byonghyo Shim",
note = "Funding Information: ACKNOWLEDGMENT This work is supported by Samsung Research Funding & Incubation Center of Samsung Electronics under Project Number SRFC-IT-1601-09. Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Communications, ICC 2017 ; Conference date: 21-05-2017 Through 25-05-2017",
year = "2017",
month = jul,
day = "28",
doi = "10.1109/ICC.2017.7996518",
language = "English",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Merouane Debbah and David Gesbert and Abdelhamid Mellouk",
booktitle = "2017 IEEE International Conference on Communications, ICC 2017",
}