TY - JOUR
T1 - UAMP-based delay-Doppler channel estimation for OTFS systems
AU - Li, Zhongjie
AU - Yuan, Weijie
AU - Guo, Qinghua
AU - Wu, Nan
AU - Zhang, Ji
N1 - Publisher Copyright:
© China Communications Magazine Co., Ltd. October 2023.
PY - 2023/10/1
Y1 - 2023/10/1
N2 - Orthogonal time frequency space (OTFS) technique, which modulates data symbols in the delay-Doppler (DD) domain, presents a potential solution for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing (UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model (HMM). The empirical state evolution (SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm, we derive the update criterion for the hyperparameters through the expectation-maximization (EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.
AB - Orthogonal time frequency space (OTFS) technique, which modulates data symbols in the delay-Doppler (DD) domain, presents a potential solution for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing (UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model (HMM). The empirical state evolution (SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm, we derive the update criterion for the hyperparameters through the expectation-maximization (EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.
KW - channel estimation
KW - hidden Markov model (HMM)
KW - orthogonal time frequency space (OTFS)
KW - unitary approximate message passing (UAMP)
UR - http://www.scopus.com/inward/record.url?scp=85176938465&partnerID=8YFLogxK
U2 - 10.23919/JCC.fa.2023-0067.202310
DO - 10.23919/JCC.fa.2023-0067.202310
M3 - Article
AN - SCOPUS:85176938465
SN - 1673-5447
VL - 20
SP - 70
EP - 84
JO - China Communications
JF - China Communications
IS - 10
ER -