Abstract : In this paper, we design an iterative channel estimation and data detection algorithm in delay-Doppler domain for orthogonal time frequency space (OTFS) system by taking advantage of the sparse nature of the channel in this domain. The proposed algorithm iterates between message-passing-aided data detection and data-aided channel estimation. This sparse channel estimation is reformulated as a specific marginalization of maximum a posteriori (MAP) problem. To deal with the intractability of this problem, we provide a Bayesian approach based on the variational mean-field approximation via the variational Bayesian expectation maximization (VB-EM) algorithm. Finally, we compare the complexity and performance in term of Bit Error Rate (BER) and Normalized Mean Square Error (NMSE) of the proposed solution to a reference solution in the literature (SP-I).
https://hal-imt.archives-ouvertes.fr/hal-03552260 Contributor : Abdeldjalil Aïssa-El-BeyConnect in order to contact the contributor Submitted on : Wednesday, February 2, 2022 - 11:10:58 AM Last modification on : Monday, April 4, 2022 - 9:28:32 AM Long-term archiving on: : Tuesday, May 3, 2022 - 6:47:20 PM
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Rabah Ouchikh, Abdeldjalil Aissa El Bey, Thierry Chonavel, Mustapha Djeddou. Iterative channel estimation and data detection algorithm for OTFS modulation. ICASSP 2022: IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, May 2022, Singapor, Singapore. ⟨hal-03552260⟩