Data-Aided Channel Estimation for OTFS Systems With a Superimposed Pilot and Data Transmission Scheme
The recently developed orthogonal time frequency space (OTFS) modulation has shown its capability of coping with the fast time-varying channels in high-mobility environments. In particular, OTFS modulation gives rise to the sparse representation of the delay-Doppler (DD) domain channel model. Hence,...
Saved in:
| Published in: | IEEE wireless communications letters Vol. 10; no. 9; pp. 1954 - 1958 |
|---|---|
| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Piscataway
IEEE
01.09.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 2162-2337, 2162-2345 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The recently developed orthogonal time frequency space (OTFS) modulation has shown its capability of coping with the fast time-varying channels in high-mobility environments. In particular, OTFS modulation gives rise to the sparse representation of the delay-Doppler (DD) domain channel model. Hence, one can an enjoy accurate channel estimation by adopting only one pilot symbol. However, conventional OTFS channel estimation schemes require the deployment of guard space to avoid data-pilot interference, which inevitably sacrifices the spectral efficiency. In this letter, we develop a data-aided channel estimation algorithm for a superimposed pilot and data transmission scheme, which can improve the spectral efficiency. To accurately estimate the channel and detect the data symbols, we coarsely estimate the channel based on the pilot symbol, followed by an iterative process which detects the data symbols and refines the channel estimates. Simulation results show that the bit error rate (BER) performance based on the proposed method can approach the baseline scheme with perfect channel estimation. |
|---|---|
| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2162-2337 2162-2345 |
| DOI: | 10.1109/LWC.2021.3088836 |