TY - GEN
T1 - Optimization on OTFS Modulation Channel Estimation Path Employing CNN-based Self-Adjustment Model
AU - Wang, Junlong
AU - Yang, Chaoyi
AU - Pan, Zhenni
AU - Shimamoto, Shigeru
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Channel estimation performance is an important evaluation parameter in Orthogonal Time Frequency Space (OTFS) modulated systems, in which the pilots in the delay-Doppler (DD)-domain are estimated at the receiver point. The proposed adjustment model will collect results of the history transmission progress and utilize these records to adjust the channel estimation path for the next transmission progress. A BP-based learning algorithm is introduced into the adjustment model, which completes the adjustment progress by analyzing pilot final channel selection and other not selected channels in history transmission. Feedback from the adjustment model is used in the next OTFS transmission for reducing channel estimation paths when data/signals with the same DD-domain index are transmitted in another transmission set. The simulation results indicate that the improvement of our proposal under classical Bit Error Rate(BER)-based scheme is competitive in various learning-based OTFS optimization solutions.
AB - Channel estimation performance is an important evaluation parameter in Orthogonal Time Frequency Space (OTFS) modulated systems, in which the pilots in the delay-Doppler (DD)-domain are estimated at the receiver point. The proposed adjustment model will collect results of the history transmission progress and utilize these records to adjust the channel estimation path for the next transmission progress. A BP-based learning algorithm is introduced into the adjustment model, which completes the adjustment progress by analyzing pilot final channel selection and other not selected channels in history transmission. Feedback from the adjustment model is used in the next OTFS transmission for reducing channel estimation paths when data/signals with the same DD-domain index are transmitted in another transmission set. The simulation results indicate that the improvement of our proposal under classical Bit Error Rate(BER)-based scheme is competitive in various learning-based OTFS optimization solutions.
KW - channel estimation
KW - delay-Doppler domain channel matrix
KW - machine learning
KW - OTFS
UR - http://www.scopus.com/inward/record.url?scp=85134735035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134735035&partnerID=8YFLogxK
U2 - 10.1109/ICCWorkshops53468.2022.9814508
DO - 10.1109/ICCWorkshops53468.2022.9814508
M3 - Conference contribution
AN - SCOPUS:85134735035
T3 - 2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
SP - 951
EP - 956
BT - 2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Communications Workshops, ICC Workshops 2022
Y2 - 16 May 2022 through 20 May 2022
ER -