TY - GEN
T1 - Underwater acoustic communications using a-priori statistics on channel time-variations
AU - Wasserblat, Moshe
AU - Tabrikian, Joseph
N1 - Publisher Copyright:
© 2000 IEEE.
PY - 2000/1/1
Y1 - 2000/1/1
N2 - This paper addresses the problem of underwater acoustic channel estimation for communications in time-varying environments. In the case of a rapidly time-varying environment, the channel needs to be estimated and tracked continuously. In this case, prior information on the channel can be used to improve channel estimation performance. In this paper, a-priori statistics on the channel time-variations are used in order to obtain a maximum a-posteriori estimator for channel tap-coefficients. It is also shown that in a shallow water waveguide, typical channel time-variations span a small subspace of channel tap-coefficients variations. This fact is used to reduce the number of parameters to be estimated and improve the channel estimation performance. The results demonstrate a performance gain of 5-10 dB in terms of the signal-to-noise ratio in decision-feedback equalizer mean-squared error, compared to the least-squares method which ignores the a-priori statistics on the channel time-variations.
AB - This paper addresses the problem of underwater acoustic channel estimation for communications in time-varying environments. In the case of a rapidly time-varying environment, the channel needs to be estimated and tracked continuously. In this case, prior information on the channel can be used to improve channel estimation performance. In this paper, a-priori statistics on the channel time-variations are used in order to obtain a maximum a-posteriori estimator for channel tap-coefficients. It is also shown that in a shallow water waveguide, typical channel time-variations span a small subspace of channel tap-coefficients variations. This fact is used to reduce the number of parameters to be estimated and improve the channel estimation performance. The results demonstrate a performance gain of 5-10 dB in terms of the signal-to-noise ratio in decision-feedback equalizer mean-squared error, compared to the least-squares method which ignores the a-priori statistics on the channel time-variations.
UR - https://www.scopus.com/pages/publications/0033708091
U2 - 10.1109/ICASSP.2000.861037
DO - 10.1109/ICASSP.2000.861037
M3 - Conference contribution
AN - SCOPUS:0033708091
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2689
EP - 2692
BT - CommunicationsSensor Array and Multichannel Signal Processing
PB - Institute of Electrical and Electronics Engineers
T2 - 25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
Y2 - 5 June 2000 through 9 June 2000
ER -