TY - GEN
T1 - Learning the MMSE channel predictor
AU - Turan, Nurettin
AU - Utschick, Wolfgang
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - In this work a feed-forward neural network-based channel predictor is derived, where assumptions on a physical wave propagation channel model in a fading scenario are incorporated into the design procedure of the predictor. We start with the general expression of an approximated minimum mean squared error (MMSE) predictor and derive a predictor having the structure of a feed-forward neural network by making two key assumptions. By properly training this neural network it is possible to compensate the approximation errors due to these assumptions. It is further possible to outperform the linear MMSE (LMMSE) predictor with perfect knowledge of the statistical moments of second order based on the covariance function for specific channel model assumptions, especially for low SNR values.
AB - In this work a feed-forward neural network-based channel predictor is derived, where assumptions on a physical wave propagation channel model in a fading scenario are incorporated into the design procedure of the predictor. We start with the general expression of an approximated minimum mean squared error (MMSE) predictor and derive a predictor having the structure of a feed-forward neural network by making two key assumptions. By properly training this neural network it is possible to compensate the approximation errors due to these assumptions. It is further possible to outperform the linear MMSE (LMMSE) predictor with perfect knowledge of the statistical moments of second order based on the covariance function for specific channel model assumptions, especially for low SNR values.
KW - Machine learning
KW - Minimum mean squared error prediction
KW - Neural networks
KW - Time-variant channel state information
UR - https://www.scopus.com/pages/publications/85090295465
U2 - 10.1109/ICCWorkshops49005.2020.9145371
DO - 10.1109/ICCWorkshops49005.2020.9145371
M3 - Conference contribution
AN - SCOPUS:85090295465
T3 - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings
BT - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020
Y2 - 7 June 2020 through 11 June 2020
ER -