TY - GEN
T1 - Rician K-Factor Estimation Using Deep Learning
AU - Alymani, Mofadal
AU - Alhazmi, Mohsen H.
AU - Almarhabi, Alhussain
AU - Alhazmi, Hatim
AU - Samarkandi, Abdullah
AU - Yao, Yu Dong
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Wireless communications systems design and its performance depend on the wireless fading channels, which are often characterized using a Rician probability function. A Rician K-factor is used to describe the fading severity in a Rician fading channel and is used in the system design and performance evaluation. Therefore, the estimation of the Rician K-factor is important in wireless communications research and development. Traditionally, a Rician K-factor equation, the statistics of the instantaneous frequency of the received signal with a lookup table, or the James-Stein estimator with the maximum likelihood estimation is used for the K-factor estimation. In this paper, we explore the use of deep learning for K-factor estimation. Specifically, we use the convolutional neural network (CNN) to estimate the Rician K-factor from a waveform signal in a Rician channel. Numerical results demonstrate its good performance in estimating the K-factor of the Rician channel.
AB - Wireless communications systems design and its performance depend on the wireless fading channels, which are often characterized using a Rician probability function. A Rician K-factor is used to describe the fading severity in a Rician fading channel and is used in the system design and performance evaluation. Therefore, the estimation of the Rician K-factor is important in wireless communications research and development. Traditionally, a Rician K-factor equation, the statistics of the instantaneous frequency of the received signal with a lookup table, or the James-Stein estimator with the maximum likelihood estimation is used for the K-factor estimation. In this paper, we explore the use of deep learning for K-factor estimation. Specifically, we use the convolutional neural network (CNN) to estimate the Rician K-factor from a waveform signal in a Rician channel. Numerical results demonstrate its good performance in estimating the K-factor of the Rician channel.
UR - http://www.scopus.com/inward/record.url?scp=85091945928&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091945928&partnerID=8YFLogxK
U2 - 10.1109/WOCC48579.2020.9114948
DO - 10.1109/WOCC48579.2020.9114948
M3 - Conference contribution
AN - SCOPUS:85091945928
T3 - 2020 29th Wireless and Optical Communications Conference, WOCC 2020
BT - 2020 29th Wireless and Optical Communications Conference, WOCC 2020
T2 - 29th Wireless and Optical Communications Conference, WOCC 2020
Y2 - 1 May 2020 through 2 May 2020
ER -