Channel Estimation based on Echo State Networks in Wireless MIMO Systems
Echo state networks (ESNs) provide architecture and supervised learning principle for recurrent neural networks (RNNs). In this paper, we apply ESN to channel estimation in wireless Multiple-Input and Multiple-Output (MIMO). There is the multipath propagation environment between a transmitter and receiver. Thus the received signal undergoes phase shift, attenuation and time delay. In order to mitigate these random effects and decoding the transmitted signal at the reservoir, we present ESNs for learning nonlinear systems and realizing accurate channel estimation. We also design a teaching scheme to train the output weights of ESNs. The potential for engineering application is illustrated by channel estimation. Numerical results show that accuracy is improved by the number of reservoir units.
Channel Estimation MIMO ESN NRMS channel coefficient reservoir
Yongbo Liao Yanhu Wang Wenchang Li
School of Energy Science and Engineering,University of Electronic Science and Technology of China;St School of Energy Science and Engineering,University of Electronic Science and Technology of China Institute of semiconductors,Chinese Academy of Sciences Beijing,China
国际会议
秦皇岛
英文
1541-1546
2015-09-18（万方平台首次上网日期，不代表论文的发表时间）