This paper describes a channel estimation and equalization algorithm using three-layer artificial neural networks （ANNs） with feedback for multiple input multiple output wireless communication systems. An ANN struct...This paper describes a channel estimation and equalization algorithm using three-layer artificial neural networks （ANNs） with feedback for multiple input multiple output wireless communication systems. An ANN structure with feedback was designed to use different learning algorithms in the different ANN layers. This actually forms a Turbo iteration process between the different algorithms which effectively improves the estimation performance of the channel equalizer. Simulation results show that this channel equalization algorithm has better computational efficiency and faster convergence than higher order statistics based algorithms.展开更多
基金Supported by the Basic Research Foundation of Tsinghua Na-tional Laboratory for Information Science and Technology (TNList) the Major Program of the National Natural Science Foundation of China (No. 60496311)
文摘This paper describes a channel estimation and equalization algorithm using three-layer artificial neural networks （ANNs） with feedback for multiple input multiple output wireless communication systems. An ANN structure with feedback was designed to use different learning algorithms in the different ANN layers. This actually forms a Turbo iteration process between the different algorithms which effectively improves the estimation performance of the channel equalizer. Simulation results show that this channel equalization algorithm has better computational efficiency and faster convergence than higher order statistics based algorithms.
