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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 lay- ers. This actually forms a Turbo iteration process between the different algorithms which effectively im- proves 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 statis- tics based algorithms.
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 lay-ers. This actually forms a Turbo iteration process between the different algorithms which effectively im- proves 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 statis- tics based algorithms.