Signal estimation with neural networks for multipath mobile communications

This paper deals with signal estimation in multipath fading channels. Multipath fading is a significant problem in wireless communications systems and may occur whenever there is more than one path from a transmitter to the intended receiver. One method of addressing this task is to implement a RAKE receiver. However, this requires estimates of tap weights based on characteristics of the channel model. Within limited environments the multipath characteristics of a channel may exhibit little variation over time. Under these conditions a neural network can be employed to learn the tap weights. This paper illustrates the use of neural networks in solving this problem and presents results from simulations