A hybrid structured neural network receiver in digital communication systems

In order to reduce the complexity of a radial basis function (RBF) network as a multiuser demodulator and an equalizer, we propose a simplified hybrid neural network architecture. The proposed neural network, which is called RN, has the structure of combining a radial basis function network with multilayer perceptrons (MLPs). The RBF network yields the linear combining output of the hidden layer while the proposed hybrid neural network produces the output using nonlinear combining techniques. From computer simulation results, the RN with the reduced structure from about 50% to about 70% over the RBF network shows better than or almost equal performance to the RBF network as a multiuser demodulator and an equalizer.