A QAM Blind Equalization Algorithm based on Fuzzy Neural Network

As a key technology of digital broadcast and TV, blind equalization overcomes inter-symbol interference to improve the effect of receiving signals. A new QAM blind equalization algorithm based on fuzzy neural network classifier is proposed. Channel estimation and fuzzy neural network classifier are combined to carry out equalization. The primary signal is attained by de-convolution. Judgment range of fuzzy neural network is adjusted dynamically by competition study algorithm, and then blind equalization is realized. Simulation shows that the new algorithm improves convergence speed and reduces residual error and BER (Bit Error Ratio).