A modular polynomial perceptron approach to channel equalization and ACI suppression

In mobile and cellular radio systems, a challenging problem is the equalization of digital signals. A new adaptation routine of the polynomial perceptron method is proposed for channel equalization and ACI suppression, in which the weights of a given order are optimized independently of the weights of higher order. The suggested method allows realization of a modular structure in which, starting from weights of th first order, higher order weights are progressively optimized to improve the performance with lower order ones without requiring their recomputation. The 16-QAM channel model is considered for simulation which includes frequency-selective Rayleigh fading and an ACI environment. The results show that the proposed method exhibits more rapid convergence with less computational complexity.