Distributed Blind Equalization Based on the Best Local Network in Networked System

Abstract

A distributed estimation algorithm is discussed referring to the single-input multiple-output (SIMO) channel model over a wireless sensor network (WSN) to estimate the transmitted data signal blindly. We find a sensor node in the best local sensor network by minimizing the total average deviation from the minimum signal power in the WSN. The signal at the sensor node is used as the input signal for the distributed blind equalizer. We assume two classes of channels in the SIMO channel model, namely, Class 1 of the common channel conditions with different noise variances and Class 2 of the different channel conditions with common noise variances, based on raised cosine channel models. Computer simulations confirm the excellent performance of the proposed method through the evaluation of mean square error and symbol error rate.