Blind Equalization Based on Normalized Error in Wireless Sensor Networks

Abstract

In this paper, we consider a single-input multiple-output (SIMO) channel-based static wireless sensor network and carry out blind equalization to estimate the transmitted signal blindly. Four cases of common or different channels and a common or different variance of noises are considered. For each case, the solution of blind equalization is derived. For the different-channel cases, we derive a new approach in which the best sensor output signal is found by adaptively implementing the normalized error used in speech processing. We estimate the transmitted signal from the corresponding sensor output by utilizing the generalized Sato equalizer. The mean square error (MSE) and symbol error rate (SER) are investigated on several communication channels. Computer simulations validate the solution for each case and show the effectiveness of the proposed method relative to the conventional methods.