Distributed Blind Equalization with Block-Adaptive Approach on Wireless Sensor Network

Abstract

The performance of distributed blind equalization over a wireless sensor network (WSN) is affected by the transmission channels between the data transmitter and each sensor node in the WSN. To overcome this problem, in this paper, we propose a block-adaptive approach to design the combination weight matrix for distributed estimation processing. The fact that the error signal power of each distributed blind equalizer is changed according to the channel condition is effectively utilized and the corresponding error signal power at the sensor node to the total error signal power in the local network is calculated. The combination weight matrix is redesigned repeatedly during $L$ updating of the tap coefficients vector of the distributed blind equalizer, that is called a block-adaptive approach in this paper. In simulation experiments, the proposed method achieves better average mean square error and symbol error rate than the state-of-the-art method for distributed blind equalization.