A Combination Rule Based on Signal Power for Distributed Blind Equalization
Sulin Chi, Tetsuya Shimamura · 2021
This paper considers distributed blind equalization for estimating an unknown transmitted data signal over wireless sensor networks (WSNs). We propose an efficient combination weight rule based on the noise amount which assigns the weights relying on the proportion of noise at sensor nodes. Simulations show that the proposed combination weight rule outperforms the existing combination weight rules in implementing the distributed generalized Sato algorithm.