A Simple Approach to Realize Blind Channel Identification for Short-Burst Signal
ZhaoYang Qiu, Zhichong Shen · 2020
Blind channel estimation is an important issue in wireless communication context. It has been a hot topic in cognitive radio and communication surveillance. Also, it is regarded as the key technique to improve the capacity of the communication systems. In this work, the blind channel estimation problem for short-burst amplitude and phase modulated signal is discussed. The decision feedback iterative structure is designed based on maximum likelihood function (MLF) model and the finite alphabet (FA) property. Two equivalent parametric models are used alternately to obtain stable estimates for both channel coefficients and transmitted symbols. As a result, the estimation with high accuracy is realized while using only a few symbols, making it suitable for short burst signal. In addition, the Cramer-Rao bound (CRB) is considered in this issue. Simulation verifies the superiority of proposed method.