Tensor-Based Blind Time-Variant Channel Estimation for Uplink Relaying Cooperative Systems

This paper develops two blind estimation algorithms based on the tensor for the time-variant channel of uplink relaying cooperative system. Compared with the traditional blind estimation of matrix-based, the proposed adaptive tracking parallel factor (PARAFAC) decomposition based on the high order tensor model not only has the characteristics of simple calculation and the flexible parameter selection, but also simplify the uniqueness of the blind channel estimation. In this system, receive signal is represent the third order tensor model firstly, and then the initial estimate update variables according to PARAFAC with the Least Mean Squares (LMS) and Recursive Least Squares (RLS). It is shown that, this method has the lower complexity and better robustness for time-varying channel. Simulation results reveal that the proposed algorithms can significantly improve the BER performance when compared to the existing research.