EM-based Semi-blind Channel Estimation in AF Two-Way Relay Networks

TL;DR

This paper introduces an EM-based semi-blind channel estimation algorithm for AF two-way relay networks, combining data and pilot signals to improve accuracy with low computational complexity and rapid convergence.

Contribution

It presents a novel EM-based semi-blind estimation method that outperforms traditional training-based approaches in accuracy and efficiency for TWRNs.

Findings

Higher estimation accuracy than conventional methods

Linear computational complexity per iteration

Fast convergence within few iterations

Abstract

We propose an expectation maximization (EM)-based algorithm for semi-blind channel estimation of reciprocal channels in amplify-and-forward (AF) two-way relay networks (TWRNs). By incorporating both data samples and pilots into the estimation, the proposed algorithm provides substantially higher accuracy than the conventional training-based approach. Furthermore, the proposed algorithm has a linear computational complexity per iteration and converges after a small number of iterations.