Blind Data Detection With Unknown Channel Coding
Yu Liu, Fanggang Wang · IEEE Communications Letters · 2020
Blind data detection is widely investigated since it finds many crucial applications in the interference cancelation, cognitive radio, and military interception, etc. In this letter, we propose a blind iterative algorithm that simultaneously improves the performance of channel coding identification and data detection in the communication system with the unknown channel coding and the unknown fading channels. First, the likelihood-based channel estimator and the soft detector and regenerator are adopted in an iterative manner, which estimates the unknown parameters and detects the information bits. Then, an average log-likelihood ratio (LLR) classifier is adopted to identify the unknown channel coding and determine the information bits. Numerical results show that the proposed algorithm outperforms the existing scheme in terms of correct identification and data detection.