On Efficient Utilization of Training Pilots for Linear Equalization of QAM Transmissions

Conventional approaches to linear equalization of data transmissions under frequency selective channels simply treat the problem as a system identification issue. However, practical data communication systems impose additional conditions on the channel input signals such as LDPC error correction coding and known data constellation. We study a unified framework to integrate these known constraints into the channel equalization procedure and propose a linear programming-based approach to channel equalization for QAM signals that can succeed with significantly reduced pilots. In addition to utilizing the information of QAM constellation, our method exploits the code information of LDPC forward error correction coding to improve the equalization performance and convergence properties.