Joint Decorrelating Channel and Data Estimation for Space-Time Spreading Systems

In this paper, we propose a new joint channel and data detection scheme based on the superimposed training technique for space-time spreading systems. The proposed scheme enhances the performance by eliminating the multiple access interference from both the channel and data estimation by employing two decorrelators: channel and data decorrelators. On a frequency-selective fading channel, our simulation results show that the proposed scheme outperforms other conventional joint channel and data estimation techniques. Moreover, unlike other conventional detection techniques, our proposed estimation technique is shown to achieve the full system diversity.