Turbo channel estimation and equalisation for a superposition-based cooperative system

This paper investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particularly interest is the channel estimation at the relay node which imposes extra requirement for the system resources. In this paper, we propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The softin-soft-out MMSE equalizer is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm. Index Terms cooperative diversity, channel estimation, turbo equalization, superimposed training.