Sparse representation for Massive MIMO Satellite channel based on Joint Dictionary Learning

In this paper, we investigate joint dictionary representation for Massive MIMO satellite channel and discuss the representation performance. What kind of the dictionary model is satisfied for channel representation is still an unknown field. This paper mainly focuses on the analysis of the joint dictionary for channel representation including uplink and downlink. The main contributions are as follows. Firstly, the conditional constraints for satellite channel representation have been established with joint dictionary, including both uplink constraints and downlink constraints. Secondly, the maximum boundary that dictionary learning can represent channel characteristics is determined, that is, the optimal approximation of channel dictionary was achieved. Finally, channel sparse representation method for joint SVD decomposition at dictionary boundary conditions is proposed.