Sparsity Analysis of DS Spread Spectrum Signals via Theoretical Analysis and Dictionary Learning.

For the purpose of solving the problem of high sampling rate and massive data processing brought by high bandwidth in the field of Aerospace Communication, researchers applied CS theory to spread spectrum signal processing. Sparsity analysis is the prerequisite for the application of CS theory. This paper studies the sparsity of the DS spread spectrum signals, which is the most common kind of signal in the current TT&C systems. Based on the theoretical analysis we get the sparse dictionary, then the dictionary is optimized by K-SVD dictionary learning algorithm. The simulation results show that the two signals have strong sparsity in the constructed sparse base dictionary, which lays a theoretical foundation for the TT&C spread spectrum signal processing based on CS theory. [ABSTRACT FROM AUTHOR]