Rugui Yao

Abstract To address the issues of suboptimal sparsity and the tendency of clustering algorithms to converge to local optima in the estimation of the mixing matrix within underdetermined blind source separation (UBSS) systems, a novel mixing matrix estimation algorithm based on source signal sparsity is proposed. Firstly, the principle of underdetermined mixing matrix estimation leveraging source sparsity is derived.

1. Introduction In the field of wireless communication, signal modulation type recognition constitutes a crucial technology and occupies a central place in signal processing and pattern recognition. It serves as the key to the realization of signal detection and demodulation. To efficiently transmit information in the channel, communication systems utilize a variety of modulation techniques to adapt to continuously changing channel conditions.

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