论文信息 - Universal Hybrid Probabilistic-geometric Shaping Based on Two-dimensional Distribution Matchers

Universal Hybrid Probabilistic-geometric Shaping Based on Two-dimensional Distribution Matchers

We propose universal distribution matchers applicable to any two-dimensional signal constellation. We experimentally demonstrate that the performance of 32-ary QAM, based on hybrid probabilistic-geometric shaping, is superior to probabilistically shaped 32QAM and regular 32QAM.

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