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

Publication Date: 3/11/2018

Event: OFC 2018

Reference: M4E.4: 1-3, 2018

Authors: Zhen Qu, NEC Laboratories America, Inc., University of Arizona; Shaoliang Zhang, NEC Laboratories America, Inc.; Ivan B. Djordjevic, University of Arizona

Abstract: 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.

Publication Link: https://ieeexplore.ieee.org/document/8385845