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Paper IDG.5.2
Paper Title Structured Quasi-Gray labelling for Reed-Muller Grassmannian Constellations
Authors Yi Qin, Renaud-Alexandre Pitaval, Huawei Technologies Sweden AB, Sweden
Session G.5: Signal Processing
Presentation Lecture
Track Graphs, Games, Sparsity, and Signal Processing
Manuscript  Click here to download the manuscript
Virtual Presentation  Click here to watch in the Virtual Symposium
Abstract The high-SNR capacity of a block-faded non-coherent channel can be achieved by a multi-dimensional Grassmannian modulation. This paper proposes an analytical quasi-Gray labelling for Reed-Muller Grassmannian constellations. The proposed labelling method enables to reduce the block error rate (BLER) of a system with error correction code, by minimizing the average Hamming distance between labels of neighboring modulation symbols. In particular, we first define an inherent generation label from which the Reed-Muller Grassmannian constellation is constructed, and show it fulfills a homogeneity property. Based on this, a bijective linear mapping between a quasi-Gray labelling and the former labelling is proposed, where the bijective linear mapping matrix is obtained by a low-complexity algorithm. Numerical results show that the proposed quasi-Gray labelling method can achieve 40% reduction of the average Hamming distance between neighboring modulation symbols compared to the generation label or random labelling. Finally, link-level simulation results further demonstrate that the proposed quasi-Gray labelling can effectively reduce the BLER.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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