Suppr超能文献

概率幅度整形的可达信息速率:一种通过随机符号编码论证的替代方法。

Achievable Information Rates for Probabilistic Amplitude Shaping: An Alternative Approach via Random Sign-Coding Arguments.

作者信息

Gültekin Yunus Can, Alvarado Alex, Willems Frans M J

机构信息

Information and Communication Theory Lab, Signal Processing Systems Group, Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.

出版信息

Entropy (Basel). 2020 Jul 11;22(7):762. doi: 10.3390/e22070762.

Abstract

Probabilistic amplitude shaping (PAS) is a coded modulation strategy in which constellation shaping and channel coding are combined. PAS has attracted considerable attention in both wireless and optical communications. Achievable information rates (AIRs) of PAS have been investigated in the literature using Gallager's error exponent approach. In particular, it has been shown that PAS achieves the capacity of the additive white Gaussian noise channel (Böcherer, 2018). In this work, we revisit the capacity-achieving property of PAS and derive AIRs using weak typicality. Our objective is to provide alternative proofs based on random sign-coding arguments that are as constructive as possible. Accordingly, in our proofs, only some signs of the channel inputs are drawn from a random code, while the remaining signs and amplitudes are produced constructively. We consider both symbol-metric and bit-metric decoding.

摘要

概率幅度整形(PAS)是一种将星座整形与信道编码相结合的编码调制策略。PAS在无线通信和光通信领域都引起了广泛关注。文献中已使用加拉格尔误差指数方法对PAS的可达信息速率(AIR)进行了研究。特别地,研究表明PAS能够实现加性高斯白噪声信道的容量(博彻勒,2018年)。在本工作中,我们重新审视PAS的容量实现特性,并使用弱典型性推导AIR。我们的目标是基于尽可能具有建设性的随机符号编码论证提供替代证明。因此,在我们的证明中,仅信道输入的一些符号从随机码中抽取,而其余符号和幅度则通过构造性方式生成。我们考虑符号度量解码和比特度量解码。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/773a/7517313/cf2cf424adfe/entropy-22-00762-g001.jpg

相似文献

7
Tighter decoding reliability bound for Gallager's error-correcting code.加拉格尔纠错码更严格的译码可靠性界。
Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Oct;64(4 Pt 2):046113. doi: 10.1103/PhysRevE.64.046113. Epub 2001 Sep 21.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验