CIF: Small: Optimal Coded Modulation When Asymmetric Signaling Achieves Capacity

CIF：小：非对称信令达到容量时的最佳编码调制

基本信息

批准号：
1911166
负责人：
Richard Wesel
金额：
$ 23万
依托单位：
University of California-Los Angeles
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-10-01 至 2023-01-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1911166&HistoricalAwards=false
关键词：
CIF Small Optimal Coded Modulation

项目摘要

This project develops the theoretical framework necessary to achieve, on certain data communication channels, the highest possible reliable data rate while still using low-complexity practical decoders. Applications include satellites communicating using either free-space optical communication or radio-frequency communication. Practically all data is communicated by sending a sequence of symbols transmitted as a waveform over a physical channel. These symbols often determine the amplitudes and/or phases of the waveform and are typically drawn from a discrete alphabet of possible values. Traditionally, symbol alphabets are symmetric. For example, if there is a symbol with an amplitude of +5 volts there will also be a symbol with an amplitude of -5 volts. For symmetric alphabets, there are a variety of existing coded modulation techniques that achieve high data rates using practical decoders. However, for important channels including common satellite channels, the best alphabets turn out not to be symmetric. This significantly complicates the design both of the coded modulation to achieve the highest rates and of the associated decoding algorithms. This project develops techniques that identify the optimal placement of alphabet symbols without requiring symmetry and introduces a new form of coded modulation, known as probabilistic permutation shaping, that achieves the highest possible data rates while still allowing practical decoders to use the optimal asymmetric alphabets. The practical impact from a successful outcome of this research will lead to high-speed satellite links for both earth-space and vice-versa.This project utilizes probabilistic permutation shaping, which approaches channel capacity using a practical low-density parity check (LDPC) decoder even when the optimal input distribution is asymmetric. This approach avoids the complexity and error propagation of multi-layer coding with multi-stage decoding. It also avoids the latency and performance loss associated with joint de-mapping and decoding. The project also develops a family of new optimization techniques utilizing a modification of the Blahut-Arimoto algorithm that dynamically re-assigns the positions of mass points. Dynamic-assignment Blahut-Arimoto characterizes not only point solutions at a specific signal-to-noise ratio, but the entire evolution of the minimal cardinality optimal finite-support distributions as the channel capacity increases over the entire range of interest. In the context of these families of finite-support distributions, which are inherently asymmetric, probabilistic permutation shaping builds on the existing framework of probabilistic amplitude shaping to provide flexible and practical coded modulation solutions that support entire families of non-uniform distributions that would have previously been considered exotic.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目开发了在某些数据通信渠道上实现最高可靠数据速率的理论框架，同时仍使用低复杂性实用解码器。应用程序包括使用自由空间光学通信或射频通信进行通信的卫星通信。实际上，通过发送一系列符号作为波形在物理通道上传输的符号来传达所有数据。这些符号通常确定波形的幅度和/或阶段，通常是从可能值的离散字母中绘制的。传统上，符号字母是对称的。例如，如果有一个振幅+5伏的符号，也将有一个符号，幅度为-5伏。对于对称字母，有许多现有的编码调制技术，可以使用实用解码器实现高数据速率。但是，对于包括常见卫星通道在内的重要通道，最好的字母不像是对称的。这显着使设计都复杂化，以达到最高速率和相关的解码算法。该项目开发了识别字母符号的最佳位置而无需对称的技术，并引入了一种新形式的编码调制形式（称为概率置换式成型），可以达到最高可能的数据速率，同时仍允许实用解码器使用最佳的非对称字母。这项研究的成功结果的实际影响将导致地球空间和反相的高速卫星链接。本项目利用概率置换式塑造，该项目使用实用的低密度平等检查（LDPC）接近通道容量。即使最佳输入分布不对称，解码器也是如此。这种方法避免了使用多阶段解码的多层编码的复杂性和错误传播。它还避免了与关节去映射和解码相关的延迟和性能损失。该项目还利用Blahut-Arimoto算法的修改开发了一种新的优化技术，该技术会动态地重新分配质量点的位置。动态分配Blahut-Arimoto不仅以特定的信噪比为特征解决方案，而且还表征了最小基数最佳最佳有限支持分布的整个演变，因为通道容量在整个兴趣范围内都会增加。在这些有限支持分布的家族的背景下，这些分布本质上是不对称的，概率的置换构成，建立在现有的概率振幅构成框架上，以提供灵活而实用的编码调制解决方案，这些解决方案支持整个非均匀分布的家庭该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力优点和更广泛的影响审查标准的评估来支持的。