Channel Coding Techniques for Low-Complexity Source Coding Applications

9415860 Zeger该项目的目标是开发有效的联合信源-信道编码技术。主要目标是从理论上深入理解信源-信道组合编码，并开发可有效应用于实际应用的实用算法，如低带宽视频压缩和低延迟语音编码。诸如移动蜂窝电话之类的非常窄的带宽传输信道需要有效的编码方案来保护所传输的源信息不受信道差错的破坏影响。以前关于信源-信道联合编码的一些工作在保护信源编码信息方面取得了有限的成功。特别是，对于低延迟实时实现，需要低复杂度技术。本项目将研究信源编码应用的信道编码技术，重点是图像、视频和语音编码应用。将研究的主题总结为：用于离散无记忆信道的低复杂度无冗余码的分类；差错控制编码将被结合到源代码设计中，并且对于具有冗余码的索引分配问题将被解决。高分辨率量化器理论将被用来研究通过噪声信道传输的信源。一些初步结果为随机指标分配提供了有用的公式，但对于最优指标分配还需要更有力的理论。对于量化和信道编码，将研究格形码。目标将是开发用于点阵源代码的高效编码算法(分别是用于信道码的解码算法)。到目前为止，初步结果已经为Leech晶格以及一些最著名的低维晶格产生了非常快的算法。将开发使用特定信源编码信息的欧几里德空间中的信道码的高效解码技术。特别是针对不等输入概率和不等差错保护的网格译码算法和理论进行了研究。这目前是一个尚未解决的问题，尽管传统解码算法的技术扩展取得了一些有限的初步成功。***

9415860 Zeger The goal of the project is to develop effective joint source-channel coding techniques. The main objectives are to achieve a deep theoretical understanding of combined source-channel codes and to develop practical algorithms that can effectively be used in real applications such as low-bandwidth video compression and low-delay speech coding. Very narrow bandwidth transmission channels, such as mobile cellular telephony, require efficient coding schemes to protect the transmitted source information from the corruptive effects of channel errors. Some previous work on joint source-channel coding has yielded limited success at protecting source coded information. In particular, low complexity techniques are needed for low delay real time implementations. This project will investigate channel coding techniques for source coding applications with an emphasis on image, video, and speech coding applications. A summary of the topics to be investigated is: Classes of low-complexity redundancy free codes for discrete memoryless channels; error control coding will be incorporated into the source code design and the index assignment problem will be addressed for codes with redundancy. High resolution quantizer theory will be studied for sources transmitting across noisy channels. Some preliminary results give useful formulas for randomized index assignments, but a much stronger theory is needed for optimal index assignment. Lattice codes will be studied both for quantization and channel coding. A goal will be to develop efficient encoding algorithms for lattice source codes (respectively, decoding algorithms for channel codes). Preliminary results so far have yielded very fast algorithms for the Leech lattice, as well as some of the best-known low dimensional lattices. Efficient decoding techniques will be developed for channel codes in Euclidean space using specific source coding information. In particular, trellis decoding algorithms and theory will be studied for unequal input probabilities and unequal error protection. This is currently an unsolved problem though extensions of techniques from traditional decoding algorithms have yielded some limited preliminary success. ***