ProWiN: Methods and Algorithms for Resilient Packet Header Compression

从无线节点传输的任何不需要的比特都会以两种方式损害网络：它浪费节点本身的功率和带宽，并且会对其他节点造成干扰。由于TCP/IP数据包的平均长度较短，因此现有的40-60字节的数据包头可能会造成极大的效率低下，从而激发对数据包头压缩的持续努力。不幸的是，压缩和错误恢复能力是不一致的：压缩报头会产生依赖关系，因此压缩的报头是脆弱的，容易出现错误传播。这是十多年来分组报头压缩的核心问题。本研究将通信统计理论中的强大工具应用于分组报头压缩/通信问题。这些工具在无线、有线和光通信、音频、图像和视频压缩以及大容量存储设备等方面的各种问题上取得了令人惊叹的记录。这项工作集中于设计涉及分组码、卷积码和Turbo码的系统，并将它们应用于分组报头压缩和通信，这直接影响到未来更好、更高效的无线网络的设计。

Any unneeded bit transmitted from a wireless node harms the network in two ways: it wastes the power and bandwidth of the node itself, and it creates interference for other nodes. Since TCP/IP packets are on average short, existing packet headers of 40-60 bytes can create huge inefficiencies, motivating an ongoing effort in packet header compression. Unfortunately compression and error resilience are at odds: compressing the headers creates dependencies, so the compressed headers are fragile and susceptible to error propagation. This has been the central problem in packet header compression for over a decade.This research applies powerful tools from the statistical theory of communication to the problem of packet header compression/communication. These tools have had a truly amazing track record in various problems in wireless, wireline, and optical communications, audio, image and video compression, as well as mass storage devices. This effort concentrates on the design of systems involving block codes, convolutional codes, and turbo codes and applying them to packet header compression and communication, with a direct impact on the design of better and more efficient wireless networks of the future.