非均衡信息包络与信源编码容量-时延-误码折衷
Non-equilibrium Information Envelopes and the Capacity-Delay-Error-Tradeoff of Source Coding
摘要：
本文发展了一种基于知识的方法，以建立信息和排队论之间的联系。与经典的均衡信息论不同，信息包络侧重于信源和编码器的动态，使用时间函数来限制生成的比特数。在极限下，信息包络收敛到平均行为，并分别恢复信源的熵和编码器的平均码字长度。与此相反，在短时间尺度上，并与内存的来源，它表明，从已知的平衡结果的大偏差发生不可忽略的概率。这可能会导致严重的网络延迟。与来自排队论的著名流量模型相比，信息包络考虑了信息源和编码器的功能，避免了先验假设，例如指数流量或经验的基于迹线的流量模型。使用随机网络演算的结果，包络产生的三元组的容量，延迟和错误的信源编码器的工作点的表征。在极限，假设一个最佳的编码器所需的容量接近熵与任意小的错误概率，如果允许无限大的延迟。我们推导出相应的表征通道，并证明该模型具有理想的属性的可加性，允许单独分析编码器和通道。
英文摘要：
This paper develops an envelope-based approach to establish a link between information and queueing theory. Unlike classical, equilibrium information theory, information envelopes focus on the dynamics of sources and coders, using functions of time that bound the number of bits generated. In the limit the information envelopes converge to the average behavior and recover the entropy of a source, respectively, the average codeword length of a coder. In contrast, on short time scales and for sources with memory it is shown that large deviations from known equilibrium results occur with non-negligible probability. These can cause significant network delays. Compared to well-known traffic models from queueing theory, information envelopes consider the functioning of information sources and coders, avoiding a priori assumptions, such as exponential traffic, or empirical, trace-based traffic models. Using results from the stochastic network calculus, the envelopes yield a characterization of the operating points of source coders by the triplet of capacity, delay, and error. In the limit, assuming an optimal coder the required capacity approaches the entropy with arbitrarily small probability of error if infinitely large delays are permitted. We derive a corresponding characterization of channels and prove that the model has the desirable property of additivity, that allows analyzing coders and channels separately.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
