New Results on AVCs with Omniscient and Myopic Adversaries

Anuj Kumar Yadav, Mohammadreza Alimohammadi, Yihan Zhang, Amitalok J. Budkuley, S. Jaggi
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Abstract

In the classic adversarial communication problem, two parties communicate over a noisy channel in the presence of a malicious jamming adversary. The arbitrarily varying channels (AVCs) offer an elegant framework to study a wide range of interesting adversary models. The optimal throughput or capacity over such AVCs is intimately tied to the underlying adversary model; in some cases, capacity is unknown and the problem is known to be notoriously hard. The omniscient adversary, one which knows the sender’s entire channel transmission a priori, is one of such classic models of interest; the capacity under such an adversary remains an exciting open problem. The myopic adversary is a generalization of that model where the adversary’s observation may be corrupted over a noisy discrete memoryless channel. Through the adversary’s myopicity, one can unify the slew of different adversary models, ranging from the omniscient adversary to one that is completely blind to the transmission (the latter is the well known oblivious model where the capacity is fully characterized).In this work, we present new results on the capacity under both the omniscient and myopic adversary models. We completely characterize the positive capacity threshold over general AVCs with omniscient adversaries. The characterization is in terms of two key combinatorial objects: the set of completely positive distributions and the CP-confusability set. For omniscient AVCs with positive capacity, we present non-trivial lower and upper bounds on the capacity; unlike some of the previous bounds, our bounds hold under fairly general input and jamming constraints. Our lower bound improves upon the generalized Gilbert-Varshamov bound for general AVCs while the upper bound generalizes the well known Elias-Bassalygo bound (known for binary and q-ary alphabets). For the myopic AVCs, we build on prior results known for the so-called sufficiently myopic model, and present new results on the positive rate communication threshold over the so-called insufficiently myopic regime (a completely insufficient myopic adversary specializes to an omniscient adversary). We present interesting examples for the widely studied models of adversarial bit-flip and bit-erasure channels. In fact, for the bit-flip AVC with additive adversarial noise as well as random noise, we completely characterize the omniscient model capacity when the random noise is sufficiently large vis-a-vis the adversary’s budget.
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具有全知和近视对手的AVCs的新结果
在经典的对抗性通信问题中,双方在存在恶意干扰对手的噪声信道上进行通信。任意变化通道(avc)为研究各种有趣的对手模型提供了一个优雅的框架。这种avc的最佳吞吐量或容量与潜在的对手模型密切相关;在某些情况下,容量是未知的,并且已知问题非常困难。无所不知的对手,即先验地知道发送方整个信道传输的对手,就是这种经典模型之一;在这样一个对手之下的能力仍然是一个令人兴奋的悬而未决的问题。近视对手是该模型的泛化,对手的观察可能在有噪声的离散无记忆信道上被破坏。通过对手的近视,我们可以统一一系列不同的对手模型,从无所不知的对手到对传输完全视而不见的对手(后者是众所周知的遗忘模型,其能力得到了充分的表征)。在这项工作中,我们提出了在全知和短视对手模型下的能力的新结果。我们完全描述了具有全知对手的普通avc的正容量阈值。表征是根据两个关键的组合对象:完全正分布集和cp -混淆集。对于具有正容量的全知avc,我们给出了其容量的非平凡下界和上界;与之前的一些边界不同,我们的边界在相当一般的输入和干扰约束下成立。我们的下界改进了一般avc的广义Gilbert-Varshamov界,而上界推广了众所周知的Elias-Bassalygo界(众所周知的二进制和q-ary字母表)。对于近视avc,我们建立在所谓的充分近视模型的先前结果的基础上,并在所谓的不充分近视制度(完全不充分近视的对手专门针对无所不知的对手)上提出了关于正速率通信阈值的新结果。我们为广泛研究的对抗性比特翻转和比特擦除信道模型提供了有趣的例子。事实上,对于具有附加对抗噪声和随机噪声的位翻转AVC,当随机噪声相对于对手的预算足够大时,我们完全表征了全知模型容量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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