Explicit Capacity-achieving Codes for Worst-Case Additive Errors
Venkatesan Guruswami, Adam Smith
备注：
This preprint has been withdrawn since it is superseded by arXiv:1004.4017 [cs.IT] (same authors), which contains significantly more general results. This preprint will no longer be updated by the authors.
For every p in (0,1/2), we give an explicit construction of binary codes of rate approaching "capacity" 1-H(p) that enable reliable communication in the presence of worst-case additive errors}, caused by a channel oblivious to the codeword (but not necessarily the message). Formally, we give an efficient "stochastic" encoding E(\cdot,\cdot) of messages combined with a small number of auxiliary random bits, such that for every message m and every error vector e (that could depend on m) that contains at most a fraction p of ones, w.h.p over the random bits r chosen by the encoder, m can be efficiently recovered from the corrupted codeword E(m,r) + e by a decoder without knowledge of the encoder's randomness r.
Our construction for additive errors also yields explicit deterministic codes of rate approaching 1-H(p) for the "average error" criterion: for every error vector e of at most p fraction 1's, most messages m can be efficiently (uniquely) decoded from the corrupted codeword C(m)+e. Note that such codes cannot be linear, as the bad error patterns for all messages are the same in a linear code. We also give a new proof of the existence of such codes based on list decoding and certain algebraic manipulation detection codes. Our proof is simpler than the previous proofs from the literature on arbitrarily varying channels.
We consider the additive white Gaussian noise channels. We prove that the error probability of decoding tends to one exponentially for rates above the capacity and derive the optimal exponent function. We shall demonstrate that the information spectrum approach is quite useful for investigating this problem.
The capacity-achieving input distribution of the discrete-time, additive white Gaussian noise (AWGN) channel with an amplitude constraint is discrete and seems difficult to characterize explicitly. A dual capacity expression is used to derive analytic capacity upper bounds for scalar and vector AWGN channels. The scalar bound improves on McKellips' bound and is within 0.1 bits of capacity for all signal-to-noise ratios (SNRs). The two-dimensional bound is within 0.15 bits of capacity provably up to 4.5 dB, and numerical evidence suggests a similar gap for all SNRs.
This article studies the zero-error feedback capacity of {\em causal} discrete channels with memory. First, by extending the classical zero-error feedback capacity concept, a new notion of {\em uniform zero-error feedback capacity} $ C_{0f} $ for such channels is introduced. Using this notion a tight condition for {bounded} stabilization of unstable {noisy} linear systems via causal channels is obtained, assuming no {channel} state information at either end of the channel.
It is known that for a discrete channel with correlated additive noise, the ordinary capacity with or without feedback both equal $ \log q-\mathcal{H} (Z) $, where $ \mathcal{H}(Z) $ is the entropy rate of the noise process $ Z $ and $ q $ is the alphabet size. In this paper, a class of finite-state additive noise channels is introduced. It is shown that the zero-error feedback capacity of such channels is either zero or $C_{0f} =\log q -h (Z) $, where $ h (Z) $ is the {\em topological entropy} of the noise process. A topological condition is given when the zero-error capacity is zero, with or…
This paper investigates the capacity of a communications channel that, in addition to additive white Gaussian noise, also suffers from interference caused by a co-existing radar transmission. The radar interference (of short duty-cycle and of much wider bandwidth than the intended communication signal) is modeled as an additive term whose amplitude is known and constant, but whose phase is independent and identically uniformly distributed at each channel use. The capacity achieving input distribution, under the standard average power constraint, is shown to have independent modulo and phase. T…
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Instituto de Telecomunicações and Departamento de Matemática, Instituto Superior Técnico, Universidade de Lisboa（电信研究所与数学系，技术科学高等学院，里斯本大学）；School of Electrical & Computer Engineering, Tel Aviv University（电气与计算机工程学院，特拉维夫大学）
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Deterministic Identification over Additive Gaussian Channels
Technical University of Munich（慕尼黑工业大学）；BMFTR Research Hub 6G-life（德国巴伐利亚未来基金会技术研究中心 6G-life）；Munich Center for Quantum Science and Technology (MCQST)（慕尼黑量子科学与技术中心）；Munich Quantum Valley (MQV)（慕尼黑量子谷）
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Superadditivity for Entanglement-Assisted Communication
National Taiwan University（台湾大学）；National Center for Theoretical Sciences（国家理论科学中心）；Hon Hai (Foxconn) Quantum Computing Center（鸿海（富士康）量子计算中心）；RWTH Aachen University（亚琛工业大学）
