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Related papers: Error Rates of Capacity-Achieving Codes Are Convex

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An algorithm is presented for error correction in the surface code quantum memory. This is shown to correct depolarizing noise up to a threshold error rate of 18.5%, exceeding previous results and coming close to the upper bound of 18.9%.…

Quantum Physics · Physics 2015-06-04 James R. Wootton , Daniel Loss

Designing channel codes under low-latency constraints is one of the most demanding requirements in 5G standards. However, a sharp characterization of the performance of traditional codes is available only in the large block-length limit.…

Signal Processing · Electrical Eng. & Systems 2020-07-27 Yihan Jiang , Hyeji Kim , Himanshu Asnani , Sreeram Kannan , Sewoong Oh , Pramod Viswanath

The two-user broadcast channel (BC) with receivers connected by bidirectional cooperation links of finite capacities, known as conferencing decoders, is considered. A novel capacity region outer bound is established based on multiple…

Information Theory · Computer Science 2025-08-12 Reza K. Farsani , Wei Yu

Random coding arguments are the backbone of most channel capacity achievability proofs. In this paper, we show that in their standard form, such arguments are insufficient for proving some network capacity theorems: structured coding…

Information Theory · Computer Science 2008-02-05 Bobak Nazer , Michael Gastpar

The zero-error channel capacity is the maximum asymptotic rate that can be reached with error probability exactly zero, instead of a vanishing error probability. The nature of this problem, essentially combinatorial rather than…

Information Theory · Computer Science 2020-01-13 Nicolas Charpenay , Maël Le Treust

The rate of a network code is the ratio of the block size of the network's messages to that of its edge codewords. We compare the linear capacities and achievable rate regions of networks using finite field alphabets to the more general…

Information Theory · Computer Science 2018-01-31 Joseph Connelly , Kenneth Zeger

We consider communication over a noisy network under randomized linear network coding. Possible error mechanism include node- or link- failures, Byzantine behavior of nodes, or an over-estimate of the network min-cut. Building on the work…

Information Theory · Computer Science 2007-11-27 Andrea Montanari , Ruediger Urbanke

We study the rates of convergence in generalization error achievable by active learning under various types of label noise. Additionally, we study the general problem of model selection for active learning with a nested hierarchy of…

Statistics Theory · Mathematics 2011-03-10 Steve Hanneke

Several gaps and errors in [1] are identified and corrected. While accommodating these corrections, a rigours proof is given that the successive convex approximation algorithm in [1] for secrecy rate maximization (SRM) does generate an…

Information Theory · Computer Science 2020-10-27 Mahdi Khojastehnia , Sergey Loyka

This paper concerns the maximum coding rate at which data can be transmitted over a noncoherent, single-antenna, Rayleigh block-fading channel using an error-correcting code of a given blocklength with a block-error probability not…

Information Theory · Computer Science 2020-03-31 Alejandro Lancho , Tobias Koch , Giuseppe Durisi

Consider a problem of forward error-correction for the additive white Gaussian noise (AWGN) channel. For finite blocklength codes the backoff from the channel capacity is inversely proportional to the square root of the blocklength. In this…

Information Theory · Computer Science 2014-08-12 Yury Polyanskiy , Yihong Wu

Under which condition is quantization optimal? We address this question in the context of the additive uniform noise channel under peak amplitude and power constraints. We compute analytically the capacity-achieving input distribution as a…

Information Theory · Computer Science 2025-01-28 Jonas Stapmanns , Catarina Dias , Luke Eilers , Jean-Pascal Pfister

This work considers a Poisson noise channel with an amplitude constraint. It is well-known that the capacity-achieving input distribution for this channel is discrete with finitely many points. We sharpen this result by introducing upper…

Information Theory · Computer Science 2021-07-30 Alex Dytso , Luca Barletta , Shlomo Shamai

We show that a simple modification of the surface code can exhibit an enormous gain in the error correction threshold for a noise model in which Pauli Z errors occur more frequently than X or Y errors. Such biased noise, where dephasing…

Quantum Physics · Physics 2018-02-07 David K. Tuckett , Stephen D. Bartlett , Steven T. Flammia

For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by…

Information Theory · Computer Science 2010-06-22 Andrew R Barron , Antony Joseph

We introduce a new family of concatenated codes with an outer low-density parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code, and prove that these codes can achieve capacity under any memoryless binary-input…

Information Theory · Computer Science 2016-08-31 Chun-Hao Hsu , Achilleas Anastasopoulos

In this paper, we complement Verd\'{u}'s work on spectral efficiency in the wideband regime by investigating the fundamental tradeoff between rate and bandwidth when a constraint is imposed on the error exponent. Specifically, we consider…

Information Theory · Computer Science 2007-07-13 X. Wu , R. Srikant

We investigate the Peak-Power Limited (PPL) Additive White Gaussian Noise (AWGN) channels in which the signal is band-limited, and its instantaneous power cannot exceed the power P. This model is relevant to many communication systems;…

Information Theory · Computer Science 2024-12-10 Michael Peleg , Shlomo Shamai

We consider the problem of modulating the value of a parameter onto a band-limited signal to be transmitted over a continuous-time, additive white Gaussian noise (AWGN) channel, and estimating this parameter at the receiver. The performance…

Information Theory · Computer Science 2016-06-22 Nir Weinberger , Neri Merhav

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang
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