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A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

We consider a channel-independent decoder which is for i.i.d. random codes what the maximum mutual-information decoder is for constant composition codes. We show that this decoder results in exactly the same i.i.d. random coding error…

Information Theory · Computer Science 2018-11-06 Sergey Tridenski , Ram Zamir

In this paper, throughput achieved in cognitive radio channels with finite blocklength codes under buffer limitations is studied. Cognitive users first determine the activity of the primary users' through channel sensing and then initiate…

Information Theory · Computer Science 2013-08-26 Gozde Ozcan , M. Cenk Gursoy

The deletion channel is the simplest point-to-point communication channel that models lack of synchronization. Input bits are deleted independently with probability d, and when they are not deleted, they are not affected by the channel.…

Information Theory · Computer Science 2011-05-02 Yashodhan Kanoria , Andrea Montanari

We study the problem of generating an approximately i.i.d. string at the output of a discrete memoryless channel using a limited amount of randomness at its input in presence of causal noiseless feedback. Feedback does not decrease the…

Information Theory · Computer Science 2016-09-29 Mani Bastani Parizi , Emre Telatar

The capacity region of the interference channel in which one transmitter non-causally knows the message of the other, termed the cognitive interference channel, has remained open since its inception in 2005. A number of subtly differing…

Information Theory · Computer Science 2015-03-13 Stefano Rini , Daniela Tuninetti , Natasha Devroye

Consider any discrete memoryless channel (DMC) with arbitrarily but finite input and output alphabets X, Y respectively. Then, for any capacity achieving input distribution all symbols occur less frequently than 1-1/e$. That is, \[…

Information Theory · Computer Science 2012-02-01 Gowtham Kumar , Alexandros Manolakos

The quantum capacity of a noisy quantum channel determines the maximal rate at which we can code reliably over asymptotically many uses of the channel, and it characterizes the channel's ultimate ability to transmit quantum information…

Quantum Physics · Physics 2021-10-26 Xin Wang

We propose an iterative method for approximately computing the capacity of discrete memoryless channels, possibly under additional constraints on the input distribution. Based on duality of convex programming, we derive explicit upper and…

Information Theory · Computer Science 2015-04-06 Tobias Sutter , David Sutter , Peyman Mohajerin Esfahani , John Lygeros

Recent advances have revealed that the rate of convergence of the expected test error in deep supervised learning decays as a function of the intrinsic dimension and not the dimension $d$ of the input space. Existing literature defines this…

Machine Learning · Statistics 2024-12-16 Saptarshi Chakraborty , Peter L. Bartlett

Shannon defined channel capacity as the highest rate at which there exists a sequence of codes of block length $n$ such that the error probability goes to zero as $n$ goes to infinity. In this definition, it is implicit that the block…

Information Theory · Computer Science 2010-06-03 Rui A. Costa , Michael Langberg , João Barros

We study the binomial channel and the structure of its capacity-achieving input and output distributions. It is known that the capacity-achieving input distribution is discrete and supported on finitely many points. The best previously…

Information Theory · Computer Science 2026-05-13 Mohammadamin Baniasadi , Luca Barletta , Alex Dytso

This paper is concerned with the problem of error-free communication over the i.i.d. duplication channel which acts on a transmitted sequence $ x_1 \cdots x_n $ by inserting a random number of copies of each symbol $ x_i $ next to the…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević

A binary code of blocklength $n$ and codebook size $M$ is called an $(n,M)$ code, which is studied for memoryless binary symmetric channels (BSCs) with the maximum likelihood (ML) decoding. For any $n \geq 2$, some optimal codes among the…

Information Theory · Computer Science 2023-07-06 Yanyan Dong , Shenghao Yang

We investigate the fundamental limits of reliable communication over multi-view channels, in which the channel output is comprised of a large number of independent noisy views of a transmitted symbol. We consider first the setting of…

Information Theory · Computer Science 2024-05-14 V. Arvind Rameshwar , Nir Weinberger

Motivated by a greedy approach for generating {\it{information stable}} processes, we prove a universal maximum likelihood (ML) upper bound on the capacities of discrete information stable channels, including the binary erasure channel…

Information Theory · Computer Science 2018-05-21 Tongxin Li

The exponential server timing channel is known to be the simplest, and in some sense canonical, queuing timing channel. The capacity of this infinite-memory channel is known. Here, we discuss practical finite-length restrictions on the…

Information Theory · Computer Science 2016-05-26 Thomas J. Riedl , Todd P. Coleman , Andrew C. Singer

Continuing our earlier work (quant-ph/0401060), we give two alternative proofs of the result that a noiseless qubit channel has identification capacity 2: the first is direct by a "maximal code with random extension" argument, the second is…

Quantum Physics · Physics 2017-08-01 Andreas Winter

In this paper, we consider noncoherent random linear coding networks (RLCNs) as a discrete memoryless channel (DMC) whose input and output alphabets consist of subspaces. This contrasts with previous channel models in the literature which…

Information Theory · Computer Science 2010-01-13 Bartolomeu F. Uchoa-Filho , Roberto W. Nobrega

Memoryless channels with synchronization errors as defined by a stochastic channel matrix allowing for symbol insertions and deletions in addition to random errors are considered. Such channels are information stable, hence their Shannon…

Information Theory · Computer Science 2011-03-01 Tolga M Duman
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