English
Related papers

Related papers: Ripple Distribution for Nonlinear Fibre-Optic Chan…

200 papers

Channel capacity bounds are derived for a point-to-point indoor visible light communications (VLC) system with signal-dependent Gaussian noise. Considering both illumination and communication, the non-negative input of VLC is constrained by…

Information Theory · Computer Science 2020-11-03 Jin-Yuan Wang , Xian-Tao Fu , Rong-Rong Lu , Jun-Bo Wang , Min Lin , Julian Cheng

This paper adds to the understanding of the capacity region of the Gaussian interference channel. To this end, the capacity region of the one-sided Gaussian interference channel is first fully characterized. This is accomplished by…

Information Theory · Computer Science 2015-09-22 Mojtaba Vaezi , H. Vincent Poor

For a continuous-time additive white Gaussian noise (AWGN) channel with possible feedback, it has been shown that as sampling gets infinitesimally fine, the mutual information of the associative discrete-time channels converges to that of…

Information Theory · Computer Science 2020-08-26 Guangyue Han , Shlomo Shamai

In a wireless network with a single source and a single destination and an arbitrary number of relay nodes, what is the maximum rate of information flow achievable? We make progress on this long standing problem through a two-step approach.…

Information Theory · Computer Science 2016-11-18 Salman Avestimehr , Suhas Diggavi , David Tse

Dissipation is a ubiquitous phenomenon in dynamical systems encountered in nature because no finite system is fully isolated from its environment. In optical systems, a key challenge facing any technological application has traditionally…

Optics · Physics 2014-10-20 Konstantinos G. Makris , Li Ge , Hakan E. Tureci

We consider the transmission of a memoryless bivariate Gaussian source over an average-power-constrained one-to-two Gaussian broadcast channel. The transmitter observes the source and describes it to the two receivers by means of an…

Information Theory · Computer Science 2009-03-20 Shraga Bross , Amos Lapidoth , Stephan Tinguely

This paper considers a discrete time-Poisson noise channel which is used to model pulse-amplitude modulated optical communication with a direct-detection receiver. The goal of this paper is to obtain insights into the capacity and the…

Information Theory · Computer Science 2021-11-23 Luca Barletta , Alex Dytso

We present an achievable rate for general deterministic relay networks, with broadcasting at the transmitters and interference at the receivers. In particular we show that if the optimizing distribution for the information-theoretic cut-set…

Information Theory · Computer Science 2007-10-24 A. S. Avestimehr , S. N. Diggavi , D. N. C. Tse

In wireless networks, the knowledge of nodal distances is essential for several areas such as system configuration, performance analysis and protocol design. In order to evaluate distance distributions in random networks, the underlying…

Information Theory · Computer Science 2012-01-24 Sunil Srinivasa , Martin Haenggi

$M$-ary signal transmission over AWGN channel with additive $Q$-ary interference where the sequence of i.i.d. interference symbols is known causally at the transmitter is considered. Shannon's theorem for channels with side information at…

Information Theory · Computer Science 2007-07-13 Hamid Farmanbar , Amir K. Khandani

In Shannon information theory the capacity of a memoryless communication channel cannot be increased by the use of feedback from receiver to sender. In this paper the use of classical feedback is shown to provide no increase in the…

Quantum Physics · Physics 2007-05-23 Garry Bowen , Rajagopal Nagarajan

This work introduces the particle-intensity channel (PIC) as a model for molecular communication systems and characterizes the properties of the optimal input distribution and the capacity limits for this system. In the PIC, the transmitter…

Information Theory · Computer Science 2017-05-24 Nariman Farsad , Christopher Rose , Muriel Médard , Andrea Goldsmith

Consider communication over a channel whose probabilistic model is completely unknown vector-wise and is not assumed to be stationary. Communication over such channels is challenging because knowing the past does not indicate anything about…

Information Theory · Computer Science 2013-03-21 Yuval Lomnitz , Meir Feder

Shannon-Hartley theorem can accurately calculate the channel capacity when the signal observation time is infinite. However, the calculation of finite-time mutual information, which remains unknown, is essential for guiding the design of…

Information Theory · Computer Science 2022-10-05 Jieao Zhu , Zijian Zhang , Zhongzhichao Wan , Linglong Dai

A multi-input multi-output (MIMO) Gaussian channel with two transmit antennas and two receive antennas is studied that is subject to an input peak-power constraint. The capacity and the capacity-achieving input distribution are unknown in…

Information Theory · Computer Science 2024-01-31 Alex Dytso , Luca Barletta , Gerhard Kramer

In this paper we study the problem of signal detection in Gaussian noise in a distributed setting where the local machines in the star topology can communicate a single bit of information. We derive a lower bound on the Euclidian norm that…

Information Theory · Computer Science 2022-02-28 Botond Szabo , Lasse Vuursteen , Harry van Zanten

It is known that sparse superposition codes asymptotically achieve the channel capacity over the additive white Gaussian noise channel with both maximum likelihood decoding and efficient decoding (Joseph and Barron in 2012, 2014). Takeishi…

Information Theory · Computer Science 2025-04-22 Yoshinari Takeishi , Jun'ichi Takeuchi

A comment on a recent Letter on the information capacity of nonlinear channels.

Optics · Physics 2007-05-23 Haiqing Wei , David V. Plant

A closed-form expression for a lower bound on the per soliton capacity of the nonlinear optical fibre channel in the presence of (optical) amplifier spontaneous emission (ASE) noise is derived. This bound is based on a non-Gaussian…

The Principle of Maximum Entropy is a rigorous technique for estimating an unknown distribution given partial information while simultaneously minimizing bias. However, an important requirement for applying the principle is that the…

Information Theory · Computer Science 2026-02-03 Kenneth Bogert , Matthew Kothe