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This paper studies several problems concerning channel inclusion, which is a partial ordering between discrete memoryless channels (DMCs) proposed by Shannon. Specifically, majorization-based conditions are derived for channel inclusion…

Information Theory · Computer Science 2013-10-21 Yuan Zhang , Cihan Tepedelenlioglu

Constellation shaping is a practical and effective technique to improve the performance and the rate adaptivity of optical communication systems. In principle, it could also be used to mitigate the impact of nonlinear effects, possibly…

Information Theory · Computer Science 2022-06-08 Marco Secondini , Stella Civelli , Enrico Forestieri , Lareb Zar Khan

Digital task-oriented semantic communication (ToSC) aims to transmit only task-relevant information, significantly reducing communication overhead. Existing ToSC methods typically rely on learned codebooks to encode semantic features and…

Signal Processing · Electrical Eng. & Systems 2025-08-18 Anbang Zhang , Shuaishuai Guo , Chenyuan Feng , Shuai Liu , Hongyang Du , Geyong Min

We consider a general online stochastic optimization problem with multiple budget constraints over a horizon of finite time periods. In each time period, a reward function and multiple cost functions are revealed, and the decision maker…

Machine Learning · Computer Science 2022-07-26 Jiashuo Jiang , Xiaocheng Li , Jiawei Zhang

This paper presents a novel compressed sensing (CS) approach to high dimensional wireless channel estimation by optimizing the input to a deep generative network. Channel estimation using generative networks relies on the assumption that…

Signal Processing · Electrical Eng. & Systems 2020-06-25 Eren Balevi , Akash Doshi , Ajil Jalal , Alexandros Dimakis , Jeffrey G. Andrews

This paper investigates the design of the capacity-achieving input distribution for the discrete-time Poisson channel (DTPC) under dark current effects with low-precision analog-to-digital converters (ADCs). This study introduces an…

Signal Processing · Electrical Eng. & Systems 2025-09-23 Qianqian Li , Lintao Li , Lixiang Liu , Lei Yang , Caihong Gong , Hua Li , Shiya Hao , Xiaoming Dai

We consider a search algorithm for the output distribution that achieves the channel capacity of a discrete memoryless channel. We will propose an algorithm by iterated projections of an output distribution onto affine subspaces in the set…

Information Theory · Computer Science 2016-01-11 Kenji Nakagawa , Kohei Watabe , Takuto Sabu

A novel technique is proposed which enables each transmitter to acquire global channel state information (CSI) from the sole knowledge of individual received signal power measurements, which makes dedicated feedback or inter-transmitter…

Networking and Internet Architecture · Computer Science 2017-07-04 Chao Zhang , Vineeth Varma , Samson Lasaulce , Raphael Visoz

We consider transmission of discrete memoryless sources (DMSes) across discrete memoryless channels (DMCs) using variable-length lossy source-channel codes with feedback. The reliability function (optimum error exponent) is shown to be…

Information Theory · Computer Science 2019-04-09 Lan V. Truong , Vincent Y. F. Tan

Emotions are an essential part of human behavior that can impact thinking, decision-making, and communication skills. Thus, the ability to accurately monitor and identify emotions can be useful in many human-centered applications such as…

Machine Learning · Computer Science 2023-08-22 Nibraas Khan , Mahrukh Tauseef , Ritam Ghosh , Nilanjan Sarkar

We consider a unit memory channel, called Binary State Symmetric Channel (BSSC), in which the channel state is the modulo2 addition of the current channel input and the previous channel output. We derive closed form expressions for the…

Information Theory · Computer Science 2015-07-03 Christos K. Kourtellaris , Charalambos D. Charalambous

Channel capacity estimation plays a crucial role in beyond 5G intelligent communications. Despite its significance, this task is challenging for a majority of channels, especially for the complex channels not modeled as the well-known…

Information Theory · Computer Science 2023-12-05 Zhefan Li , Rui She , Pingyi Fan , Chenghui Peng , Khaled B. Letaief

Memoryless channels with deletion errors as defined by a stochastic channel matrix allowing for bit drop outs are considered in which transmitted bits are either independently deleted with probability $d$ or unchanged with probability…

Information Theory · Computer Science 2012-11-13 Mojtaba Rahmati , Tolga M. Duman

We study the classical problem of characterizing the channel capacity and its achieving distribution in a generic fashion. We derive a simple relation between three parameters: the input-output function, the input cost function and the…

Information Theory · Computer Science 2017-11-17 Jihad Fahs , Ibrahim Abou-Faycal

The sum capacity of a class of discrete memoryless interference channels is determined. This class of channels is defined analogous to the Gaussian Z-interference channel with weak interference; as a result, the sum capacity is achieved by…

Information Theory · Computer Science 2012-07-16 Fangfang Zhu , Biao Chen

Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals with non-smooth Riesz kernels show a rich structure as singular measures can become absolutely continuous ones and conversely. In this paper we contribute to the…

Machine Learning · Computer Science 2024-03-22 Fabian Altekrüger , Johannes Hertrich , Gabriele Steidl

The reliability function of a channel is the maximum achievable exponential rate of decay of the error probability as a function of the transmission rate. In this work, we derive bounds on the reliability function of discrete memoryless…

Information Theory · Computer Science 2023-06-13 Mohsen Heidari , Achilleas Anastasopoulos , S. Sandeep Pradhan

In this paper, the problem of determining the capacity of a communication channel is formulated as a cooperative game, between a generator and a discriminator, that is solved via deep learning techniques. The task of the generator is to…

Information Theory · Computer Science 2023-05-24 Nunzio A. Letizia , Andrea M. Tonello , H. Vincent Poor

Efficiently aggregating data from different sources is a challenging problem, particularly when samples from each source are distributed differently. These differences can be inherent to the inference task or present for other reasons:…

Machine Learning · Computer Science 2017-11-15 Matthew Staib , Sebastian Claici , Justin Solomon , Stefanie Jegelka

The capacity-distortion (C-D) trade-offs for joint state and message communications (JSMC) over single- and multi-user channels are investigated, where the transmitters have access to generalized state information and feedback while the…

Information Theory · Computer Science 2025-02-14 Xinyang Li , Yiqi Chen , Vlad C. Andrei , Aladin Djuhera , Ullrich J. Mönich , Holger Boche