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This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in the context of linear inverse problems with additive Gaussian noise. We fit a GMM to given channel samples to obtain an analytic probability density…

Signal Processing · Electrical Eng. & Systems 2022-09-14 Michael Koller , Benedikt Fesl , Nurettin Turan , Wolfgang Utschick

The objective of this article is to propose and statistically validate a more general additive non-Gaussian noise distribution, which we term McLeish distribution, whose random nature can model different impulsive noise environments…

Information Theory · Computer Science 2020-03-06 Ferkan Yilmaz

Information transmission over discrete-time channels with memoryless additive noise obeying a Cauchy, rather than Gaussian, distribution, are studied. The channel input satisfies an average power constraint. Upper and lower bounds to such…

Information Theory · Computer Science 2024-11-19 Shuqin Pang , Wenyi Zhang

Accurate wireless channel estimation is critical for next-generation wireless systems, enabling precise precoding for effective user separation, reduced interference across cells, and high-resolution sensing, among other benefits.…

Signal Processing · Electrical Eng. & Systems 2026-03-03 Alireza Javid , Nuria González-Prelcic

Recent research in the design of end to end communication system using deep learning has produced models which can outperform traditional communication schemes. Most of these architectures leveraged autoencoders to design the encoder at the…

Information Theory · Computer Science 2020-01-28 Vishnu Raj , Sheetal Kalyani

This paper investigates the robust wideband channel estimation problem in the millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. In such a scenario, the beam squint effect that the array response vectors vary…

Signal Processing · Electrical Eng. & Systems 2024-09-25 Li Ge , Lin Chen , Xue Jiang , Weifeng Zhu , Qibo Qin , Xingzhao Liu

Data-driven discovery of governing equations from noisy observations remains a fundamental challenge in scientific machine learning. While GENERIC formalism informed neural networks (GFINNs) provide a principled framework that enforces the…

Machine Learning · Computer Science 2026-04-08 Jun Sur Richard Park , Auroni Huque Hashim , Siu Wun Cheung , Youngsoo Choi , Yeonjong Shin

Semantic Communication (SC) is an emerging technology aiming to surpass the Shannon limit. Traditional SC strategies often minimize signal distortion between the original and reconstructed data, neglecting perceptual quality, especially in…

Machine Learning · Computer Science 2024-08-12 Kexin Zhang , Lixin Li , Wensheng Lin , Yuna Yan , Rui Li , Wenchi Cheng , Zhu Han

In this paper, we propose to use the discretized version of the so-called Enhanced Gaussian Noise (EGN) model to estimate the non-linearity effects of fiber on the performance of optical coherent and uncompensated transmission (CUT)…

Signal Processing · Electrical Eng. & Systems 2020-02-19 Ramin Hashemi , Mehdi Habibi , Hamzeh Beyranvand , Ali Emami , Mahdi Hashemi , Davood Ranjbar Rafie

The two-user Gaussian interference channel (G-IC) is revisited, with a particular focus on practically amenable discrete input signalling and treating interference as noise (TIN) receivers. The corresponding deterministic interference…

Information Theory · Computer Science 2021-03-18 Min Qiu , Yu-Chih Huang , Jinhong Yuan

This is the second part of the two-part paper considering the communications under the bursty mixed noise composed of white Gaussian noise and colored non-Gaussian impulsive noise. In the first part, based on Gaussian distribution and…

Signal Processing · Electrical Eng. & Systems 2024-05-10 Tianfu Qi , Jun Wang , Zexue Zhao

The use of open-loop coding can be easily extended to a closed-loop concatenated code if the channel has access to feedback. This can be done by introducing a feedback transmission scheme as an inner code. In this paper, this process is…

Information Theory · Computer Science 2011-02-23 Zachary Chance , David J. Love

The use of open-loop coding can be easily extended to a closed-loop concatenated code if the channel has access to feedback. This can be done by introducing a feedback transmission scheme as an inner code. In this paper, this process is…

Information Theory · Computer Science 2011-02-23 Zachary Chance , David J. Love

Channel models are essential for the design, evaluation, and optimization of wireless communication systems. The emerging space-air-ground-sea integrated network (SAGSIN), characterized by diverse service applications and extended-spectrum…

Signal Processing · Electrical Eng. & Systems 2026-03-17 Nanhao Zhou , Chao Zou , Yu Zhou , Yanqun Tang , Xiaoying Zhang , Haoran Yin , Xuefeng Yin , Yuxiang Zhang , Dan Fei , Fan Jiang

Almost all modern communication systems rely on electromagnetic fields as a means of information transmission, and finding the capacities of these systems is a problem of significant practical importance. The Additive White Gaussian Noise…

Quantum Physics · Physics 2013-02-05 Robert Koenig , Graeme Smith

The minimum mean-square error of the estimation of a signal where observed from the additive white Gaussian noise (WGN) channel's output, is analyzed. It is assumed that the channel input's signal is composed of a (normalized) sum of N…

Information Theory · Computer Science 2007-07-13 Jacob Binia

Signal processing is crucial for satisfying the high data rate requirements of future sixth-generation (6G) wireless networks. However, the rapid growth of wireless networks has brought about massive data traffic, which hinders the…

Signal Processing · Electrical Eng. & Systems 2025-02-18 Ziheng Liu , Jiayi Zhang , Yiyang Zhu , Enyu Shi , Bo Ai

This paper considers a Gaussian channel with one transmitter and two receivers. The goal is to maximize the communication rate at the intended/primary receiver subject to a disturbance constraint at the unintended/secondary receiver. The…

Information Theory · Computer Science 2016-03-25 Alex Dytso , Ronit Bustin , Daniela Tuninetti , Natasha Devroye , H. Vincent Poor , Shlomo Shamai

In recent years, impressive progress has been made in the design of implicit probabilistic models via Generative Adversarial Networks (GAN) and its extension, the Conditional GAN (CGAN). Excellent solutions have been demonstrated mostly in…

Machine Learning · Computer Science 2020-02-06 Karan Aggarwal , Matthieu Kirchmeyer , Pranjul Yadav , S. Sathiya Keerthi , Patrick Gallinari

The most natural way to describe an information-carrying system containing a specific noise is an additive white Gaussian-noise (AWGN) channel. In bosonic quantum systems (especially the Gaussian case), although the classical information…

Quantum Physics · Physics 2019-05-14 Kabgyun Jeong , Hun Hee Lee , Youngrong Lim