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The identification of channel scenarios in wireless systems plays a crucial role in channel modeling, radio fingerprint positioning, and transceiver design. Traditional methods to classify channel scenarios are based on typical statistical…

Machine Learning · Computer Science 2025-06-17 Yuan Li , Zhong Zheng , Chang Liu , Zesong Fei

Electron beam probe (EBP) is a new principle detector, which makes use of a low-intensity and low-energy electron beam to measure the transverse profile, bunch shape, beam neutralization and beam wake field of an intense beam with small…

In this paper, we propose the joint interference cancellation, fast fading channel estimation, and data symbol detection for a general interference setting where the interfering source and the interfered receiver are unsynchronized and…

Signal Processing · Electrical Eng. & Systems 2020-05-12 Minh Tri Nguyen , Long Bao Le

In vibration-based condition monitoring, optimal filter design improves fault detection by enhancing weak fault signatures within vibration signals. This process involves optimising a derived objective function from a defined objective. The…

Signal Processing · Electrical Eng. & Systems 2024-05-07 Stephan Schmidt , Daniel N. Wilke , Konstantinos C. Gryllias

Many real-world systems modeled using partial differential equations (PDEs) involve unknown parameters that must be estimated from limited, noisy system observations. While typically assumed to be constants, some of these unobserved…

Methodology · Statistics 2025-08-19 Andrea Arnold

We consider a network of single-antenna sensors that observe an unknown deterministic parameter. Each sensor applies a phase shift to the observation and the sensors simultaneously transmit the result to a multi-antenna fusion center (FC).…

Information Theory · Computer Science 2015-06-11 Feng Jiang , Jie Chen , A. Lee Swindlehurst

This paper describes an expectation propagation (EP) method for multi-class classification with Gaussian processes that scales well to very large datasets. In such a method the estimate of the log-marginal-likelihood involves a sum across…

Machine Learning · Statistics 2017-06-23 Carlos Villacampa-Calvo , Daniel Hernández-Lobato

We present the tree-structure expectation propagation (Tree-EP) algorithm to decode low-density parity-check (LDPC) codes over discrete memoryless channels (DMCs). EP generalizes belief propagation (BP) in two ways. First, it can be used…

Information Theory · Computer Science 2015-03-19 Pablo M. Olmos , Juan José Murillo-Fuentes , Fernando Pérez-Cruz

This paper proposes new accurate approximations for average error probability (AEP) of a communication system employing either $M$-phase-shift keying (PSK) or differential quaternary PSK with Gray coding (GC-DQPSK) modulation schemes over…

Information Theory · Computer Science 2020-09-29 Yassine Mouchtak , Faissal El Bouanani

Many applications require that we learn the parameters of a model from data. EM is a method used to learn the parameters of probabilistic models for which the data for some of the variables in the models is either missing or hidden. There…

Machine Learning · Computer Science 2013-01-30 Luis E. Ortiz , Leslie Pack Kaelbling

Extremely large-scale antenna array (ELAA) systems emerge as a promising technology in beyond 5G and 6G wireless networks to support the deployment of distributed architectures. This paper explores the use of ELAAs to enable joint…

Modern wireless machine-to-machine-type communications aim to provide both ultra reliability and low latency, stringent requirements that appear to be mutually exclusive. From the noisy channel coding theorem, we know that reliable…

Information Theory · Computer Science 2020-12-04 Diego Barragán Guerrero , Minh Au , Ghyslain Gagnon , François Gagnon , Pascal Giard

The sensitivity of gravitational-wave (GW) detectors is characterized by their noise curves, which determine the detector's reach and ability to measure the parameters of astrophysical sources accurately. The detector noise is typically…

Instrumentation and Methods for Astrophysics · Physics 2025-03-21 Sumit Kumar , Alexander H. Nitz , Xisco Jiménez Forteza

Quantum sensors are an ideal candidate for detecting weak electromagnetic signals because of their exceptional sensitivity and compact form factor. In this work, we analyze the performance of a quantum-sensor-based receive chain for…

Quantum Physics · Physics 2026-02-10 William M. Watkins , Leigh Norris , Paraj Titum

This paper analyzes the unified performance of energy detection (ED) of spectrum sensing (SS) over generalized fading channels in cognitive radio (CR) networks. The detective performance of SS schemes will be obviously affected by fading…

Information Theory · Computer Science 2018-01-01 He Huang , Chaowei Yuan

We present a message passing approach to Expected Free Energy (EFE) minimization on factor graphs, based on the theory introduced in arXiv:2504.14898. By reformulating EFE minimization as Variational Free Energy minimization with epistemic…

Artificial Intelligence · Computer Science 2026-03-03 Wouter W. L. Nuijten , Mykola Lukashchuk , Thijs van de Laar , Bert de Vries

A distributed detection scheme where the sensors transmit with constant modulus signals over a Gaussian multiple access channel is considered. The deflection coefficient of the proposed scheme is shown to depend on the characteristic…

Information Theory · Computer Science 2017-04-05 Cihan Tepedelenlioglu , Sivaraman Dasarathan

Channel knowledge map (CKM) is an emerging technique to enable environment-aware wireless communications, in which databases with location-specific channel knowledge are used to facilitate or even obviate real-time channel state information…

Information Theory · Computer Science 2021-08-17 Kun Li , Peiming Li , Yong Zeng , Jie Xu

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless…

Information Theory · Computer Science 2015-11-25 Seunghyun Lee , Rui Zhang

Variational autoencoders (VAEs) have been used extensively to discover low-dimensional latent factors governing neural activity and animal behavior. However, without careful model selection, the uncovered latent factors may reflect noise in…

Machine Learning · Computer Science 2023-12-13 Julia Huiming Wang , Dexter Tsin , Tatiana Engel