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Due to severe signal attenuation at millimeter-wave (mmWave) frequencies large antenna arrays are required at both base station and user equipment to achieve necessary beamfoming gain and compensate for the signal power loss. The initial…

Signal Processing · Electrical Eng. & Systems 2020-04-06 Veljko Boljanovic , Han Yan , Danijela Cabric

In this paper, we study several microphone channel selection and weighting methods for robust automatic speech recognition (ASR) in noisy conditions. For channel selection, we investigate two methods based on the maximum likelihood (ML)…

Sound · Computer Science 2016-10-04 Zhaofeng Zhang , Xiong Xiao , Longbiao Wang , EngSiong Chng , Haizhou Li

In this study, a channel estimator for millimeter wave (mmWave) systems is proposed. By considering the sparse nature of channels in millimeter wave band, the channel estimation problem formulated as an atomic norm minimization problem.…

Signal Processing · Electrical Eng. & Systems 2019-08-13 Mahdi Eskandari , Hamidreza Bakhshi

Accurate channel estimation is essential for reliable communication in sub-THz extremely large (XL) MIMO systems. Deploying XL-MIMO in high-frequency bands not only increases the number of antennas, but also fundamentally alters channel…

Signal Processing · Electrical Eng. & Systems 2025-04-15 Wen-Xuan Long , Marco Moretti , Michele Morelli , Luca Sanguinetti , Rui Chen

In millimeter-wave communications (MMWC), in order to compensate for high propagation attenuation, phased arrays are favored to achieve array gain by beamforming, where transmitting and receiving antenna arrays need to be jointly trained to…

Information Theory · Computer Science 2016-11-15 Zhenyu Xiao , Lin Bai , Jinho Choi

A proper channel modeling methodology that characterizes the statistics of extreme events is key in the design of a system at an ultra-reliable regime of operation. The strict constraint of ultra-reliability corresponds to the packet error…

Signal Processing · Electrical Eng. & Systems 2024-01-12 Niloofar Mehrnia , Sinem Coleri

Despite the superiority of convolutional neural networks demonstrated in time series modeling and forecasting, it has not been fully explored on the design of the neural network architecture and the tuning of the hyper-parameters. Inspired…

Machine Learning · Computer Science 2022-02-14 Xinze Zhang , Kun He , Yukun Bao

We report the performance of a 10 atm Xenon/trimethylamine time projection chamber (TPC) for the detection of X-rays (30 keV) and gamma-rays (0.511-1.275 MeV) in conjunction with the accurate tracking of the associated electrons. When…

Beam prediction is critical for reducing beam-training overhead in millimeter-wave (mmWave) systems, especially in high-mobility vehicular scenarios. This paper presents a BEV-Fusion based framework that unifies camera, LiDAR, radar, and…

Signal Processing · Electrical Eng. & Systems 2026-04-08 Jiaming Zeng , Cunhua Pan , Haoyang Weng , Ruijing Liu , Hong Ren , Jiangzhou Wang

In this letter, we investigate a novel quadrature spatial scattering modulation (QSSM) transmission technique based on millimeter wave (mmWave) systems, in which the transmitter generates two orthogonal beams targeting candidate scatterers…

Information Theory · Computer Science 2023-03-27 Xusheng Zhu , Wen Chen , Zhendong Li , Qingqing Wu , Jun Li

To glean the benefits offered by massive multi-input multi-output (MIMO) systems, channel state information must be accurately acquired. Despite the high accuracy, the computational complexity of classical linear minimum mean squared error…

Information Theory · Computer Science 2024-04-23 Bin Li , Ziping Wei , Shaoshi Yang , Yang Zhang , Jun Zhang , Chenglin Zhao , Sheng Chen

Highly directional millimeter wave (mmWave) radios need to perform beam management to establish and maintain reliable links. To do so, existing solutions mostly rely on explicit coordination between the transmitter (TX) and the receiver…

Networking and Internet Architecture · Computer Science 2021-06-09 Michele Polese , Francesco Restuccia , Tommaso Melodia

Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and throughput. Most existing work assumes the ideal channel…

Information Theory · Computer Science 2020-09-01 Shicong Liu , Zhen Gao , Jun Zhang , Marco Di Renzo , Mohamed-Slim Alouini

The rapid development of 6G systems demands advanced technologies to boost network capacity and spectral efficiency, particularly in the context of intelligent reflecting surfaces (IRS)-aided millimeter-wave (mmWave) communications. A key…

Signal Processing · Electrical Eng. & Systems 2026-01-19 Xiaokun Tuo , Zijian Chen , Ming-Min Zhao , Changsheng You , Min-Jian Zhao

The large beamforming gain used to operate at millimeter wave (mmWave) frequencies requires obtaining channel information to configure hybrid antenna arrays. Previously proposed wideband channel estimation strategies, however, assume…

Signal Processing · Electrical Eng. & Systems 2019-06-06 Javier Rodriguez-Fernandez , Nuria Gonzalez-Prelcic

In large scale dynamic wireless networks, the amount of overhead caused by channel estimation (CE) is becoming one of the main performance bottlenecks. This is due to the large number users whose channels should be estimated, the user…

Information Theory · Computer Science 2022-04-19 Mohanad Obeed , Yasser Al-Eryani , Anas Chaaban

Future wireless multiple-input multiple-output (MIMO) systems will integrate both sub-6 GHz and millimeter wave (mmWave) frequency bands to meet the growing demands for high data rates. MIMO link establishment typically requires accurate…

Signal Processing · Electrical Eng. & Systems 2025-10-16 Faruk Pasic , Lukas Eller , Stefan Schwarz , Markus Rupp , Christoph F. Mecklenbräuker

To achieve high data rates defined in 5G, the use of millimeter-waves and massive-MIMO are indispensable. To benefit from these technologies, an accurate estimation of the channel parameters is crucial. We propose a novel two-stage…

Signal Processing · Electrical Eng. & Systems 2020-07-15 Fazal-E-Asim , Felix Antreich , Charles C. Cavalcante , André L. F. de Almeida , Josef A. Nossek

The Expectation-Maximisation (EM) algorithm is a central tool in statistics and machine learning, widely used for latent-variable models such as Gaussian Mixture Models (GMMs). Despite its ubiquity, EM is typically treated as a…

Machine Learning · Computer Science 2025-09-30 Samuel Boïté , Eloi Tanguy , Julie Delon , Agnès Desolneux , Rémi Flamary

While the tracking of multiple extended targets demands for sophisticated algorithms to handle the high complexity inherent to the task, it also requires low runtime for online execution in real-world scenarios. In this work, we derive a…

Systems and Control · Electrical Eng. & Systems 2024-11-19 Christian Gramsch , Shishan Yang , Hosam Alqaderi
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