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Recent trends in learning wireless policies attempt to develop deep neural networks (DNNs) for handling multiple tasks with a single model. Existing approaches often rely on large models, which are hard to pre-train and fine-tune at the…

Signal Processing · Electrical Eng. & Systems 2025-09-11 Yuxuan Duan , Chenyang Yang

We study joint downlink-uplink beamforming design for wireless federated learning (FL) with a multi-antenna base station. Considering analog transmission over noisy channels and uplink over-the-air aggregation, we derive the global model…

Information Theory · Computer Science 2023-07-04 Chong Zhang , Min Dong , Ben Liang , Ali Afana , Yahia Ahmed

The tunable properties of molecular materials place them among the favorites for a variety of future generation devices. In addition, to maintain the current trend of miniaturization of those devices, a departure from the present top-down…

In this paper, we experimentally and theoretically show the improvement in noise characteristics in a distributed Raman amplifier (DRA) system for wavelength division multiplexing (WDM) transmission, utilizing our proposed pumping…

In this article, we study the joint communication and sensing (JCAS) paradigm in the context of millimeter-wave (mm-wave) mobile communication networks. We specifically address the JCAS challenges stemming from the full-duplex operation and…

Signal Processing · Electrical Eng. & Systems 2021-09-14 Carlos Baquero Barneto , Taneli Riihonen , Sahan Damith Liyanaarachchi , Mikko Heino , Nuria González-Prelcic , Mikko Valkama

We introduce, design, and evaluate a set of universal receiver beamforming techniques. Our approach and system DEFORM, a Deep Learning (DL) based RX beamforming achieves significant gain for multi antenna RF receivers while being agnostic…

Networking and Internet Architecture · Computer Science 2022-03-21 Hai N. Nguyen , Guevara Noubir

This paper designs a novel hybrid (a mixture of analog and digital) beamforming and examines the relation between the hybrid and digital beamformings for downlink multiuser massive multiple input multiple output (MIMO) systems. We assume…

Optimization and Control · Mathematics 2014-07-04 Tadilo Endeshaw Bogale , Long Bao Le

Performative prediction is a framework that captures distribution shifts that occur during the training of machine learning models due to their deployment. As the trained model is used, data generation causes the model to evolve, leading to…

Machine Learning · Computer Science 2025-11-10 Xue Zheng , Tian Xie , Xuwei Tan , Aylin Yener , Xueru Zhang

We investigate analytically the coupling of a coplanar waveguide resonator to a coplanar waveguide feedline. Using a conformal mapping technique we obtain an expression for the characteristic mode impedances and coupling coefficients of an…

Signal Processing · Electrical Eng. & Systems 2018-05-24 Ilya Besedin , Alexey P. Menushenkov

Model merging (e.g., via interpolation or task arithmetic) fuses multiple models trained on different tasks to generate a multi-task solution. The technique has been proven successful in previous studies, where the models are trained on…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Yi-Lin Sung , Linjie Li , Kevin Lin , Zhe Gan , Mohit Bansal , Lijuan Wang

Multicast beamforming is a promising technique for multicast communication. Providing an efficient and powerful beamforming design algorithm is a crucial issue because multicast beamforming problems such as a max-min-fair problem are…

Information Theory · Computer Science 2020-04-21 Satoshi Takabe , Tadashi Wadayama

This paper investigates the performance of optimal single stream beamforming schemes in multiple-input multiple-output (MIMO) dual-hop amplify-and-forward (AF) systems. Assuming channel state information is not available at the source and…

Information Theory · Computer Science 2016-11-17 Caijun Zhong , Tharm Ratnarajah , Shi Jin , Kai Kit Wong

Beamforming and precoding/combining are techniques aimed at processing multiantenna signals at the transmitter and/or at the receiver of a wireless communication system. While they have been routinely used to improve performance in current…

Signal Processing · Electrical Eng. & Systems 2020-04-13 Donatella Darsena , Giacinto Gelli , Francesco Verde

In the era of large language models, model merging is a promising way to combine multiple task-specific models into a single multitask model without extra training. However, two challenges remain: (a) interference between different models…

Computation and Language · Computer Science 2024-10-15 Zhenyi Lu , Chenghao Fan , Wei Wei , Xiaoye Qu , Dangyang Chen , Yu Cheng

The increasing popularity of spatial audio in applications such as teleconferencing, entertainment, and virtual reality has led to the recent developments of binaural reproduction methods. However, only a few of these methods are…

Audio and Speech Processing · Electrical Eng. & Systems 2025-02-17 Ami Berger , Vladimir Tourbabin , Jacob Donley , Zamir Ben-Hur , Boaz Rafaely

Audio zooming, a signal processing technique, enables selective focusing and enhancement of sound signals from a specified region, attenuating others. While traditional beamforming and neural beamforming techniques, centered on creating a…

Audio and Speech Processing · Electrical Eng. & Systems 2023-11-23 Meng Yu , Dong Yu

With the rise of diffusion models, audio-video generation has been revolutionized. However, most existing methods rely on separate modules for each modality, with limited exploration of unified generative architectures. In addition, many…

Multimedia · Computer Science 2025-07-08 Lei Zhao , Linfeng Feng , Dongxu Ge , Rujin Chen , Fangqiu Yi , Chi Zhang , Xiao-Lei Zhang , Xuelong Li

Radiometeric CMB measurements need to be highly stable and this stability is best obtained with differential receivers. The residual 1/f noise in the differential output is strongly dependent on the radiometer input offset which can be…

In this paper we consider the generation of discrete white noise. Despite this seems to be a simple problem, common noise generator implementations do not deliver comparable results at different sampling rates. First we define what we mean…

Sound · Computer Science 2011-03-22 Henning Thielemann

Numerous explainability methods have been proposed to shed light on the inner workings of GNNs. Despite the inclusion of empirical evaluations in all the proposed algorithms, the interrogative aspects of these evaluations lack diversity. As…

Machine Learning · Computer Science 2024-03-15 Mert Kosan , Samidha Verma , Burouj Armgaan , Khushbu Pahwa , Ambuj Singh , Sourav Medya , Sayan Ranu
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