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We investigate Early Hybrid Automatic Repeat reQuest (E-HARQ) feedback schemes enhanced by machine learning techniques as a path towards ultra-reliable and low-latency communication (URLLC). To this end, we propose machine learning methods…

信息论 · 计算机科学 2019-10-28 Nils Strodthoff , Barış Göktepe , Thomas Schierl , Cornelius Hellge , Wojciech Samek

We address the problem of allocating limited resources in a network under persistent yet statistically unknown adversarial attacks. Each node in the network may be degraded, but not fully disabled, depending on its available defensive…

数据结构与算法 · 计算机科学 2025-07-01 Mansoor Davoodi , Setareh Maghsudi

This paper studies the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC) services in a cellular network that is assisted by a reconfigurable intelligent surface (RIS). The system model…

信号处理 · 电气工程与系统科学 2021-08-06 Mohammed AL-Mekhlafi , Mohamed Amine Arfaoui , Mohamed Elhattab , Chadi Assi , Ali Ghrayeb

In this paper, a novel experienced deep reinforcement learning (deep-RL) framework is proposed to provide model-free resource allocation for ultra reliable low latency communication (URLLC). The proposed, experienced deep-RL framework can…

信息论 · 计算机科学 2020-10-15 Ali Taleb Zadeh Kasgari , Walid Saad , Mohammad Mozaffari , H. Vincent Poor

Ultra-reliable and low-latency communications (URLLC) play a vital role in factory automation. To share the situational awareness data collected from the infrastructure as raw or processed data, the system should guarantee the URLLC…

信息论 · 计算机科学 2020-03-05 Nalin Jayaweera , Dileepa Marasinghe , Nandana Rajatheva , Matti Latva-aho

In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and enhanced Mobile BroadBand (eMBB). While eMBB services focus on…

网络与互联网体系结构 · 计算机科学 2020-11-13 Madyan Alsenwi , Nguyen H. Tran , Mehdi Bennis , Shashi Raj Pandey , Anupam Kumar Bairagi , Choong Seon Hong

Computation offloading at lower time and lower energy consumption is crucial for resource limited mobile devices. This paper proposes an offloading decision-making model using federated learning. Based on the task type and the user input,…

分布式、并行与集群计算 · 计算机科学 2025-12-16 Anwesha Mukherjee , Rajkumar Buyya

Vehicular edge computing (VEC) is a promising technology to support real-time vehicular applications, where vehicles offload intensive computation tasks to the nearby VEC server for processing. However, the traditional VEC that relies on…

信号处理 · 电气工程与系统科学 2023-12-01 Qiong Wu , Wenhua Wang , Pingyi Fan , Qiang Fan , Jiangzhou Wang , Khaled B. Letaief

The growing demand for on-device large language model (LLM) inference highlights the need for efficient mobile edge computing (MEC) solutions, especially in resource-constrained settings. Speculative decoding offers a promising solution by…

机器学习 · 计算机科学 2025-12-01 Jungyeon Koh , Hyun Jong Yang

In this article, we propose a novel formulation for the resource allocation problem of a sliced and disaggregated Radio Access Network (RAN) and its transport network. Our proposal assures an end-to-end delay bound for the Ultra-Reliable…

网络与互联网体系结构 · 计算机科学 2023-06-06 Flávio G. C. Rocha , Gabriel M. F. de Almeida , Kleber V. Cardoso , Cristiano B. Both , José F. de Rezende

We introduce Variational Latent Mode Decomposition (VLMD), a new algorithm for extracting oscillatory modes and associated connectivity structures from multivariate signals. VLMD addresses key limitations of existing Multivariate Mode…

机器学习 · 计算机科学 2025-05-26 Manuel Morante , Naveed ur Rehman

In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the…

Mobile edge computing (MEC) has attracted great interests as a promising approach to augment computational capabilities of mobile devices. An important issue in the MEC paradigm is computation offloading. In this paper, we propose an…

网络与互联网体系结构 · 计算机科学 2017-06-29 Chenmeng Wang , S. Hu

Embodied vision-based real-world systems, such as mobile robots, require a careful balance between energy consumption, compute latency, and safety constraints to optimize operation across dynamic tasks and contexts. As local computation…

In the traditional cellular-based mobile edge computing (MEC), users at the edge of the cell are prone to suffer severe inter-cell interference and signal attenuation, leading to low throughput even transmission interruptions. Such edge…

系统与控制 · 电气工程与系统科学 2023-12-05 Langtian Qin , Hancheng Lu , Yuang Chen , Baolin Chong , Feng Wu

Ultra-reliable and low-latency communications (URLLC) are considered as one of three new application scenarios in the fifth generation cellular networks. In this work, we aim to reduce the user experienced delay through prediction and…

信号处理 · 电气工程与系统科学 2024-10-30 Zhanwei Hou , Changyang She , Yonghui Li , Zhuo Li , Branka Vucetic

Ultra-reliable and low-latency communication (URLLC) is a pivotal technique for enabling the wireless control over industrial Internet-of-Things (IIoT) devices. By deploying distributed access points (APs), cell-free massive multiple-input…

信息论 · 计算机科学 2023-02-21 Qihao Peng , Hong Ren , Cunhua Pan , Nan Liu , Maged Elkashlan

Ultra-reliable and low-latency communications (URLLC) is firstly proposed in 5G networks, and expected to support applications with the most stringent quality-of-service (QoS). However, since the wireless channels vary dynamically, the…

信号处理 · 电气工程与系统科学 2023-05-26 Kang Li , Pengcheng Zhu , Yan Wang , Fu-Chun Zheng , Xiaohu You

In this paper, we study resource allocation for downlink orthogonal frequency division multiple access (OFDMA) systems with the objective to enable ultra-reliable low latency communication (URLLC). To meet the stringent delay requirements…

信息论 · 计算机科学 2019-01-18 Walid R. Ghanem , Vahid Jamali , Yan Sun , Robert Schober

Large language models (LLMs) achieve remarkable generative performance, yet their output quality is dependent on the decoding strategy. While sampling-based methods (e.g., top-k, nucleus) and search-and-select based methods (e.g., beam…

机器学习 · 计算机科学 2026-05-12 Benjamin Patrick Evans , Sumitra Ganesh , Leo Ardon