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Found 33 papers, 4 papers with code
Sample-Driven Federated Learning for Energy-Efficient and Real-Time IoT Sensing
In particular, We first formulate an optimization problem that harnesses the sampling process to concurrently reduce overfitting while maximizing accuracy.
Joint Communication and Computation Framework for Goal-Oriented Semantic Communication with Distortion Rate Resilience
Recent research efforts on semantic communication have mostly considered accuracy as a main problem for optimizing goal-oriented communication systems.
Revisiting LARS for Large Batch Training Generalization of Neural Networks
This paper explores Large Batch Training techniques using layer-wise adaptive scaling ratio (LARS) across diverse settings, uncovering insights.
Physical Layer Security for NOMA Systems: Requirements, Issues, and Recommendations
Nevertheless, from a security view-point, when multiple users are utilizing the same time-frequency resource, there may be concerns regarding keeping information confidential.
Wirelessly Powered Federated Learning Networks: Joint Power Transfer, Data Sensing, Model Training, and Resource Allocation
This work for the first time investigates a resource allocation problem in collaborative sensing-assisted sustainable FL (S2FL) networks with the goal of minimizing the total completion time.
A Survey on Federated Learning for the Healthcare Metaverse: Concepts, Applications, Challenges, and Future Directions
Recent technological advancements have considerately improved healthcare systems to provide various intelligent healthcare services and improve the quality of life.
Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics
In this survey, we first introduce several popular DL algorithms such as federated learning (FL), multi-agent Reinforcement Learning (MARL), distributed inference, and split learning, and present a comprehensive overview of their applications for UAV swarms, such as trajectory design, power control, wireless resource allocation, user assignment, perception, and satellite communications.
Edge Computing for Semantic Communication Enabled Metaverse: An Incentive Mechanism Design
Fourth, we present the design of the DL-based auction for edge resource allocation in SemCom-enabled Metaverse.
Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions
Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Label driven Knowledge Distillation for Federated Learning with non-IID Data
Moreover, leveraging the advantages of hierarchical network design, we propose a new label-driven knowledge distillation (LKD) technique at the global server to address the second problem.
Resource Allocation for Compression-aided Federated Learning with High Distortion Rate
Based on the property of a FL model, we first determine the number of IoT devices participating in the FL process.
IIFNet: A Fusion based Intelligent Service for Noisy Preamble Detection in 6G
We propose an informative instance-based fusion network (IIFNet) to cope with random noise and to improve detection performance, simultaneously.
HCFL: A High Compression Approach for Communication-Efficient Federated Learning in Very Large Scale IoT Networks
Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-Things (IoT) devices to learn a collaborative model without sending the raw data to centralized nodes for processing.
Artificial Intelligence for the Metaverse: A Survey
Many virtual environments with thousands of services and applications, from social networks to virtual gaming worlds, have been developed with immersive experience and digital transformation, but most are incoherent instead of being integrated into a platform.
Federated Learning for Smart Healthcare: A Survey
Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI).
Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions
In this article, we present a survey on the use of FL for big data services and applications, aiming to provide general readers with an overview of FL, big data, and the motivations behind the use of FL for big data.
Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence.
Federated Learning Framework with Straggling Mitigation and Privacy-Awareness for AI-based Mobile Application Services
In this work, we propose a novel framework to address straggling and privacy issues for federated learning (FL)-based mobile application services, taking into account limited computing/communications resources at mobile users (MUs)/mobile application provider (MAP), privacy cost, the rationality and incentive competition among MUs in contributing data to the MAP.
UAV Communications for Sustainable Federated Learning
Finally, simulations illustrate the potential of our proposed UAV-SFL approach in providing a sustainable solution for FL-based wireless networks, and in reducing the UAV transmit power by 32. 95%, 63. 18%, and 78. 81% compared with the benchmarks.
Transfer Learning for Future Wireless Networks: A Comprehensive Survey
Finally, we highlight important challenges, open issues, and future research directions of TL in future wireless networks.
Deep Learning for Intelligent Demand Response and Smart Grids: A Comprehensive Survey
Electricity is one of the mandatory commodities for mankind today.
Sum-Rate Maximization for UAV-assisted Visible Light Communications using NOMA: Swarm Intelligence meets Machine Learning
As the integration of unmanned aerial vehicles (UAVs) into visible light communications (VLC) can offer many benefits for massive-connectivity applications and services in 5G and beyond, this work considers a UAV-assisted VLC using non-orthogonal multiple-access.
Fusion of Federated Learning and Industrial Internet of Things: A Survey
In this paper, we provide a thorough overview on integrating FL with IIoT in terms of privacy, resource and data management.
Intelligent reflecting surface aided wireless networks-Harris Hawks optimization for beamforming design
Intelligent Reflecting Surface (IRS) is envisioned to be a promising green and cost-effective solution to enhance wireless network performance by smartly reconfiguring the signal propagation.
Networking and Internet Architecture
Energy-Efficient Design of IRS-NOMA Networks
Combining intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) is an effective solution to enhance communication coverage and energy efficiency.
Chain-Net: Learning Deep Model for Modulation Classification Under Synthetic Channel Impairment
Modulation classification, an intermediate process between signal detection and demodulation in a physical layer, is now attracting more interest to the cognitive radio field, wherein the performance is powered by artificial intelligence algorithms.
Learning Constellation Map with Deep CNN for Accurate Modulation Recognition
Modulation classification, recognized as the intermediate step between signal detection and demodulation, is widely deployed in several modern wireless communication systems.
Intelligent Radio Signal Processing: A Survey
Intelligent signal processing for wireless communications is a vital task in modern wireless systems, but it faces new challenges because of network heterogeneity, diverse service requirements, a massive number of connections, and various radio characteristics.
Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions
Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous success stories.
Swarm Intelligence for Next-Generation Wireless Networks: Recent Advances and Applications
Due to the proliferation of smart devices and emerging applications, many next-generation technologies have been paid for the development of wireless networks.
Unmanned Aerial Vehicles in Smart Agriculture: Applications, Requirements and Challenges
However, Smart Bluetooth (also referred to as Bluetooth Low Energy) is a wireless technology used to transfer data over short distances.
Reconfigurable Intelligent Surface Aided Power Control for Physical-Layer Broadcasting
Our goalis to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BSand the phase shifts of the passive elements at the RIS.
Deep Learning for Deepfakes Creation and Detection: A Survey
By reviewing the background of deepfakes and state-of-the-art deepfake detection methods, this study provides a comprehensive overview of deepfake techniques and facilitates the development of new and more robust methods to deal with the increasingly challenging deepfakes.
