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Found 25 papers, 1 papers with code
Robust Federated Learning for Wireless Networks: A Demonstration with Channel Estimation
Federated learning (FL) offers a privacy-preserving collaborative approach for training models in wireless networks, with channel estimation emerging as a promising application.
3D Cooperative Localization in UAV Systems: CRLB Analysis and Security Solutions
The MAGD adapts the gradient descent algorithm to handle the configuration changes in cooperative localization systems, ensuring accurate localization in dynamic scenarios.
A Short Overview of 6G V2X Communication Standards
We are on the verge of a new age of linked autonomous cars with unheard-of user experiences, dramatically improved air quality and road safety, extremely varied transportation settings, and a plethora of cutting-edge apps.
A Reliable and Resilient Framework for Multi-UAV Mutual Localization
This paper presents a robust and secure framework for achieving accurate and reliable mutual localization in multiple unmanned aerial vehicle (UAV) systems.
Evaluating the Impact of Numerology and Retransmission on 5G NR V2X Communication at A System-Level Simulation
To meet the stringent reliability and latency requirements of C-V2X communication, we suggest and assess a retransmission scheme along with a scheme that incorporates varying resource allocations for retransmission in NR V2X communication.
A Secure and Robust Approach for Distance-Based Mutual Positioning of Unmanned Aerial Vehicles
Unmanned aerial vehicle (UAV) is becoming increasingly important in modern civilian and military applications.
Machine Learning for QoS Prediction in Vehicular Communication: Challenges and Solution Approaches
This proactive behavior of the network can be leveraged to sustain, for example, a specific quality of service requirement.
Explainable Artificial Intelligence (XAI)
Feature Engineering
Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies
The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities.
Trust-Awareness to Secure Swarm Intelligence from Data Injection Attack
Enabled by the emerging industrial agent (IA) technology, swarm intelligence (SI) is envisaged to play an important role in future industrial Internet of Things (IIoT) that is shaped by Sixth Generation (6G) mobile communications and digital twin (DT).
Modeling the System-Level Reliability towards a Convergence of Communication, Computing and Control
Enabled and driven by modern advances in wireless telecommunication and artificial intelligence, the convergence of communication, computing, and control is becoming inevitable in future industrial applications.
Signal Restoration and Channel Estimation for Channel Sounding with SDRs
Based on these considerations, in this work, a practical algorithm is devised to compensate for the drawbacks of using SDRs for channel sounding encountered in a concrete setup.
Massive Twinning to Enhance Emergent Intelligence
As a complement to conventional AI solutions, emergent intelligence (EI) exhibits competitiveness in 6G IIoT scenario for its various outstanding features including robustness, protection to privacy, and scalability.
Mobility prediction Based on Machine Learning Algorithms
Nowadays mobile communication is growing fast in the 5G communication industry.
AI-Empowered VNF Migration as a Cost-Loss-Effective Solution for Network Resilience
With a wide deployment of Multi-Access Edge Computing (MEC) in the Fifth Generation (5G) mobile networks, virtual network functions (VNF) can be flexibly migrated between difference locations, and therewith significantly enhances the network resilience to counter the degradation in quality of service (QoS) due to network function outages.
An Abstracted Survey on 6G: Drivers, Requirements, Efforts, and Enablers
As of today, 5G mobile systems have been already widely rolled out, it is the right time for academia and industry to explore the next generation mobile communication system beyond 5G.
Networking and Internet Architecture
ARENA: A Data-driven Radio Access Networks Analysis of Football Events
Mass events represent one of the most challenging scenarios for mobile networks because, although their date and time are usually known in advance, the actual demand for resources is difficult to predict due to its dependency on many different factors.
LACO: A Latency-Driven Network Slicing Orchestration in Beyond-5G Networks
Network Slicing is expected to become a game changer in the upcoming 5G networks and beyond, enlarging the telecom business ecosystem through still-unexplored vertical industry profits.
Platoon--assisted Vehicular Cloud in VANET: Vision and Challenges
Based on these facts, the authors of this paper presented a visionary concept -- "platoon-assisted vehicular cloud" -- that exploits underutilized resources in platoons to augment vehicular cloud aiming to provide cost-effective and on-demand computing resources.
Machine Learning for Network Slicing Resource Management: A Comprehensive Survey
The emerging technology of multi-tenancy network slicing is considered as an essential feature of 5G cellular networks.
Supervised Learning for Physical Layer based Message Authentication in URLLC scenarios
PHYSEC based message authentication can, as an alternative to conventional security schemes, be applied within \gls{urllc} scenarios in order to meet the requirement of secure user data transmissions in the sense of authenticity and integrity.
A Machine Learning Method for Prediction of Multipath Channels
In this paper, a machine learning method for predicting the evolution of a mobile communication channel based on a specific type of convolutional neural network is developed and evaluated in a simulated multipath transmission scenario.
A Machine-Learning Phase Classification Scheme for Anomaly Detection in Signals with Periodic Characteristics
In this paper we propose a novel machine-learning method for anomaly detection applicable to data with periodic characteristics where randomly varying period lengths are explicitly allowed.
An AI-driven Malfunction Detection Concept for NFV Instances in 5G
Efficient network management is one of the key challenges of the constantly growing and increasingly complex wide area networks (WAN).
Slice as an Evolutionary Service: Genetic Optimization for Inter-Slice Resource Management in 5G Networks
In the context of Fifth Generation (5G) mobile networks, the concept of "Slice as a Service" (SlaaS) promotes mobile network operators to flexibly share infrastructures with mobile service providers and stakeholders.
Application of Machine Learning for Channel based Message Authentication in Mission Critical Machine Type Communication
Beside unfulfilled reliability requirements, the availability of a system can further be reduced, if it is under attack in the sense of violation of information security goals such as data authenticity or integrity.
Networking and Internet Architecture Signal Processing
