Recent Articles

Open access

ISSN: 2352-8648
CN: 50-1212/TN
p-ISSN: 2468-5925

A novel formula for micro-UAV swarm systems: architecture, algorithms, and verification

During indoor operations, Unmanned Aerial Vehicles (UAVs) are required to embody attributes such as heightened sensitivity, compact design, and robust maneuverability. A high operational advantage is...

Sensing accuracy gain, unified performance analysis and optimization in 6G cooperative ISAC systems

Sixth Generation (6G) mobile communication networks will involve sensing as a new function, with the overwhelming trend of Integrated Sensing And Communications (ISAC). Although expanding the serving...

Rate-splitting multiple access-assisted ISAC design in NAFD cell-free mMIMO systems

Integrated Sensing And Communication (ISAC) is regarded as a promising technology for facilitating the rapid advancement of Sixth-Generation (6G) due to its concurrent transmission of information and...

UAV-assisted full-duplex ISAC: Joint communication scheduling, beamforming, and trajectory optimization

This paper proposes the Unmanned Aerial Vehicle (UAV)-assisted Full-Duplex (FD) Integrated Sensing And Communication (ISAC) system. In this system, the UAV integrates sensing and communication functions,...

Research and experimental validation for 3GPP ISAC channel modeling standardization

Integrated Sensing and Communication (ISAC) is considered a key technology in 6G networks. An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems....

Integrated sensing and communication empowered by resilient massive access in SAGIN: An energy efficient perspective

As key technologies in 6G, Space-Air-Ground Integrated Networks (SAGIN) promises to provide seamless global coverage through a comprehensive, ubiquitous communication system, while Integrated Sensing...

Lightweight deep reinforcement learning for dynamic resource allocation in vehicular edge computing

Vehicular Edge Computing (VEC) enhances the quality of user services by deploying wealth of resources near vehicles. However, due to highly dynamic and complex nature of vehicular networks, centralized...

Sum-rate optimization methods and analysis for reconfigurable intelligent surface aided communication system

When deploying Reconfigurable Intelligent Surface (RIS) to improve System Sum-Rate (SSR), the timeliness and accuracy of SSR optimization methods are difficult to achieve simultaneously through a single...

Security and privacy in edge computing: a survey of electric vehicles

Electric Vehicles (EVs) have developed into a complex ecosystem that includes many technical components such as task offloading on mobile devices, the Internet of Vehicles (IoV), and smart grids. Moreover,...

Open-set blind recognition of non-binary LDPC codes

Blind encoder recognition methods have drawn much research interest in recent years, as they can play an important role in non-cooperative scenarios. This paper proposes an open-set blind recognition...

TopoLLM: LLM-driven adaptive tool learning for real-time emergency network topology planning

Communication infrastructure is often among the first casualties in natural or human-induced disasters, severely impairing the coordination and efficiency of rescue operations. Rapid deployment of Unmanned...

GCN and DRL based on dependent task offloading mechanism in edge computing

Task offloading is critical for optimizing resource allocation in edge computing systems. In practical scenarios, user applications often comprise multiple interdependent tasks, where both task dependencies...

Efficient user scheduling in mmWave networks: leveraging knowledge transfer with channel knowledge map

This paper proposes a Deep Reinforcement Learning (DRL) algorithm for user scheduling in Millimeter Wave (mmWave) networks, which utilizes Channel Knowledge Map (CKM) for knowledge transfer to enhance...

Enhanced multi-agent deep reinforcement learning for efficient task offloading and resource allocation in vehicular networks

In response to the rising demand for low-latency, computation-intensive applications in vehicular networks, this paper proposes an adaptive task offloading approach for Vehicle-to-Everything (V2X) environments....

Characterization and optimization of satellite complex networks based on hyperbolic space

In recent years, the rapid advancement of mega-constellations in Low Earth Orbit (LEO) has led to the emergence of satellite communication networks characterized by a complex interplay between high-...

Model Layered Optimization with Contrastive Learning for Personalized Federated Learning

In federated learning (FL), the distribution of data across different clients leads to the degradation of global model performance in training. Personalized Federated Learning (pFL) can address this...

Experience Replay with Cohesive-Subgraph Awareness for Continual Graph Learning in IoT

In Internet-of-Things (IoT) scenarios, Continual Graph Learning (CGL) has become a key technique for capturing the complex relational structures underlying diverse applications including sensor networks,...

Deep Reinforcement Learning-based Forwarding Node Selection Algorithm in Internet of Vehicles

Due to open communication environment, Internet of Vehicles (IoV) are vulnerable to many attacks, including the gray hole attack, which can disrupt the process of transmitting messages. And this results...

Capacity and delay performance analysis for large-scale UAV-enabled wireless networks

In this paper, we analyze the capacity and delay performance of a large-scale Unmanned Aerial Vehicle (UAV)-enabled wireless network, in which untethered and tethered UAVs deployed with content files...

Energy-saving control strategy for ultra-dense network base stations based on multi-agent reinforcement learning

Aiming at the problem of mobile data traffic surge in 5G networks, this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network (UDN)...

Accurate and efficient elephant-flow classification based on co-trained models in evolved software-defined networks

Accurate early classification of elephant flows (elephants) is important for network management and resource optimization. Elephant models, mainly based on the byte count of flows, can always achieve...

Enhancing flexibility and system performance in 6G and beyond: A user-based numerology and waveform approach

A Mixed Numerology OFDM (MN-OFDM) system is essential in 6G and beyond. However, it encounters challenges due to Inter-Numerology Interference (INI). The upcoming 6G technology aims to support innovative...

FlyCache: Recommendation-driven edge caching architecture for full life cycle of video streaming

With the rapid development of 5G technology, the proportion of video traffic on the Internet is increasing, bringing pressure on the network infrastructure. Edge computing technology provides a feasible...

Efficient modulation mode recognition based on joint communication parameter estimation in non-cooperative scenarios

Due to the neglect of the retrieval of communication parameters (including the symbol rate, the symbol timing offset, and the carrier frequency), the existing non-cooperative communication mode recognizers...

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