A5101757379- Wireless Signal Modulation Classification
- Cognitive Computing and Networks
- Cooperative Communication and Network Coding
- IPv6, Mobility, Handover, Networks, Security
- Additive Manufacturing Materials and Processes
- Energy Efficient Wireless Sensor Networks
- IoT and Edge/Fog Computing
- Robotics and Automated Systems
- High Entropy Alloys Studies
- Vehicular Ad Hoc Networks (VANETs)
- Optical Network Technologies
- Wireless Communication Security Techniques
- Caching and Content Delivery
- Privacy-Preserving Technologies in Data
- Photonic and Optical Devices
- Neural Networks and Reservoir Computing
- Traffic control and management
- High Temperature Alloys and Creep
- Digital Media Forensic Detection
- Remote Sensing and Land Use
- Landslides and related hazards
- Particle accelerators and beam dynamics
- Additive Manufacturing and 3D Printing Technologies
- 3D Surveying and Cultural Heritage
- Software-Defined Networks and 5G
University of Glasgow
2021-2025
Northwestern Polytechnical University
2023-2024
Yangtze University
2023-2024
State Key Laboratory of Remote Sensing Science
2024
Ministry of Natural Resources
2023
Beijing Municipal Ecological and Environmental Monitoring Center
2022
University of Electronic Science and Technology of China
2018-2019
Wuhan Technical College of Communications
2015
Shanghai Maritime University
2015
Southwest University
2014
We propose a transfer learning assisted deep neural network (DNN) method for optical-signal-to-noise ratio (OSNR) monitoring and realize fast remodel to response various system parameters changing, e.g. optical launch power, residual chromatic dispersion (CD) bit rate. By transferring the hyper-parameters of DNN at initial stage, we can channel variation with fewer training set size calculations save consumptions. For feature extraction processing, use amplitude histograms received 56-Gb/s...
Virtual reality (VR) over wireless is expected to be one of the killer applications in next-generation communication networks. Nevertheless, huge data volume along with stringent requirements on latency and reliability under limited bandwidth resources makes untethered VR delivery increasingly challenging. Such bottlenecks, therefore, motivate this work seek potential using semantic communication, a new paradigm that promises significantly ease resource pressure, for efficient delivery. To...
The prosperity of artificial intelligence (AI) has laid a promising paradigm communication system, i.e., intelligent semantic (ISC), where contents, instead traditional bit sequences, are coded by AI models for efficient communication. Due to the unique demand background knowledge recovery, wireless resource management faces new challenges in ISC. In this paper, we address user association (UA) and bandwidth allocation (BA) problems an ISC-enabled heterogeneous network (ISC-HetNet). We first...
Semantic communication (SemCom) has been recently deemed a promising next-generation wireless technique to enable efficient spectrum savings and information exchanges, thus naturally introducing novel practical network paradigm where cellular device-to-device (D2D) SemCom approaches coexist. Nevertheless, the involved resource management becomes complicated challenging due unique semantic performance measurements energy-consuming coding mechanism. To this end, paper jointly investigates...
We have proposed and demonstrated a transfer learning (TL)-assisted deep network (DNN) for nonlinear distortion compensation in optical side-band PAM-4 modulation direct-detection transmission. Since there exists partial correlation of distortions, we can the parameters trained DNN to target model speed up remodeling reduce complexity. conduct experiments demonstrate effectiveness scheme Nyquist transmissions. The required iterations or train size with TL be less than half that retraining...
Cache-enabled device-to-device (D2D) communication is a potential approach to tackle the resource shortage problem. However, public concerns of data privacy and system security still remain, which thus arises an urgent need for reliable caching scheme. Fortunately, federated learning (FL) with distributed paradigm provides effective way issue by training high-quality global model without any raw exchanges. Besides issue, blockchain can be further introduced into FL framework resist malicious...
Semantic communication (SemCom) is expected to be a core paradigm in future networks, yielding significant benefits terms of spectrum resource saving and information interaction efficiency. However, the existing SemCom structure limited by lack context-reasoning ability background knowledge provisioning, which, therefore, motivates us seek potential incorporating generative artificial intelligence (GAI) technologies with SemCom. Recognizing GAI's powerful capability automating creating...
Securing safe driving for connected and autonomous vehicles (CAVs) continues to be a widespread concern, despite various sophisticated functions delivered by artificial intelligence in-vehicle devices. Diverse malicious network attacks are ubiquitous, along with the worldwide implementation of Internet Vehicles, which exposes range reliability privacy threats managing data in CAV networks. Combined fact that capability existing CAVs handling intensive computation tasks is limited, this...
Semantic communication (SemCom) has recently been considered a promising solution to guarantee high resource utilization and transmission reliability for future wireless networks. Nevertheless, the unique demand background knowledge matching makes it challenging achieve efficient management multiple users in SemCom-enabled networks (SC-Nets). To this end, article investigates SemCom from networking perspective, where two fundamental problems of user association (UA) bandwidth allocation (BA)...
Semantic communication (SemCom), as an emerging paradigm focusing on meaning delivery, has recently been considered a promising solution for the inevitable crisis of scarce resources. This trend stimulates us to explore potential applying SemCom wireless vehicular networks, which normally consume tremendous amount resources meet stringent reliability and latency requirements. Unfortunately, unique background knowledge matching mechanism in makes it challenging simultaneously realize...
Abstract Improving drilling efficiency and reducing cost are new challenges for deep drilling. Based on this, a coupling impactor is designed by applying the principle of hydraulic pulse pressurization axial impact. compression structure principle, fluid flow equation flowing through mechanism mechanical balance piston body established in order to study pressure pulsation characteristics coupled fluid.
Recently, semantic communication (SemCom) has shown great potential in significant resource savings and efficient information exchanges, thus naturally introducing a novel practical cellular network paradigm where two modes of SemCom conventional bit (BitCom) coexist. Nevertheless, the involved wireless management becomes rather complicated challenging, given unique background knowledge matching time-consuming coding requirements SemCom. To this end, paper jointly investigates user...
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