Papers Intelligent Communication
“Intelligent Communication” 태그가 달린 논문 30편 · 필터 해제
From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications
With the advent of 6G communications, intelligent communication systems face multiple challenges, including constrained perception and response capabilities, limited scalability, and low adaptability in dynamic environme…
Intelligent CommunicationDeepSeek-Inspired Exploration of RL-based LLMs and Synergy with Wireless Networks: A Survey
Reinforcement learning (RL)-based large language models (LLMs), such as ChatGPT, DeepSeek, and Grok-3, have gained significant attention for their exceptional capabilities in natural language processing and multimodal da…
Edge-computingIntelligent CommunicationReinforcement Learning (RL)RMDM: Radio Map Diffusion Model with Physics Informed
With the rapid development of wireless communication technology, the efficient utilization of spectrum resources, optimization of communication quality, and intelligent communication have become critical. Radio map recon…
DenoisingIntelligent CommunicationmodelLarge Language Model-Based Semantic Communication System for Image Transmission
The remarkable success of Large Language Models (LLMs) in understanding and generating various data types, such as images and text, has demonstrated their ability to process and extract semantic information across divers…
DecoderIntelligent CommunicationLanguage ModelingLanguage Modelling+2Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities
With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. …
Industrial RobotsIntelligent CommunicationSemantic CommunicationMVX-ViT: Multimodal Collaborative Perception for 6G V2X Network Management Decisions Using Vision Transformer.
Advancements in sixth-generation (6G) networks, coupled with the evolution of multimodal sensing in vehicle-to-everything (V2X) networks, have opened avenues for transformative research into multimodal-based artificial i…
Beam PredictionIntelligent CommunicationMultimodal Deep LearningSensor FusionFiber neural networks for the intelligent optical fiber communications
Optical neural networks have long cast attention nowadays. Like other optical structured neural networks, fiber neural networks which utilize the mechanism of light transmission to compute can take great advantages in bo…
Intelligent CommunicationAdaptive Wireless Image Semantic Transmission and Over-The-Air Testing
Semantic communication has undergone considerable evolution due to the recent rapid development of artificial intelligence (AI), significantly enhancing both communication robustness and efficiency. Despite these advance…
Intelligent Communicationobject-detectionObject DetectionQuantization+1FedCRL: Personalized Federated Learning with Contrastive Shared Representations for Label Heterogeneity in Non-IID Data
Heterogeneity resulting from label distribution skew and data scarcity can lead to inaccuracy and unfairness in intelligent communication applications that mainly rely on distributed computing. To deal with it, this pape…
Contrastive LearningDistributed ComputingFairnessFederated Learning+3Deep Learning in Physical Layer: Review on Data Driven End-to-End Communication Systems and their Enabling Semantic Applications
Deep learning (DL) has revolutionized wireless communication systems by introducing datadriven end-to-end (E2E) learning, where the physical layer (PHY) is transformed into DL architectures to achieve peak optimization. …
Intelligent CommunicationRepresentation LearningSemantic CommunicationLMaaS: Exploring Pricing Strategy of Large Model as a Service for Communication
The next generation of communication is envisioned to be intelligent communication, that can replace traditional symbolic communication, where highly condensed semantic information considering both source and channel wil…
Intelligent CommunicationIntelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning
Internet of Things (IoT) technologies have enabled numerous data-driven mobile applications and have the potential to significantly improve environmental monitoring and hazard warnings through the deployment of a network…
Intelligent CommunicationMulti-agent Reinforcement Learningreinforcement-learningToward Trusted and Swift UAV Communication: ISAC-Enabled Dual Identity Mapping
The UAV network has recently emerged as a capable carrier for ubiquitous wireless intelligent communication in the B5G/6G era. Nevertheless, the separation of dual identity raises challenges from the perspective of commu…
Integrated sensing and communicationIntelligent CommunicationISACManagementSTAR-RIS-Assisted Privacy Protection in Semantic Communication System
Semantic communication (SemCom) has emerged as a promising architecture in the realm of intelligent communication paradigms. SemCom involves extracting and compressing the core information at the transmitter while enabli…
Intelligent CommunicationSemantic CommunicationDigital-SC: Digital Semantic Communication with Adaptive Network Split and Learned Non-Linear Quantization
Semantic communication, an intelligent communication paradigm that aims to transmit useful information in the semantic domain, is facilitated by deep learning techniques. Robust semantic features can be learned and trans…
image-classificationImage ClassificationIntelligent CommunicationQuantization+1Two-Bit RIS-Aided Communications at 3.5GHz: Some Insights from the Measurement Results Under Multiple Practical Scenes
In this paper, we propose a two-bit reconfigurable intelligent surface (RIS)-aided communication system, which mainly consists of a two-bit RIS, a transmitter and a receiver. A corresponding prototype verification system…
Intelligent CommunicationQuantizationEMC2-Net: Joint Equalization and Modulation Classification based on Constellation Network
Modulation classification (MC) is the first step performed at the receiver side unless the modulation type is explicitly indicated by the transmitter. Machine learning techniques have been widely used for MC recently. In…
Intelligent CommunicationWAIR-D: Wireless AI Research Dataset
It is a common sense that datasets with high-quality data samples play an important role in artificial intelligence (AI), machine learning (ML) and related studies. However, although AI/ML has been introduced in wireless…
Intelligent CommunicationSynthetic Traffic Generation with Wasserstein Generative Adversarial Networks
Network traffic data are critical for network research. With the help of synthetic traffic, researchers can readily generate data for network simulation and performance evaluation. However, the state-of-the-art traffic g…
Intelligent CommunicationSynthetic Data GenerationMulti-Agent Feedback Enabled Neural Networks for Intelligent Communications
In the intelligent communication field, deep learning (DL) has attracted much attention due to its strong fitting ability and data-driven learning capability. Compared with the typical DL feedforward network structures, …
DenoisingIntelligent Communication