• Research Areas
1. Communicaton-Computing Co-Design for Semantic Communications

• Goal
• Maximizing the performance of semantic communications and implementing a real-time computer vision transmission system


• Approach
• Joint optimization of communication and computing resources
• Breakthrough the tradeoff performances among fidelity, energy, and delay


• Issues
• Maximizing accuracy while ensuring end-to-end latency for real-time intelligent surveillance services
• Minimizing energy consumption while guaranteeing precision for real-time immersive 3D/VR monitoring services
• Minimizing energy-latency costs while ensuring fidelity for real-time interactive XR conferencing services
• Implementation and performance evaluation of a real-time computer vision transmission system in virtual and real environments

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2. Machine Learning-based Communications and Networks

• Goal
• Achieve fully autonomic operation, maximum throughput, minimum cost through machine learning


• Approach
• Solve CN & SON issues by applying ML algorithm


• Issues
• ML-based Optimization of Communication Networks
• Deep Learning-based Resource Allocation and Optimization
• Multi-Agent Reinforcement Learning Algorithms for Optimization
• Computing and Networking for Machine Learning Services
• Joint Optimization of Cooperative Inference and Resource Allocation for Intelligent Surveillance
• In-Network Computing for 3D Video Transmission

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3. Bio-Inspired Self-Organizing Communication and Networks

• Goal
• Achieve a self-organized networking with low overhead while gauranteeing user quality of service


• Approach
• Apply bio-inspired algorithms (e.g., ACO, Flocking algorithm, Firefly synch/desync., etc)


• Issues
• Bio-Inspired Routing
• Regional Route Maintenance Protocol Based on Local Pheromone Diffusion
• Bio-Inspired Routing Protocol Based on Pheromone Diffusion
• Bio-Inspired Resource Management
• Bio-inspired Resource Allocation Algorithms and MAC Protocol Design
• Bio-Inspired Transmit Power Control
• Bio-inspired Fair Resource-Allocation Algorithm
• Bio-Inspired Energy Saving
• Biologically Inspired Power Control Algorithm for Energy-Efficient Cellular Networks
• Bio-Inspired Uplink Power Control for Energy-Efficient Mobile Stations
• Bio-Inspired Fast Consensus
• Optimal Number of Neighbors for Fast Consensus
• Coverage Control for Fast Consensus
• Performance Evaluation of Biologically Inspired Consensus Algorithm
• Bio-Inspired System Modeling and Engineering
• Principles, Applications, and Challenges of Synchronization in Nature
• Self-Organization in Mobile Networking Systems
• 생체모방 알고리즘 기반 통신 네트워크 기술
• 자연계 동조 현상의 이해와 공학적 활용 방안

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4. Next-Generation Wireless Communications and Networks

• Goal
• Maximize data rate and energy efficiency while guaranteeing the seamless connectivity


• Issues
• Wireless Energy Harvesting
• Adaptive Wireless-powered Relaying Protocols
• Wireless-Powered Two-Way Relaying Protocols
• Harvest or Access Protocol (IEEE TVT submitted)
• Cooperative Interference Management
• Cyclic Interference Alignment
• Hierarchical Interference Alignment
• Interfering Channel Alignment
• Device-to-Device Communication Assisted Interference Mitigation
• Distributed Resource Management & Access Control
• MP-CSMA/CR
• Carrier Sense Multiple Access with Collision Resolution (CSMA/CR)
• Distributed Transmit Power Control
• Joint Scheduling and Power Control
• Ultra-Low Power Management
• User State Transition Mechanisms
• LTE Power-Saving Mechanisms
• Power-Saving Mode for Mobile VoIP Services
• Seamless Connectivity Management
• Ad Hoc Cooperative Vertical Handoff
• Vertical Handover for Multi-Layered Real-Time Video
• Opportunistic Vertical Handover
• Optimal Handover Decision Algorithms
• Energy-aware Source Routing in MANET