- Research Areas
- Artificial Intelligence-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
- Computing and Networking for Machine Learning Services
- ML-based Communication Networks and Self-Organizing Networks
- Routing based on Collaborative Filtering Algorithm
- Dynamic Random Slot Allocation based on Bayesian Estimation
- Swarm Intelligence-based Communications 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
- Bio-Inspired Resource Management
- Bio-Inspired Energy Saving
- Bio-Inspired Fast Consensus
- Bio-Inspired System Modeling and Engineering
- Next-Generation Wireless Communications and Networks
- Goal
- Maximize data rate and energy efficiency while guaranteeing the seamless connectivity
- Issues
- Wireless Energy Harvesting
- Cooperative Interference Management
- Distributed Resource Management & Access Control
- Ultra-Low Power Management
- Seamless Connectivity Management