AI techniques have great potential in providing efficient adaptation of wireless communication systems in dynamic wireless environments. Our research group has one of the largest academic teams in the UK dedicated to the application of AI to wireless communication systems.
We have successfully applied a range of AI algorithms to radio resource assignment problems. Machine learning techniques have been exploited for the purpose of channel assignment and energy-efficient topology management, including reinforcement learning, transfer learning and case-based learning. Cross-layer design is inherent in order to maximise the utility of the radio spectrum.
Projects
- Network Coded Modulation for Next Generation Wireless Access Networks (NetCodMod5)
- FP7 Aerial Base Stations with Opportunistic Links For Unexpected and Temporary Events (ABSOLUTE)
- FP7 Beyond Next Generation Mobile Broadband
- Cognitive Routing for Tactical Ad Hoc Networks
- Cognitive Radio for 5G Small Cell Systems employing Smart Antennas
- Artificial Intelligence in Cognitive and Green Radio: Lessons from Control Engineering
- Learning and Reasoning Strategies for Cognitive Radio Networks
- Application of Distributed Artificial Intelligence to Green Cognitive Radio
- Resource Allocation strategies for future Wireless M2M communication
- Cognitive Radio for 4G Communications
- Energy-efficient Topology Management for Beyond Next Generation Broadband Systems
- Energy-efficient Cognitive Radio Exploiting Antenna Beam-Forming for Ad-Hoc Networks
- Cognitive Radio for Short Range Systems
- Cognitive Routing for Wireless Ad Hoc Networks
- Reduced Complexity Cognitive Radio Systems
- Self-Organising Intelligent Wireless Systems
- Low-complexity Practical Medium Access Control Schemes for Hardware Implementation
- Bio Inspired Routing Methodologies for Wireless Sensor Networks
- Intelligent Medium Access Control Protocols for Wireless Sensor Networks
- Application of Reinforcement Learning on Medium Access Control for Wireless Sensor Networks
- Smart Dust for Large Scale Underwater Wireless Sensing