Cognitive Engine Development for IEEE 802.22

1. Cognitive Engine Development for IEEE 802.22 Lizdabel Morales April 16th, 2007 lizdabel@vt.edu

2. Presentation Outline • Introduction • IEEE 802.22 • Cognitive Radio • CE Development Approach • Simulation and Results • Future Work

3. What is a cognitive radio? Cognitive radio Cognition cycle An enhancement on the traditional software radio concept wherein the radio is aware of its environment and its capabilities, is able to independently alter its physical layer behavior, and is capable of following complex adaptation strategies.

4. Cognitive Radio is a promising tool for… Cognitive Radio Platform • Access to spectrum • finding an open frequency and using it • Interoperability • talking to legacy radios using a variety of incompatible waveforms

5. Motivation for using “cognition” in IEEE 802.22 Systems • Using previous experience to predict: • Channel reputation • Incumbent detection • Other patterns • Protect incumbent users by being aware of the environment • Co-existence and self co-existence • Spectrum utilization improvements • Future proofing for other CR technologies “It is not known whether a CR network can offer satisfactory performance despite the injection of many new incumbent handling mechanisms…” [Cordeiro, et. al. 2005]

6. MPRG’s Development of an IEEE 802.22 Cognitive Engine • Objective was to create a Cognitive Engine for IEEE 802.22 systems • Phases I and II completed • Main Accomplishments: • Development of a solid and generic architecture for the IEEE 802.22 CE • Development of a flexible framework that allows for future design, development and testing of more sophisticated modules

7. WRAN Considered Scenario • System Description • Single WRAN BS • CPE’s with different application requests • Incumbent users – TV only and Part 74 devices • Events that trigger change in the system: • New CPE service request in the WRAN • Incumbent detected in TV channel

8. Cognitive Engine Architecture

9. Cognitive Engine Modules • Sensing Module – provides radio environment sensing results • REM– provides a snapshot of the radio scenario through time • Main Controller – decides which algorithm to use • Case and Knowledge Reasoner – provides coarse solution, starting point for the Multi-objective Optimizer • Multi-objective Optimizer – further refines the solution obtained by the CBR

10. Utility function & Performance metrics Utility function used in CE should reflect the performance metrics of cognitive WRAN systems, and weight of each performance metrics may vary with radio scenarios: • U1 = QoS satisfaction of each (uplink and downlink) connection … for adding new CPE connections • U2 = Incumbent PU protection (fast adaptation and evacuation) … more important for relocating CPEs in case PU reappears • U3 = Spectral efficiency … more important for multi-cell or large number of CPEs • U4 = Power efficiency and interference temperature reduction …more important for mobile UE and large-scale cognitive networks U = w1*U1+ w2*U2 + w3*U3+ w4*U4

11. Testing scenarios for WRAN BS CE Performance evaluation

12. REM-CKL vs. GA CKL runs much faster than GA, especially under complicated situations.

13. 802.22 Specification Scenario Detect incumbent user Update policy Deactivate uncompliant nodes Allocate resources Current framework picks up after incumbent user is detected

14. Questions