1 / 17

Game Theory and Cognitive Radio

Work Sponsors. Office of Naval ResearchGrant Number N00014-03-1-0629National Science FoundationIntegrated Research and Education in Advanced Networking

tirza
Download Presentation

Game Theory and Cognitive Radio

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. Game Theory and Cognitive Radio James (Jody) Neel Friday, Nov. 19, 2004

    2. Work Sponsors Office of Naval Research Grant Number N00014-03-1-0629 National Science Foundation Integrated Research and Education in Advanced Networking – an IGERT program MPRG Affiliates Program

    3. Presentation Objectives Describe how/when game theory applies to cognitive radio. Give a brief example.

    4. Level 0 SDR 1 Goal Driven 2 Context Aware 3 Radio Aware 4 Planning 5 Negotiating 6 Learns Environment 7 Adapts Plans 8 Adapts Protocols Cognition Cycle Level 0 – No Cognitive Operations Level 1 – Minimal Cognition Establishes Minimum Cognition Cycle Requires ability to observe environment Environment includes RF, Network, Location, and Time Level 2 - Knowledgeable of Application Provides context to interpret stimuli from environment May provide additional information to better decide which waveform to implement e.g. Higher throughput for Data, Lower latency for voice Level 3 – Knowledgeable of Radio, Network, Channel Utilizes specific models to improve value of observations Level 4 – Has several alternate strategies Now chooses best strategy and best waveform to implement strategy Level 5 – Possible to coordinate actions with other radios Negotiation can be “Do you know this waveform?” or “Are you willing to pay $ for this service?” Level 6 – Learning Begins Significant Increase in complexity, may require AI Learning is based on observations and decisions At this stage CR can autonomously learn new models of the environment This is used to improve observations, orientation and decisions Level 7 – New Plans are learned in addition to pre-programmed plans Level 8 – CR can invent new waveforms. Must now Generate Best Waveform in response to selected plan. Implies need to negotiate protocolsLevel 0 – No Cognitive Operations Level 1 – Minimal Cognition Establishes Minimum Cognition Cycle Requires ability to observe environment Environment includes RF, Network, Location, and Time Level 2 - Knowledgeable of Application Provides context to interpret stimuli from environment May provide additional information to better decide which waveform to implement e.g. Higher throughput for Data, Lower latency for voice Level 3 – Knowledgeable of Radio, Network, Channel Utilizes specific models to improve value of observations Level 4 – Has several alternate strategies Now chooses best strategy and best waveform to implement strategy Level 5 – Possible to coordinate actions with other radios Negotiation can be “Do you know this waveform?” or “Are you willing to pay $ for this service?” Level 6 – Learning Begins Significant Increase in complexity, may require AI Learning is based on observations and decisions At this stage CR can autonomously learn new models of the environment This is used to improve observations, orientation and decisions Level 7 – New Plans are learned in addition to pre-programmed plans Level 8 – CR can invent new waveforms. Must now Generate Best Waveform in response to selected plan. Implies need to negotiate protocols

    5. Analyzing Distributed Dynamic Behavior Dynamic benefits Improved spectrum utilization Improve QoS Many decisions may have to be localized Distributed behavior Adaptations of one radio can impact adaptations of others Interactive decisions Difficult to predict performance

    6. Is this a game?

    7. Games A game is a model (mathematical representation) of an interactive decision process. Its purpose is to create a formal framework that captures the process’s relevant information in such a way that is suitable for analysis. Different situations indicate the use of different game models.

    8. How a Normal Form Game Works

    9. Level 0 SDR 1 Goal Driven 2 Context Aware 3 Radio Aware 4 Planning 5 Negotiating 6 Learns Environment 7 Adapts Plans 8 Adapts Protocols The Cognition Cycle is a Player Level 0 – No Cognitive Operations Level 1 – Minimal Cognition Establishes Minimum Cognition Cycle Requires ability to observe environment Environment includes RF, Network, Location, and Time Level 2 - Knowledgeable of Application Provides context to interpret stimuli from environment May provide additional information to better decide which waveform to implement e.g. Higher throughput for Data, Lower latency for voice Level 3 – Knowledgeable of Radio, Network, Channel Utilizes specific models to improve value of observations Level 4 – Has several alternate strategies Now chooses best strategy and best waveform to implement strategy Level 5 – Possible to coordinate actions with other radios Negotiation can be “Do you know this waveform?” or “Are you willing to pay $ for this service?” Level 6 – Learning Begins Significant Increase in complexity, may require AI Learning is based on observations and decisions At this stage CR can autonomously learn new models of the environment This is used to improve observations, orientation and decisions Level 7 – New Plans are learned in addition to pre-programmed plans Level 8 – CR can invent new waveforms. Must now Generate Best Waveform in response to selected plan. Implies need to negotiate protocolsLevel 0 – No Cognitive Operations Level 1 – Minimal Cognition Establishes Minimum Cognition Cycle Requires ability to observe environment Environment includes RF, Network, Location, and Time Level 2 - Knowledgeable of Application Provides context to interpret stimuli from environment May provide additional information to better decide which waveform to implement e.g. Higher throughput for Data, Lower latency for voice Level 3 – Knowledgeable of Radio, Network, Channel Utilizes specific models to improve value of observations Level 4 – Has several alternate strategies Now chooses best strategy and best waveform to implement strategy Level 5 – Possible to coordinate actions with other radios Negotiation can be “Do you know this waveform?” or “Are you willing to pay $ for this service?” Level 6 – Learning Begins Significant Increase in complexity, may require AI Learning is based on observations and decisions At this stage CR can autonomously learn new models of the environment This is used to improve observations, orientation and decisions Level 7 – New Plans are learned in addition to pre-programmed plans Level 8 – CR can invent new waveforms. Must now Generate Best Waveform in response to selected plan. Implies need to negotiate protocols

    10. Cognitive Radio Network as a Game

    11. Level 0 SDR 1 Goal Driven 2 Context Aware 3 Radio Aware 4 Planning 5 Negotiating 6 Learns Environment 7 Adapts Plans 8 Adapts Protocols When Game Theory can be Applied Level 0 – No Cognitive Operations Level 1 – Minimal Cognition Establishes Minimum Cognition Cycle Requires ability to observe environment Environment includes RF, Network, Location, and Time Level 2 - Knowledgeable of Application Provides context to interpret stimuli from environment May provide additional information to better decide which waveform to implement e.g. Higher throughput for Data, Lower latency for voice Level 3 – Knowledgeable of Radio, Network, Channel Utilizes specific models to improve value of observations Level 4 – Has several alternate strategies Now chooses best strategy and best waveform to implement strategy Level 5 – Possible to coordinate actions with other radios Negotiation can be “Do you know this waveform?” or “Are you willing to pay $ for this service?” Level 6 – Learning Begins Significant Increase in complexity, may require AI Learning is based on observations and decisions At this stage CR can autonomously learn new models of the environment This is used to improve observations, orientation and decisions Level 7 – New Plans are learned in addition to pre-programmed plans Level 8 – CR can invent new waveforms. Must now Generate Best Waveform in response to selected plan. Implies need to negotiate protocolsLevel 0 – No Cognitive Operations Level 1 – Minimal Cognition Establishes Minimum Cognition Cycle Requires ability to observe environment Environment includes RF, Network, Location, and Time Level 2 - Knowledgeable of Application Provides context to interpret stimuli from environment May provide additional information to better decide which waveform to implement e.g. Higher throughput for Data, Lower latency for voice Level 3 – Knowledgeable of Radio, Network, Channel Utilizes specific models to improve value of observations Level 4 – Has several alternate strategies Now chooses best strategy and best waveform to implement strategy Level 5 – Possible to coordinate actions with other radios Negotiation can be “Do you know this waveform?” or “Are you willing to pay $ for this service?” Level 6 – Learning Begins Significant Increase in complexity, may require AI Learning is based on observations and decisions At this stage CR can autonomously learn new models of the environment This is used to improve observations, orientation and decisions Level 7 – New Plans are learned in addition to pre-programmed plans Level 8 – CR can invent new waveforms. Must now Generate Best Waveform in response to selected plan. Implies need to negotiate protocols

    12. Example Application

    13. Player Set N Set of decision making radios Individual nodes i, j ? N Actions Pi – power levels available to node i May be continuous or discrete P – power space p – power tuple (vector) pi – power level chosen by player i Nodes of interest Each node has a node or set of nodes at which it measures performance {?i} the set of nodes of interest of node i. Utility function Target SINR at node of interest Ad-hoc Power Control as a Game

    14. Two cluster ad-hoc network 11 nodes DS-SS N = 63 Path loss exponent n = 4 Power levels [-120, 20 dBm] Step size 0.1 dBm Synchronous updating Target SINR ? ~ 8.4 dB Objective Function Specific Scenario

    15. Potential Game Model Identification NE Properties (assuming compact spaces) NE Existence: All potential games have a NE NE Identification: Maximizers of V are NE Convergence Better response algorithms converge. Stability Game is stable (Lyapunov) V is a Lyapunov function Design note: If V is designed so that its maximizers are coincident with your design objective function, then NE are also optimal.

    16. Simulation Results

    17. Example Potential Games Menon – Fair Interference Avoidance (Session 1.4) Neel – SDR02 – specialized ad-hoc power control and waveform adaptations Single Cell Power Control – target SINR Ad-hoc power control – target SINR (fixed assignment) Hicks – Globecom04 – Littoral combat interference avoidance Lau - Aloha

    18. Conclusions Game theory applies to cognitive radio levels 1-6. Use of game models can greatly simplify analysis. Choice of goal and allowable adaptations largely determine applicable models.

More Related