Evolving Strategies for Contentious but Efficient Coexistence in Unlicensed Bands N. Clemens C. Rose WINLAB.

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Presentation transcript:

Evolving Strategies for Contentious but Efficient Coexistence in Unlicensed Bands N. Clemens C. Rose WINLAB

Our Problem: “survivor” Scenario: transceivers in an unlicensed band Transceiver Skills: ‘cognitive’ and agile Question: can transceivers learn to get along?

2 Orthogonal ChanNels Equal Cross Gains (g = 0.3) Equal Gaussian Noise Floor (N = ) System Model

The Two-Player Game Actions: quantized power allocation All power in channel 1 All power in channel 2 Spread equally in both channels Radio Interaction: mutual interference Payoff: channel capacity Strategy: past outcomes govern next action Goal: maximize average capacity

Actions and Payoffs

Player Strategy Structure History = two previous plays Next play = S(history) 9 action pairs per play 81 two-play histories (9X9) Strategy  S(k), k=1,…,81 4 Possible values for S(.) Channel 1 Channel 2 Spread Random Must find good S(.)

Strategy Search Number of Strategies: 4 81 Use Genetic Algorithms Strategy string  genome Compose population of strings Allow “fittest” strategies to “mate” Discard weaker strategies Repeat (until tired)

Experiments Start with random population Human-engineered evaluator set for comparison Completely random strategies Squatters, hoppers, avoiders Fitness measured against evaluator set Result: Populations evolve effective strategies We distill essential features

Winners’ Characteristics Winners negotiate among themselves to achieve near- optimality Winner (red) fares well against random strategies

Examples of Useful Traits Segregation: stay on your side of the fence Self-Reliance: Push me? I push you back! Callousness: exploit passivity Forgiveness: to teach and to encourage cooperation Randomize: (occasionally) to avoid repeated collision

Schema: identifying common traits Trait Characterization: Preference for a certain response Avoidance of a certain response Compose a histogram of relative trait frequencies

The Schema Skeleton Fix the observed traits in a strategy genome Choose the remaining positions randomly The performance of this is good! A handful of rules can define a “good” strategy!

Conclusion Competitive strategies for cognitive radios effective stable Implementation fix a radio with a strategy or let radios evolve strategies in situ Caveat need to try multi-player games

Thank You!