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Evolving Strategies for Contentious but Efficient Coexistence in Unlicensed Bands

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?.

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Evolving Strategies for Contentious but Efficient Coexistence in Unlicensed Bands

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

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

  3. System Model 2 Orthogonal ChanNels Equal Cross Gains (g = 0.3) Equal Gaussian Noise Floor (N = 10-3)

  4. 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

  5. 1.51.5 7.22 6.96.9 27.2 2.92.9 27.2 6.96.9 7.22 1.51.5 Actions and Payoffs

  6. 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(.)

  7. Strategy Search • Number of Strategies: 481 • Use Genetic Algorithms • Strategy string  genome • Compose population of strings • Allow “fittest” strategies to “mate” • Discard weaker strategies • Repeat (until tired)

  8. 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

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

  10. 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

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

  12. 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!

  13. 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

  14. Thank You!

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