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General Distributed Economic Framework for Dynamic Spectrum Allocation

General Distributed Economic Framework for Dynamic Spectrum Allocation. Attila VIDÁCS , László TOKA, László Kovács HSN Lab, Dept. of Telecommunications and Media Informatics Budapest University of Technology and Economics (BME-TMIT). Outline. Motivation Goal

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General Distributed Economic Framework for Dynamic Spectrum Allocation

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  1. General Distributed Economic Framework for Dynamic Spectrum Allocation Attila VIDÁCS, László TOKA, László KovácsHSN Lab, Dept. of Telecommunications and Media Informatics Budapest University of Technology and Economics (BME-TMIT) | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  2. Outline • Motivation • Goal • Scalable and distributed framework for DSA • Emphasis also on the economic perspective • Modeling approach • Spatio-temporal DSA scheme • Game Theoretic modeling • Mechanism design • Proposed allocation and pricing scheme | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  3. Motivation • Actual radio spectrum allocation is not efficient due to rigid regulation: • access-limited (i.e., big player syndrome) • peak traffic planning causes temporal underutilization since spectrum demands vary in time • spatial and spectral restrictions on frequency re-usage • Service convergence • Enabling technologies: New generation radio interfaces support flexible transmission frequencies • e.g., cognitive radio, Long Term Evolution, etc. | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  4. Goal • Spectrumdemands vary in time and space  spatio-temporal Dynamic Spectrum Allocation(DSA) • Scalable and distributed economic framework for DSA • to allocate the frequency bands for wireless service providers • with the goal of improving the efficiency of spectrum utilization; • in a self-organizing scheme in which the participants manage the allocation and pricing in a distributed way; • the central authority is present only for control purposes; • where interference is modeled in a general way; • to charge for the usage (pricing). • Methodology: • Mechanism design to assure desirable properties | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  5. Game-theoretic modeling • Our basic principles: • Overall spectrum utilization should be maximal • In the case of „conflict of interest” the frequency bands are allocated to those who „value” it most • Participants: frequency owner and nodes (users) • The model takes into account the „selfishness” of the participants (in a Game-theoretic way) • Nodes (players): frequency leasers that exploit radio bands within delimitable geographic zones (e.g., base stations) • Temporal-bounded license of frequency band units • Participants are modeled by their valuation towards spectrum • i.e., „willingness to pay” for license • Bidding: participants make bids to acquire necessary licenses to provide their service | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  6. Allocating spectrum… • Dividing spectrum is not the same as dividing other goods! • (mainly because of interference and tolerance!) • A birthday cake analogy: • People at a birthday party sitting next to each other can have neighbouring slices of the cake. • Guest don’t poke into each other’s plate. • They get (more or less) the same amount. • They use it for the same purpose. • The 12-slice cake have exactly 12 slices after cut into pieces. • The cake is cut only along one dimension („vertically”). • The first slice tastes the same as the last one. | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  7. Interference model • General, physical model (point-to-point) • more realistic than modeling by conflict graph • significant complexity of allocation • Measured SINR as inter-node effects • interference • noise • geographic coupling • service-type coupling • (power, coding, etc.) • Central authority controls and enforces transmitting power levels of nodes | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  8. Allocation and Pricing • User’s utility is based on discount estimated income from its service • Users place bids for required frequency bands • Bidding against the actual license holder *IF* inter-node interference overgrows bearable limit • If multiple bidders for the same frequency band, a second-price (or Vickrey) auction is carried out • i.e., the highest bidder wins and pays the second bid • User buy-outs may happen when a new user successfully overbids actual leaser that causes inter-node jamming • Pricing: payment division at spectrum re-selling (discounted cost) on second price | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  9. Distributed Algorithm • Strategy: • To buy out the cheapest interfering player set possible to assure own service quality • Iterative spectrum allocation algorithm: • Define interference matrix that describes inter-node effects; • Define node valuations and required frequency bands; • Every participant runs heuristic optimization to minimize cost – buys the cheapest band, conform to demand, with the cheapest necessary buy-outs. | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  10. Distributed Algorithm | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  11. Consequences • Incentive compatibility („truthfulness”) Players report their true presentation valuations when bidding for spectrum in DDSA. • Key: Vickrey-auctions, cost division • Fairness and efficiency Less interference-friendly nodes pay relatively more for the spectrum. • Only high valuation enables a node to eliminate interference. • Nodes that cause heavy interference must have high valuation • Key: iterative one-way exclusion | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  12. Evaluation • Advantages to central DSA • Temporal flexibility. • No central intelligence needed. • Scalable: distributed optimization. • Same outcome(at least for a simple simulation). • Summary: • We proposed a general dynamic DSA framework that offers a distributed mechanism design, well suited to practical employment issues. • The model handles interference effects without any restricting assumptions. • The solution provides scalable and incentive-compatible allocation and pricing mechanisms. | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

  13. http://www.hsnlab.hu Thank you for your attention | 29-30 June, 2009 | FuturICT 2009, Budapest, Hungary

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