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Self-Organizing Coalitions for Conflict Evaluation and Resolution in Femtocells

Self-Organizing Coalitions for Conflict Evaluation and Resolution in Femtocells. Luis G. U. Garcia, Aalborg University Gustavo W. O. da Costa, Aalborg University Andrea F. Cattoni, Aalborg University Klaus I. Pedersen, Nokia Siemens Networks

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Self-Organizing Coalitions for Conflict Evaluation and Resolution in Femtocells

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  1. Self-Organizing Coalitions for Conflict Evaluation and Resolution in Femtocells Luis G. U. Garcia, Aalborg University Gustavo W. O. da Costa, Aalborg University Andrea F. Cattoni, Aalborg University Klaus I. Pedersen, Nokia Siemens Networks Preben E. Mogensen, Aalborg University, Nokia Siemens Networks

  2. Outline Problem and solution overview Supporting concepts Coalition formation rules Simulation scenario and results Conclusions

  3. Frequency planning / spectrum usage in cellular networks Past Current Future Heterogeneous networks including uncoordinated femtocell deployment Small macrocells with tight planned reuse (1) Large macrocells with sparse planned reuse

  4. Problem: • Massive number of femtocells  planning and optimization is too costly. • High interference possible due to dense deployment and random HeNB and UE locations. • Proposed Solution: Dynamic spectrum sharing using carrier aggregation.

  5. Proposed framework • Low load – First-come, First served • High load – Self-Organizing Coalitions for Conflict Evaluation and Resolution (SOCCER)

  6. SOCCER in a nutshell • Distributed dynamic method for spectrum sharing amongst femtocells  no need for planning. Self-optimizing. • Measurements determine incoming and outgoing SINR (BIM) • Evaluation of system capacity for different options (reuse/orthogonal allocation). • Six simple rules for formation of coalitions and redistribution of resources (component carriers) on efficient and fair way. • Enabler: low capacity HeNB to HeNB communication link, as typically assumed for ACCS. • Avoid reconfiguration storms: everything solved locally.

  7. Outline Problem and solution overview Supporting concepts Coalition formation rules Simulation scenario and results Conclusions

  8. Evaluation of coalitions • Pair wise evaluation, based on sum system capacity SINR Cell A Reuse is better SINR Cell B Orthogonal is better Strong interference bonding condition

  9. Clique 2 Maximal Clique-3 Strong Interference Bonding Graph Maximal clique sizes define the optimal local frequency reuse!

  10. Outline Problem and solution overview Supporting concepts Coalition formation rules Simulation scenario and results Conclusions

  11. CFR CFA Coalition formation rules • A coalition is a bilateral mutual agreement of having an orthogonal allocation. • New coalitions are formed when HeNB needs more spectrum. • Optimized method for maximal cliques up to size 3  only 6 simple formation rules.

  12. Coalition formation

  13. Outline Problem and solution overview Supporting concepts Coalition formation rules Simulation scenario and results Conclusions

  14. Dual stripe, 6 floors, 40 apartments per floor * Simulated scenario 25% and 75% deployment ratio * 3GPP RAN 4, “Simulation assumptions and parameters for FDD HeNB RF requirements,” Tech. Rep. R4-092042, May 2009.

  15. What is the maximal clique distribution on this scenario? 25% deployment ratio 75% deployment ratio

  16. Normalized Throughput at 25% deployment ratio

  17. Normalized Throughput at 75% deployment ratio

  18. Outline Problem and solution overview Supporting concepts Coalition formation rules Simulation scenario and results Conclusions

  19. Conclusions • Femtocell deployment should rely on self-organizing spectrum allocation • Proposal • At low traffic load  simple threshold based selection. • At high traffic load  interference management using coalitions (SOCCER). • SOCCER has a lot of potential to become practical • Simple • Very effective method • Based on standardized measurements • Applicable to LTE-Advanced as well as other systems

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