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Self-Organizing Coalitions for Conflict Evaluation and Resolution in Femtocells Luis G. U. Garcia, Aalborg University Gustavo W. O. da Costa, Aalborg University.

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Presentation on theme: "Self-Organizing Coalitions for Conflict Evaluation and Resolution in Femtocells Luis G. U. Garcia, Aalborg University Gustavo W. O. da Costa, Aalborg University."— Presentation transcript:

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 Conclusions Simulation scenario and results

3 Frequency planning / spectrum usage in cellular networks Large macrocells with sparse planned planned reuse PastCurrentFuture Small macrocells with tight planned planned reuse (1) Heterogeneous networks includinguncoordinated femtocell deployment

4 Problem 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 Proposed Solution: Dynamic spectrum sharing using carrier aggregation.

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

6 SOCCER in a nutshell Self-optimizing 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). simple efficientfairSix 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 Conclusions Simulation scenario and results

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

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

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

11 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. CFR CFA

12 Coalition formation

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

14 Simulated scenario Dual stripe, 6 floors, 40 apartments per floor * 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 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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