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Interference Minimization and Uplink Relaying For a 3G/WLAN Network

Interference Minimization and Uplink Relaying For a 3G/WLAN Network. Ju Wang Virginia Commonwealth University May, 2005. Motivation. Traditional cellular network could not fulfill the massive bandwidth requirement of the mobile multimedia applications. Asynchronized uplink access

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Interference Minimization and Uplink Relaying For a 3G/WLAN Network

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  1. Interference Minimization and Uplink Relaying Fora 3G/WLAN Network Ju Wang Virginia Commonwealth University May, 2005

  2. Motivation • Traditional cellular network could not fulfill the massive bandwidth requirement of the mobile multimedia applications. • Asynchronized uplink access • Subject to intra-cell and inter-cell interference • WLAN has the range limitations. • Solution: hybrid 3G/WLAN architecture.

  3. Basic Idea • Cluster mobiles in the same cell to several clusters. • Each cluster is served by a cluster head, which functions as a relayed points. • Communications inside a cluster is through WLAN interfaces. • Only cluster heads are allowed to transmit in the 3G band. • Advantages: • Reduced transmission activities and interferences • Reduce uplink connections, making it easy for scheduling

  4. Challenges • How to select cluster heads • Centralized or discrete manner • Constraints • Optimization goals: number of cluster, maximum cluster size… • Uplink scheduling algorithms • Fair access for all mobiles • Maximizing throughput • Deal with mobile movement

  5. Clustering with Interference Minimization • We try to minimize the possible interference to other cells • Assume a 3-way sectorization • Two neighbor sectors are affected most by local transmission

  6. Problem Formulation

  7. Problem Nature • Equivalent to an instance of weighted set- cover problem, which is NP-complete. • General set cover problem does have polynomial approximation algorithm that deliver a constant upper bound. • Looking for an optimum vertex cover instead • Have good heuristic • Good chance of find a backup cluster head • In our case, the weight distribution is closely related to the physical location of mobile nodes, which might be helpful in heuristic.

  8. Cost function characterization • optimum vertex cover has as its objective to minimize the out-of-cell interference, • Minimum vertex cover is the smallest vertex cover in the non-weighted graph case. • An interesting observation: with the interference weight function, the above two set is very close to each other under the cell geometry.

  9. Case analysis with 3 nodes

  10. Pilot-assisted RMT selection • measure all PLi from mobile stations. • collect the WLAN connectivity information from all mobile stations to form the graph G(V;E). • calculate a edge path loss : ELPj = PLj1+PLj2 where j1 and j2 are the two end nodes of edge j. • sort the remaining edges according to their ELP value, and select the edge of the lowest path loss, • placing it into the matching set. • add the two end nodes of the selected edge to the RMT set

  11. Results

  12. Simulation results: Interference

  13. Future works • Performance evaluation considering mobile movement • Inter-cluster handoff • Inter-cell handoff • Distributed heuristics • QoS guarantee • Traffic Scheduling • Admission control • Questions…

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