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Cell Zooming for Cost-Efficient Green Cellular Networks

Cell Zooming for Cost-Efficient Green Cellular Networks. IEEE Communications Magazine • November 2010. 2012. 2. 21 Jae-Hun Lee. Contents. Introduction Implementation Algorithm Performance Evaluation Conclusion. Introduction. Cell Zooming zooming in zooming out

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Cell Zooming for Cost-Efficient Green Cellular Networks

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  1. Cell Zooming for Cost-Efficient Green Cellular Networks IEEE Communications Magazine • November 2010 2012. 2. 21 Jae-Hun Lee

  2. Contents • Introduction • Implementation • Algorithm • Performance Evaluation • Conclusion

  3. Introduction • Cell Zooming • zooming in • zooming out • adaptively adjusts the cell size according to traffic conditions

  4. Framework of cell zooming

  5. Implementation • Techniques • Physical Adjustment • - adjusting by antenna height and antenna tilt • BS Cooperation • - form a cluster as a new cell from MUs’ perspective • - the sum of the original cell size of BSs • - reduce ICI(Inter Cell Interference) • Relaying • - improve the performance of cell-edge MUs • BS sleeping • - largely reduce the energy consumption of cellular network • - if the cell zooms in to 0, its neighbor cells will zoom out to guarantee • the coverage

  6. Implementation

  7. Implementation • Benefits • load balancing by transferring traffic • energy saving • Challenges • traffic load fluctuations should be exactly traced & fed back to the CS • compatibility • - additional mechanical equipments • - special control channels for feeding back the network information • ICI and coverage holes

  8. Algorithm • 3 stages • coordination stage • transition stage • serving stage • energy consumption depends on the work mode of cells

  9. Algorithm • To minimize the number of active BSs, • Centralized algorithm • - all the channel conditions and user requirements in the network • are collected by the CS • - resource allocation and cell zooming operations are performed in • a centralized way • Distributed algorithm • - each MU will select the BS to be associated with by itself based • on the information provided broadcasted by the BSs • Centralized algorithm requires more signaling overhead, but can • achieve better performance compared with the distributed one.

  10. Centralized algorithm • Step 1: Initialize all the to be 0, and all the elements in matrix X • to be 0. • Step 2: Find the set of BSs without violating the bandwidth constraints • which means . • Step 3: All the BSs with the ratio 0 will zoom in to zero and work in sleep • mode in the next serving period.

  11. Distributed algorithm • Step 1: Initialize all the to be 0, and all the elements in matrix X • to be 0. • Step 2: Find the set of BSs without violating the bandwidth constraints • which means . • Step 3: Repeat Step 2 until there is no undate of X and end the procedure • no coordination among BSs is needed, therefore much signaling overhead • is reduced

  12. Simulation Environment • 10 by 10 hexagon cells • Cell radius : 200m] • assume each BS can extend its coverage to at most 400m • Power Consumption 400W for BS in active mode, and 10W in sleep mode • Bandwidth of BS : 5MHz • Average sojourn time : 1 minute • Rate requirement of each MU : 122kbps • Cell zooming period T : 1 hour • All the simulation results are averaged over 100 cell zooming periods.

  13. Simulation Environment

  14. Simulation Results

  15. Conclusion • Solve the traffic imbalance • Reduce the energy consumption • Need a trade-off between energy saving and blocking • probability

  16. Thank you for attention!

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