1. UMTS Radio Network Planning Andreas Eisenblätter Thorsten Koch (ZIB) Alexander Martin (TU Darmstadt)

2. Overview UMTS Network Planning Optimisation model Integrated planning Computational results Conclusions Cooperation:EU-Project MOMENTUM Operators:KPN, E-Plus, Vodafone Portugal Vendor:Siemens Mobile R&D:Atesio, TU Darmstadt, TU Lisbon, ZIB

3. UMTS Network Planning Scenario Downtown Berlin Network 16 potential sites  3 antennas per site © Digital Building Model Berlin (2002), E-Plus Mobilfunk GmbH & Co. KG, Germany

4. UMTS Network Planning Scenario Downtown Berlin Network 16 potential sites  3 antennas per site Demand/ Traffic voice telephony video telephony file download streaming multimedia

5. UMTS Network Planning Scenario Downtown Berlin Network 16 potential sites  3 antennas per site Demand/ Traffic voice telephony video telephony file download streaming multimedia

6. UMTS Network Planning Scenario Downtown Berlin Network 16 potential sites  3 antennas per site Demand/ Traffic voice telephony video telephony file download streaming multimedia

7. Network Planning Decisions Decisions sectorization antenna height antenna tilt / azimuth antenna type carrier RRM parameters pilot power Which sites to use?

8. UMTS – Universal Mobile Telecommunication Network W-CDMA Multi-service voice user video telephony user

9. UMTS – Universal Mobile Telecommunication Network W-CDMA Multi-service CIR-target Self interference interference C I  R R voice user video telephony user

10. W-CDMA Multi service CIR-target Self interference Network quality interference C I  R R other cell interference W-CDMA Multi-service CIR-target voice user video telephony user UMTS – Universal Mobile Telecommunication Network

11. Modeling: Sets and Parameters interference C I  R R other cell int.

12. Modeling: Variables interference C I  R R other cell int.

13. Modeling: Coverage Constraints interference C I  R R other cell int.

14. Modeling: Uplink Constraints interference C I  R R other cell int.

15. Modeling: Downlink Constraints I interference C I  R R other cell int.

16. Modeling: Downlink Constraints II interference C I  R R other cell int. ^

17. Modeling: Linearized Downlink CIR-Constraints interference C I  R R other cell int.

18. Sites site & equipment costs configuration Traffic multiple profiles multi-service stochastic input active users spatial distribution Serving mobiles uplink (UL) dedicated channels (CIR) downlink (DL) dedicated channels (CIR) pilot channel (E c /I 0 -based) MIP Model Scope & Structure sites installations pilot powers mobile assignment UL power DL power traffic snapshot

19. assignment UL power DL power Sites site & equipment costs configuration Traffic multiple profiles multi-service stochastic input active users spatial distribution Serving mobiles uplink (UL) dedicated channels (CIR) downlink (DL) dedicated channels (CIR) pilot channel (E c /I 0 -based CIR) sites installations pilot powers assignment UL power DL power... traffic snapshot MIP Model Scope & Structure

20. multi- snapshot optimiser (MIP) installation snapshot Integrated Optimization processor generatorfitter configuration rating static / dynamic simulations - external assessment OK? installation mapping generator no yes attenuation

21. multi- snapshot optimiser (MIP) installation snapshot Solving the MIP processor generatorfitter generator using ZIMPL to generate MIP (http://www.zib.de/koch/zimpl) solving MIP using CPLEX with tuned settings explicit generation MIR cuts (simple algebraic structure) numerical challenge: dynamic range of input constraint scaling & reformulation using few snapshots at a time careful pre-selection of initial installations size O(I x M)

22. First Computational Results Scenario Downtown Berlin Network 16 potential sites  3 antennas per site Demand/ Traffic voice telephony video telephony file download streaming multimedia MIP reduced: 20857 rows, 5670 columns, 79476 nze CPLEX root LP: 8.21 sec. heuristics, few BB nodes

23. First Computational Results Scenario Downtown Berlin Network 16 potential sites  3 antennas per site Demand/ Traffic voice telephony video telephony file download streaming multimedia MIP reduced: 20857 rows, 5670 columns, 79476 nze CPLEX root LP 8.21 sec. heuristics, few BB nodes © Path loss predictions by E-Plus Mobilfunk GmbH & Co. KG, Germany

24. Conclusions Locations Pilot Power SectorisationAntenna type Height TiltCarrier Fairly accurate MIP for UMTS Radio Network Planning Large realistic data sets, huge effort to collect  public benchmarks First computational results on small, realistic scenarios Lacking theoretical underpinning Getting to the practitioners (soon) http://momentum.zib.de Proc. 6 th Informs Telcom. Conference Conclusions