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Planning Base Station and Relay Station Locations in IEEE 802.16j Multi-hop Relay Networks

Planning Base Station and Relay Station Locations in IEEE 802.16j Multi-hop Relay Networks. Yang Yu, Seán Murphy, Liam Murphy Department of Computer Science and Informatics University College Dublin, Ireland IEEE CCNC 2008. Outline. Introduction Planning Model Problem Formulation

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Planning Base Station and Relay Station Locations in IEEE 802.16j Multi-hop Relay Networks

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  1. Planning Base Station and Relay Station Locations in IEEE 802.16j Multi-hop Relay Networks Yang Yu, Seán Murphy, Liam Murphy Department of Computer Science and Informatics University College Dublin, Ireland IEEE CCNC 2008

  2. Outline • Introduction • Planning Model • Problem Formulation • Simulation • Conclusion

  3. Introduction

  4. Introduction • Relays can be developed at significantly lower cost than Base Stations (BSs) • While 3G network planning has been well studied, the base radio technology on which it is based differs from that of 802.16

  5. Goal • To determine the optimal placement of BSs and Relay Stations (RSs) given the following : • a set of candidate sites • user demand • cost information

  6. Planning Model • The following inputs are assumed: • a set of candidate BS and RS sites • user demand, modelled by a set of discrete Test Points (TPs) • a suitable propagation model • a set of costs associated with BS and RS • the multihop concept is limited to nodes which are at most two hops from the BS • SSs can connect to an RS which is connected to the BS, or they can connect directly to the BS

  7. Problem Formulation _Definitions

  8. Problem Formulation _Definitions Propagation factor of the radio link between TP i and candidate site of BS j; Propagation factor of the radio link between TP i and candidate site of RS j; Propagation factor of the radio link between candidate site of RS i and candidate site of BS j

  9. Problem Formulation _ (1)

  10. Problem Formulation _ (2) TP to BS Cost of BS Cost of RS TP to RS RS to BS

  11. Problem Formulation _ (3)state space reduction • This problem can be solved by using the branch and bound algorithm • It’s still a NP-Hard Problem • So more constrains is to reduce the problem state space

  12. Problem Formulation _ (3)state space reduction

  13. Simulation_ parameter(1) • The size of area is 3km * 3km • The locations of each BSs, RSs and TPs is chosen randomly • BS cost is random

  14. 20 candidate BSs, 60 candidate RSs and 200 TPs 10 BSs are selected with 36 RSs

  15. Simulation_ (2) Calculation time when three parameters scaling in the mean time The numbers of BSs are varied The numbers of RSs are 3 times The numbers of TPs are 10 times

  16. Simulation_ (3) Calculation time when only the number of BS is scaling The numbers of BSs is scaling The numbers of RSs are 90 The numbers of TPs are 300

  17. Simulation_ (4) Calculation time when only the number of RS is scaling The numbers of BSs are 30 The numbers of RSs is scaling The numbers of TPs are 300 Number of RSs

  18. Simulation_ (5) Calculation time when only the number of TP is scaling The numbers of BSs are 30 The numbers of RSs are 90 The numbers of TPs is scaling Number of TPs

  19. Simulation_ (6) Comparison of the calculation time, with and without the additional constraints

  20. Conclusions • The proposed model is for planning 802.16-based relay networks • An integer programming formulation was developed • The results show that the standard branch and bound algorithm can find optimal solutions

  21. Thank you~

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