1. Decentralized Femtocell Transmission Regulation in Spectrum-Sharing Macro and Femto Networks Xiaoli Chu King’s College London, UK OPTNet 2011, Sheffield, 14 September 2011

2. - 2 - Outline Introduction Collocated spectrum-sharing macro and femto cells ▫ Motivation ▫ Contribution ▫ System model ▫ Outage probability analysis ▫ Femtocell location and transmit power Simulation results ▫ Analytical results verified by simulations Conclusion

3. Introduction

4. - 4 - Business opportunities New user terminals New applications New markets

5. - 5 - Technical challenges Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2010–2015 Current 2G and 3G networks will not be able to meet future mobile data traffic demands Most of the data traffic is performed indoors, where coverage is the worst As a result, vendors and operators are desperately looking for new solutions

6. - 6 - Solutions: Femtocells Femtocells are low-power wireless access points (FAPs) that operate in licensed spectrum to connect standard mobile devices to a mobile operator’s network using residential DSL or cable broadband connections [Source: Femto Forum]. ▫ Improve indoor coverage ▫ Unload traffic from overburdened macrocells ▫ Likely to be user-deployed

7. Collocated Spectrum-Sharing Macro and Femto Cells

8. - 8 - Motivation Spectrum-sharing macro and femto cells ▫ Benefits  Spectrum-sharing allows for increased spectral efficiency and better spatial reuse ▫ Challenges  Spectrum-sharing suffers from inter-cell interference and creates dead spots where UE QoS cannot be guaranteed.

9. - 9 - Contribution Analysis of downlink (DL) outage probabilities (OPs) ▫ Closed-form macro and femto DL OP lower bounds embracing the randomness of transmit power employed by different interfering FAPs. Analysis includes both Rayleigh flat fading and shadowing ▫ Our work accounts for path loss, Rayleigh fading, lognormal (LN) shadowing, and LN interfering FAP power, and allows different DL (SIR) targets and OP constraints for macro and femto cells. Decentralized resource allocation ▫ Decentralized strategy to regulate FAP’s transmit power and usage of radio resources to guarantee a satisfactory macro and femto DL coverage.

10. - 10 - OFDMA downlink of collocated spectrum-sharing macrocell and closed-access femtocells ▫ A central MBS covers a disc area with radius r M ▫ Femtocells of radius r F are randomly distributed on R 2 as a spatial Poisson point process (SPPP) with a density of F. ▫ N F femtocells per cell site on average ▫ U F indoor UEs per femtocell, each located on femtocell edge ▫ MBS transmit power P M,Tx is evenly distributed among RBs ▫ FAP transmit power P F,Tx is evenly distributed among RBs ▫ Each FAP transmits with a probability  within an RB. ▫ Spatial intensity of co-channel FAPs is u F = F . ▫ Macro-to-macro interference and thermal noise are ignored. System Model MBS rMrM MUE Femto coverage circle Macro coverage circle FAP rFrF FUE R2R2 P M,Tx P F,Tx

11. - 11 - Channel Model Path loss follows the IMT-2000 channel model f c is the carrier frequency in MHz, d is the distance of the link, and  denotes the wall-penetration loss. Each frequency subchannel sees Rayleigh flat fading and lognormal shadowing

12. - 12 - Femtocell DL SIR The received SIR of an indoor FUE at the femtocell edge ▫ P F = P F,Tx G FAP G UE, P M = P M,Tx G MBS G UE ; ▫ D FM is the distance from the MBS to the FUE, D FFi is the distance from interfering FAP i to the FUE; ▫ H F, H FM and H FFi are unit-mean exponential channel power gains; ▫ Q F ~ LN(  F,  2  F 2 ), Q FM ~ LN(  FM,  2  FM 2 ) and Q FFi ~ LN(  FF,  2  FF 2 ) denote lognormal shadowing,  = 0.1ln10; ▫  is the set of FAPs having access to the given RB, with intensity u F. macro intef femto intef

13. - 13 - Femto Outage Probability Outage probability of an indoor FUE w.r.t. the target SIR  F For an indoor FUE at a distance d FM from the MBS Based on the stochastic geometry theory Prob of macro-to-femto interf. being strong enough to create outage Prob of femto-to-femto and macro-to-femto interf. causing outage

14. - 14 - Macrocell DL SIR The received SIR of an outdoor MUE is ▫ D M is the distance from the MBS to the MUE, D MFi is the distance from FAP i to the MUE; ▫ H M and H MFi denote unit-mean exponential channel power gains; ▫ Q M ~ LN(  M,  2  M 2 ) and Q MFi ~ LN(  MF,  2  MF 2 ) denote lognormal shadowing. femto intef

15. - 15 - Macro Outage Probability Outage probability of an MUE w.r.t. the target SIR  M For an MUE at a distance d M from the MBS Based on the stochastic geometry theory

16. - 16 - Minimum MBS-to-FAP Distance P(SIR F <  F ) ≤  F and P(SIR M <  M ) ≤  M, where 0 ≤  F,  M < 1 P(S F /I FM <  F |D FM = d FM ) is a monotonically decreasing function of d FM. Minimum d FM required for P(SIR F <  F |D FM = d FM ) ≤  F ▫ = H F Q F /(H FM Q FM ) approximately follows a LN distribution Any UE located less than d FM,min from the MBS should be associated with the macrocell. MBS FAP rFrF FUE d FM,min rMrM

17. - 17 - FAP Transmit Power Femtocells’ transmit power should be within the range [P F,Tx,min, P F,Tx,max ] P F,Tx,max is delimited by network standard. P F,Tx,min is chosen as the minimum P F,Tx that makes an FUE at the macrocell edge meet Pr(S F /I FM <  F |D FM = r M ) ≤  F. where is the inverse CDF of the LN RV evaluated at  F.

18. - 18 - FAP Self-Regulation FAP at a distance d ( d FM,min ≤ d ≤ r M ) from the MBS, ▫ For an RB, if P (LB) F,Tx (d)  min{P (UB) F,Tx (d), P F,Tx,max }, then the FAP can transmit in the RB with P F,Tx set in the range [P (LB) F,Tx (d), min{P (UB) F,Tx (d), P F,Tx,max }] for simultaneously meeting both the macro and femto DL OP constraints; ▫ otherwise, the FAP can only transmit in the RB with P (LB) F,Tx (d) and at a reduced probability .

19. Simulations and Results

20. - 20 - Simulation Setup FAPs and MUEs are randomly dropped within the macrocell coverage, following two independent SPPPs. ParametersValuesParametersValues  10 dB, 15 dBP M,Tx 43 dBm  M,  FM 4P F,Tx  23 dBm FF 3G MBS 15 dBi  FF,  MF 3.5G FAP 2 dBi MM 8 dBG UE 0 dBi FF 4 dBrMrM 1000 m  FF 12 dBrFrF 30 m  MF,  FM 10 dBUFUF 2 fcfc 2000 MHz MM 5 dB  M,  F 0.1 FF 10 dB

21. - 21 - Outage Probability DL OP vs. the distance from the MBS, for N F = 30 and 100,  = 10 dB.

22. - 22 - Simulated DL OP vs. the distance from the MBS, when the femtocell regulation strategy is employed at each FAP. Performance of Femto Self Reg

23. - 23 - Femto Self Reg FAP transmit power and  vs. the distance from the MBS, when using the proposed femtocell regulation strategy.

24. - 24 - Conclusions OFDMA downlink of collocated spectrum-sharing macrocell and closed-access femtocells ▫ Closed-form analytical expressions for outage probabilities ▫ Analytical expression of minimum MBS-to-FAP distance ▫ Simulation results have verified the accuracy of analytical results. Interference caused by femtocells has to be limited by ▫ regulating femtocell transmit power, which depends on the distance from the MBS; or ▫ restricting the probability of each femtocell transmitting in each RB, which can be controlled in both frequency and time domains.

25. - 25 - Further Information This research has been supported by the UK EPSRC Grants EP/H020268/1, CASE/CNA/07/106, and the RCUK UK- China Science Bridges Project (EP/G042713/1): R&D on (B)4G Wireless Mobile Communications. Related publications and submissions: ▫ X. Chu, Y. Wu, D. López-Pérez and H. Wang, “Decentralized femtocell transmission regulation in spectrum-sharing macro and femto networks,” IEEE VTC 2011-Fall, San Francisco, USA, Sep 2011. ▫ X. Chu, Y. Wu and H. Wang, “Outage probability analysis for collocated spectrum- sharing macrocell and femtocells,” IEEE ICC 2011, Kyoto, Japan, Jun 2011. ▫ X. Chu, Y. Wu, L. Benmesbah and W. K. Ling, “Resource allocation in hybrid macro/femto networks,” IEEE WCNC 2010 WS, Sydney, Australia, Apr 2010. ▫ X. Chu, Y. Wu, D. López-Pérez and X. Tao, “On providing downlink services in collocated spectrum-sharing macro and femto networks,” IEEE Trans. Wireless Commun., under review.

26. - 26 - Thank You ! Xiaoli Chu xiaoli.chu@kcl.ac.uk