Decentralized Femtocell Transmission Regulation in Spectrum-Sharing Macro and Femto Networks

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. 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. Business opportunities New markets New user terminals New applications

5. Technical challenges • 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 Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2010–2015

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. 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. 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 differentinterfering 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. System Model rM • OFDMA downlink of collocated spectrum-sharing macrocell and closed-access femtocells • A central MBS covers a disc area with radius rM • Femtocells of radius rF are randomly distributed on R2as a spatial Poisson point process (SPPP) with a density ofF. • NF femtocells per cell site on average • UFindoor UEs per femtocell, each located on femtocell edge • MBS transmit power PM,Tx is evenly distributed among RBs • FAP transmit power PF,Tx is evenly distributed among RBs • Each FAP transmits with a probability  within an RB. • Spatial intensity of co-channel FAPs is uF = F. • Macro-to-macro interference and thermal noiseare ignored. Macro coverage circle Femto coverage circle MBS PM,Tx FAP rF PF,Tx MUE FUE R2

11. Channel Model Path loss follows the IMT-2000 channel model fc 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. Femtocell DL SIR • The received SIR ofan indoorFUE at the femtocell edge • PF = PF,TxGFAPGUE, PM = PM,TxGMBSGUE; • DFMis the distance from the MBS to the FUE, DFFi is the distance from interfering FAP i to the FUE; • HF, HFM and HFFi areunit-mean exponential channel power gains; • QF ~ LN(F, 2F2), QFM ~ LN(FM, 2FM2) and QFFi ~ LN(FF, 2FF2) denote lognormal shadowing, = 0.1ln10; •  is the set of FAPs having access to the given RB, with intensity uF. macro intef femto intef

13. Femto Outage Probability • Outage probability of an indoorFUEw.r.t. the target SIR F • For an indoor FUE at a distance dFM 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. Macrocell DL SIR • The received SIR ofan outdoor MUE is • DM is the distance from the MBS to the MUE, DMFi is the distance from FAP i to the MUE; • HM and HMFi denote unit-mean exponential channel power gains; • QM ~ LN(M, 2M2) and QMFi ~ LN(MF, 2MF2) denote lognormal shadowing. femto intef

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

16. rM MBS dFM,min FAP rF FUE Minimum MBS-to-FAP Distance • P(SIRF < F) ≤ F and P(SIRM < M) ≤ M, where0 ≤ F, M < 1 • P(SF/IFM < F|DFM = dFM) is a monotonically decreasing function of dFM. • Minimum dFM required for P(SIRF < F|DFM = dFM) ≤ F •  = HFQF/(HFMQFM) approximately follows a LN distribution • Any UE located less than dFM,min from the MBS should be associated with the macrocell.

17. FAP Transmit Power • Femtocells’ transmit power should be within the range [PF,Tx,min, PF,Tx,max] • PF,Tx,max is delimited by network standard. • PF,Tx,minis chosen as the minimum PF,Tx that makes an FUE at the macrocell edge meet Pr(SF/IFM<F|DFM= rM) ≤F. where is the inverse CDF of the LN RV  evaluated at F.

18. FAP Self-Regulation • FAP at a distance d (dFM,min ≤ d ≤ rM) from the MBS, • For an RB, if P(LB)F,Tx(d)  min{P(UB)F,Tx(d), PF,Tx,max}, then the FAP can transmit in the RB with PF,Tx set in the range [P(LB)F,Tx(d),min{P(UB)F,Tx(d), PF,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. Simulation Setup FAPs and MUEs are randomly dropped within the macrocell coverage, following two independent SPPPs.

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

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

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

24. Conclusions • OFDMA downlink ofcollocated 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 dependson 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. 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. Thank You ! Xiaoli Chu xiaoli.chu@kcl.ac.uk