Adaptive Interference Management of OFDMA Femtocells for Co-Channel Deployment

1. Adaptive Interference Management of OFDMA Femtocells for Co-Channel Deployment Instructor: 陳仁暉 Student: 連挺鈞 IEEE Journal on Selected Areas in Communications, Vol. 29, No. 6, June 2011 Y. Ji-Hoon and S. Kang

2. Outline • Purpose • Motivation • Problem Definition • Requirement of Femto Management • Related Work • Contribution • System Model • CTRL Architecture • Numerical Results • Multi-Cell Simulation • Conclusion

3. Purpose • Femtocell • Co-channel deployment of femto and macro-cells combined with orthogonal frequency-division multiple access (OFDMA) to decrease uplink interference. • Advantage of femtocell • Cost-effective • By including femtocell into the system, femto cells and subscribers both benefits: • Better service coverage and higher indoor data throughput • Macrocell offloading and indoor coverage improvement

4. Motivation • Implement an architecture for maximum transmit power of femtocell users based on fed-back macrocell load margin for protection of macrocell uplink communication • Target signal to interference plus noise ratios (SINRs) of femtocell to reach a Nash equilibrium • Instantaneous transmit power of femtocell users to achieve target SINRs against bursty interference from other nearby users. • This implementation is called Complementary Tri-control Loops (CTRL)

5. Problem Definition • Degradation of both macrocell and femtocells users in uplink (UL) communications is a serious problem

6. Problem Definition • Types of interference • Femtocells reside close to macro BS • Macrocell users resides in vicinity of a femto BS • Users of femto BS using stronger transmit power to maintain receive SINR • Femtocell’s UL in neighboring femtocells. • Femto management objective • Protection of macrocell’s UL against femtocell interference • Efficient resource-usage coordination among femtocells • Protection of femtocell’s UL against bursty interference

7. Requirement of Femto Management • No change to macrocell radio resource management (RRM) • RRM may affect already-stabilized macrocell user services and trigger tedious, costly optimization processes, and service disruption • Distributed and self-organizing operation • Using least amount of global information • Support of legacy user device • Market penetration • No special hardware • Maintain femto BS’s cost-efficiency purpose

8. Related Work • Chandrasekhar et al. [6] • Game theory approach • Changes RRM • Jo et al. [7] • No RRM changes, but only protect macrocell and no convergence analysis • Yavuz et al. [4] • Power reduced too much  increase power • D. Lopez et al. [11] • Co-channel deployment • Resource split between macro and femto-cells

9. Contribution • Distributed and self-organizing femtocell management architecture(CTRL) • Maximum transmit power control loop (MTXPC) • Fed-back macrocell UL load margin to protection of macrocell • Target SINR control loop (TSINRC) • Utility-optimal resource coordination among femto-cells w/o signaling them • Instantaneous transmit power control loop (ITXPC) • Control transmit power of a femtocell user • Advantage • No modification of RRM (seamless network) • Adapt to environment change and no hardware acquired • Compatible with legacy user devices

10. System Model (Network Architecture) • Macro-cells • M = {1, …, M} • Femto-cells • F = { 1, …, F} • Femto-cells users • fi: ith user index; f: femto-cell index • : cardinality of set • Indexing rule • where

11. System Model (Macrocell Load Feedback) • Feedback current status of macro-cells • Cell load margin: Difference between current cell load and load threshold • Positive when current load is lower than threshold • Feedback over wired Network • Two ways of implement • Direct signaling interface between macro and femto-cells • Using existing signaling interference and an operation, administration and management (OAM) server • First method requires costly standardization • Second method is easier, but incurs larger delay (Delay of internet)

12. System Model (Macrocell Load Feedback) • Feedback over the air • Macro BSs broadcast load margin information • Two issues: • Implementation feasibility and standard violation • FDD: Femto BSs need to overhear macrocell signals at a frequency other than their original receiving frequency • TDD: Need to enable full duplex (tx and rx at same time) • Using same frequency, femto BSs may not be able to demodulate • Macrocell’s feedback at a frequency other than femtocell’s transmission frequency (Solved by multiple frequency bands) • Interference cancelation as in wireless relay

13. CTRL Architecture (Overview) • MTXPC Loop • In charge of protecting macrocell’s UL by controlling maximum transmit power of femtocell users based on fed-back macrocell load margin • Contained in each resource block • Positive: Macrocell has room • Negative: Overloaded cell • Max. transmit power: inner-macrocell user traffic, other macrocells’ interference and femtocell interference

14. CTRL Architecture (Overview) • TSINRCLoop • Enables efficient resource coordination among neighboring femtocells based on local information • Femto BSs need to infer current situation based on implicit feedback • ITXPC Loop • Interference of nearby macrocell users or other femtocell users • Controls instantaneous transmit power of femtocell user

15. CTRL Architecture (Problem Formulation) • MTXPC loop • (L: Load) • TSINRC loop • p: power allocation vector • b: allocation indicator of user I • γ: corresponding SINR vectors • ITXPC loop

16. Numerical Results • MTXPC configuration • Q: Global femtocell status composed of other activity factors, channel gain and user-specific constants of other femto cells • d: feedback delay • Ith(0) = 1 and IM(50) = 0.5 • Q = 1 and d = 0 • Kp: constants to cal. proportional integral controller

17. Numerical Results

18. Multi-Cell Simulation • Static user transmission • Dynamic user transmission • Power on/off of users

19. Multi-Cell Simulation

20. Multi-Cell Simulation

21. Conclusion • Advantage • Provide several mathematic induction and simulation result • Provide proof of these mathematical thesis • Implementation seems impeccable • Disadvantage • Equations are not well organized

22. Additional Information • Cognitive radio: • 在無線網路中,以訊號減少干擾下做傳輸或接受的轉換。 • Seamless: 不受干擾。 • Nash equilibrium: • Gametheory中，使得每個玩家都有平等的策略。 • Z-transform: • 以離散的訊號轉換為以頻率切割的表示法。 • Gaussian function • 在無線網路中，可以以高斯定律來模擬femto基地台、使用者，或是封包傳輸以一平均分佈表示公式。 • Markov chain: 以數學機率模型來表示型態轉換。