Distributed Power Allocation for Inter-cell Interference Management in Multi-cell OFDMA Systems

1. Distributed Power Allocation for Inter-cell Interference Management in Multi-cell OFDMA Systems Soomin Ko, Hanbyul Seo, Hojoong Kwon, and Byeong Gi Lee Seoul National University Korea

2. Goal • Multi cell, multi channel downlink system • Improves the throughput-fairness trade-off without inter-BS coordination • Each cell controls inter-cell interference • Each cell allocates transmission power to channels in a distributive manner • Distributed Inter-cell Power Allocation (DIPA)

3. Observation • Fast fading channel • Difficult to allocate power according to short-term channel condition • DIPA: first concept • Allocate power according to long-term channel condition • Users’ preference on the channels • Each user has different preferences (in the sense of long-term channel condition) • Since each user experiences different Pathloss and Shadowing • DIPA: second concept • Determine the power allocation preferred by each user • Incorporate the individual power allocations into one policy

4. Main concept I: Frame, Super-frame • Frame, Super-frame • Super-frame • Power allocation operates in a large time scale • Using average interference during the previous super-frame • Frame • User scheduling operates in a small time scale

5. Main concept II: Incorporating individual preferences • 2 incorporating strategies • Selection and Concentration • Universal sharing • Ex) In the case of 4 channels, 2 users • User A: prefers (P/2,P/2,0,0) ,User B: prefers (0,0,P/2,P/2) • Selection and concentration • (P/2, 0,P/2,0) • High reuse factor • Suitable for high-interference-users (HIU) • Universal sharing • (P/4,P/4,P/4,P/4) • Low reuse factor • Suitable for low-interference-users (LIU)

6. Flow of DIPA • Super-frame • User: Channel preference feedback • BS: Power allocation based on the feedback • Step 1: Reflects preference of HIU • Uses Selection and Concentration • Step 2: Reflects preference of LIU • Uses Universal sharing • Frame • User: SINR feedback • BS: Scheduling based on the feedback

7. Flow of DIPA

8. Operation of DIPA : Users • Super-frame • Measure average interference • Set vm,k =1 if average interference of channel m < T • Set user k = HIU if the number of channels with vm,k =1 M/R • Each HIU selects M/R channels where the average interference are lowest and sets vm,k = 1 for the channels • Feedback vm,k • vm,k : preference indicator, T: Threshold • M: number of channels,R: parameter

9. Operation of DIPA : BS • Power allocation : Step 1 + Step 2 • Step 1 : Adopt Selection and Concentration • m* : channel preferred by the largest number of HIUs • Set pm* = min(PtR/M, Pr) • Update fk = fk + vm,k /jHIUvm,j • Update Pr = Pr - pm* • Exclude user k from the later power allocation if fk M/(RK) • Exclude channel m* from the later power allocation • Repeat the above operation as long as Pr is positive and at least one high-interference user remains • Pr : remaining power, fk : satisfaction indicator • K : number of users

10. Operation of DIPA : BS • Step 2 : Adopt Universal sharing • For each LIU, set qm,k = Pr vm,k /  m vm,k 1(pm=0) • For each channel m with pm = 0, set pm = kLIUqm,k / KLIU • qm,k : dummy variable, KLIU : number of LIUs • 1(): indicator function • User scheduling • After the power allocation in the current super-frame is finished • BS determines user scheduling in each frame based on the instantaneous channel condition and given power allocation • DIPA can be combined with any opportunistic scheduler

11. Example • In the case of M=6, K=4, Pt=6, T=1, R=3 • Interference • Preference indicator, vm,k HIU

12. Example • Step 1 • m* = 2 • pm* = min(PtR/M, Pr) = 3 • f1 = 1/2, f2 = 1/2, Step 1 completed (since f1, f2 M/(RK)=1/2) • Step 2 qm,k Power allocation result

13. Simulation result • Trade-off between throughput and fairness • DIPA efficiently trade off the throughput and the fairness

14. Summary • DIPA • Distributed operation • Without inter-BS coordination • Efficient trade off between throughput andfairness • Can improve both thethroughput and the fairness compared with static FFR