Adaptive Radio Resource Allocation in Hierarchical QoS Scheduling for IEEE 802.16 Systems

1. Adaptive Radio Resource Allocation in Hierarchical QoS Scheduling forIEEE 802.16 Systems Hua Wang and Lars Dittmann Department of Communications, Optics & Materials Technical University of Denmark, Lyngby, Denmark IEEE GLOBECOM2007 報告人：李宗穎

2. Outline • Introduction • Class Scheduler Design • Radio Resource Allocation in the Aggregate Scheduler • Simulation • Conclusion

3. Introduction • One level priority-based scheduling algorithms • the advantage of low implementation complexity • It is hard to well define a unified priority criterion in different traffic characteristics • Two-level hierarchical scheduler • In this paper, first estimates the required amount of bandwidths based on the backlogged traffic and the modulation efficiency

4. Two-Level Hierarchical Scheduler for IEEE 802.16

5. Class Scheduler Design - UGS • The time slots allocated for UGS connections are fixed, based on their constant bit-rate requirements negotiated in the initial service access phase

6. Class Scheduler Design – rtPS (1/3) • Paper apply the Exponential Rule algorithm to schedule rtPS connections • It was proposed to provide QoS guarantees over a shared wireless link in terms of the average packet delay, expressed as Wk is the head-of-line packet delay of the kth Tk,max is the maximum allowable delay δk is the maximum outage probability

7. Class Scheduler Design – rtPS (2/3) (1) (1) The FIFO and LWDF discipline, HOL packet spent the longest time at the Base Station (2) (2) The maximum rate rule schedulers the user whose channel can support the largest data rate (3) (3) It has been proven in [1] that this rule is throughput optimal, this rule tries to balance the weighted delays of packets and utilize the channels in a good manner [1] M. Andrew, K. Kumaran, K. Ramanan, A. L. Stolyar, R. Vijayakumar, P. Whiting, ”CDMA Data QoS Scheduling on the Forward Link with Variable Channel Conditions,” Bell Laboratories Tchnical Report, April, 2000.

8. Class Scheduler Design – rtPS (3/3) [2] [3] (δ1 >δ2-logδ2 < -logδ1 ) μk(t) is the instantaneous channel rate at time t [2] Sanjay S., and Alexander L.S. ,“Scheduling Algorithms for a Mixture of Real-Time and Non-Real-Time Data in HDR,” Proceedings of International Teletraffic Congress (ITC), 2001. (cited 234) [3] A. L. Stolyar and K. Ramanan, “Largest Weighted Delay First Scheduling: Large Deviations and Optimality,” Annals of Applied Probability, Vol. 11 (2001), No.1.

9. Class Scheduler Design – nrtPS (1/2) • The nrtPS service can tolerate longer delays, but requires a minimum throughput • M-LWDF algorithm is guarantee a minimum throughput rk,reqto user k, expressed as Pr(Rk < rk,req) ≤ δk

10. Class Scheduler Design – nrtPS (2/2) • each queue with a virtual token bucket. Tokens in each bucket k arrive at a constant rate rk,req • Wk(t) is the delay of the longest waiting token in token bucket k, calculated as Wk(t) = [Number of tokens in bucket k/rk,req]

11. Class Scheduler Design (BE) • Paper apply the Proportional Fair (PF) algorithm to schedule BE connections • At each scheduling time-slot, the PF algorithm selects user i with the highest priority value as follows:

12. Conventional Radio Resource Allocation Algorithms • Service classes following strict class priority, from highest to lowest: UGS, rtPS, nrtPS and BE • higher priority classes may starve the bandwidth for lower priority classes

13. Proposed Adaptive Resource Allocation Algorithm (i) the amount of backlogged traffic (ii) the satisfaction of QoS requirement (iii) the average spectral efficiency in term of modulation efficiency

14. Resource Allocation for UGS • the aggregate scheduler allocates a fixed amount of time slots NUGS = Σi∈{UGS} dito UGS class based on their constant-bit-rate requirements Nrest = Ntotal− NUGS

15. Resource Allocation for rtPS (1/2) • BrtPS(t)  backlogged traffic • μrtPS(t)  average modulation efficiency • α(t)  QoS-aware heuristic control parameter • the estimated number of time slots for rtPS class :

16. Resource Allocation for rtPS (2/2) • QoS-aware heurustic control parameter Pr(t) is the delay outage probability at time t This the outage threshold Dmax is the truncated maximum value of d(t) β is a shape factor which is used to tune the adaptation degree ξ is the maximum value of Δα(t)

17. Resource Allocation for nrtPS • the bandwidth estimation procedure is the same as rtPS class • Pr(t) in nrtPS is defined as the probability that the average throughput is less than the predefined minimum throughput within a certain time window

18. Resource Allocation for BE • For BE class, as there is no QoS guarantees, after serving UGS, rtPS, and nrtPS classes, the residual bandwidth is allocated to BE class

20. Simulation Model (OPNET) • β = 80, Th= 0.03, ξ = 0.05, Dmax = 0.1 • αmin(t)=0.1 αmax(t)=0.4 • If αmax(t)=0.4  rtPS : nrtPS : BE = 40% : 40% : 20%

21. Average packet delay in rtPS

22. Delay outage probability in rtPS

23. Average throughput in nrtPS

24. Throughput outage probability in nrtPS

25. Conclusion • In this paper, an adaptive resource allocation algorithm of the aggregate scheduler in two-level hierarchical QoS scheduling for IEEE 802.16 systems is proposed to increase the spectral efficiency while satisfying the diverse QoS requirements in each service class