Adaptive Radio Resource Allocation in
Hierarchical QoS Scheduling for
IEEE 802.16 Systems
Hua Wang and Lars Dittmann
Department of Communications, Optics & Materials
Technical University of Denmark, Lyngby, Denmark
IEEE GLOBECOM 2007
報告人：李宗穎
Outline
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Introduction
Class Scheduler Design
Radio Resource Allocation in the
Aggregate Scheduler
Simulation
Conclusion
2
Introduction
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One level priority-based scheduling algorithms
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the advantage of low implementation complexity
It is hard to well define a unified priority criterion
in different traffic characteristics
Two-level hierarchical scheduler
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In this paper, first estimates the required amount of
bandwidths based on the backlogged traffic and the
modulation efficiency
3
Two-Level Hierarchical
Scheduler for IEEE 802.16
4
Class Scheduler Design - UGS
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The time slots allocated for UGS
connections are fixed, based on their
constant bit-rate requirements negotiated in
the initial service access phase
5
Class Scheduler Design – rtPS (1/3)
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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
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Class Scheduler Design – rtPS (2/3)
j  arg max Wk (t )
k
(1)
(1) The FIFO and LWDF discipline, HOL packet spent the longest time at the
Base Station
j  arg max uk (t )
(2)
k
(2) The maximum rate rule schedulers the user whose channel can support
the largest data rate
j  arg max rk uk (t )Wk (t ) (3)
k
(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.
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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 NonReal-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.
8
Class Scheduler Design – nrtPS (1/2)
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The nrtPS service can tolerate longer
delays, but requires a minimum throughput
M-LWDF algorithm is guarantee a
minimum throughput rk,req to user k,
expressed as Pr(Rk < rk,req) ≤ δk
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Class Scheduler Design – nrtPS (2/2)
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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]
i  arg max rk uk (t )Wk (t )
k
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Class Scheduler Design (BE)
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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:
 uk (t ) 
i  arg max 

k
 uk 
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Conventional Radio Resource
Allocation Algorithms
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Service classes following strict class priority,
from highest to lowest: UGS, rtPS, nrtPS and
BE
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higher priority classes may starve the bandwidth
for lower priority classes
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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
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Resource Allocation for UGS
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the aggregate scheduler allocates a fixed
amount of time slots NUGS = Σi∈{UGS} di to
UGS class based on their constant-bit-rate
requirements
Nrest = Ntotal − NUGS
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Resource Allocation for rtPS
(1/2)
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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 :
15
Resource Allocation for rtPS (2/2)
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QoS-aware heurustic control parameter
Pr(t) is the delay outage probability at time t
Th is 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)
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Resource Allocation for nrtPS
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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
17
Resource Allocation for BE
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For BE class, as there is no QoS guarantees,
after serving UGS, rtPS, and nrtPS classes,
the residual bandwidth is allocated to BE
class
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Simulation Model (OPNET)
rtPS
nrtPS
Traffic
VoIP and video
Internet traffic
QoS parameter
Packet delay < 100ms
outage probability < 5%
Throughput ≥ 100 Kbits/sec
outage probability < 5%
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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%
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Average packet delay in rtPS
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Delay outage probability in rtPS
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Average throughput in nrtPS
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Throughput outage probability in
nrtPS
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Conclusion
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In this paper, an adaptive resource allocation
algorithm of the aggregate scheduler in twolevel 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
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