Packet Scheduling for Fairness and
Performance Improvement in
OFDMA Wireless Networks
Nararat RUANGCHAIJATUPON
and
Yusheng JI
The Graduate University for Advanced Studies
National Institute of Informatics (NII), Japan
The 26th Asia-Pacific Advanced Network Meeting
August 4–8, 2008, Queenstown, New Zealand
Presentation Outline







OFDMA
Scheduler and Resources
Utility Matrix & Proportional Fairness
Modified Simple Moving Average
Utility Matrix-based Scheduling
Simulation & Results
Conclusion
August 4-8, 2008
26th APAN Meeting
2
OFDMA
 Orthogonal Frequency Division
Multiple Access
 Reliability against fading channel
 Subchannelization (IEEE 802.16)
 Distributed subcarrier permutation
 Adjacent subcarrier permutation
 Adaptive Modulation Coding (AMC)
 Connectivity
August 4-8, 2008
26th APAN Meeting
3
System Model
- Centralized scheduler on BS
- Uniform power allocation to each subchannel
August 4-8, 2008
26th APAN Meeting
4
Resources
August 4-8, 2008
26th APAN Meeting
5
Utility Matrix & Proportional Fairness
im,n 
Rm,n (t )
Tn
August 4-8, 2008
Rm,n(t) – Achievable data rate of user n via
subchannel m
Tn – Average data rate
26th APAN Meeting
6
Modified Simple Moving Average
Wn (t )  U n (t  1)
Tn 
Vn (t  1)
Tn – Average data rate in PF utility function
U n (t )   Rm ,n (t  1),

m n ( t 1)

U n (t  1)   if q n (t  1)  0
 0,
 if q (t  1)  0
n

Un(t) – keep sum of total instantaneous
rates obtained by user n during the nonempty-queue period
Ωn(t) – the set of subchannels in which
user n is scheduled at frame t
Vn (t )  1, if qn (t  1)  0
Vn (t  1)  
 1, if qn (t  1)  0
Vn(t) – records the number of frame
while user n has data in the queue
Wn (t ), if qn (t  1)  0
Wn (t  1)  
 Tn , if qn (t  1)  0
Wn(t) – to retain the average data rate
when user n’s queue is empty
August 4-8, 2008
26th APAN Meeting
7
Utility Matrix-based Scheduling
 Find the maximum
PF element
 Allocate required
time slots
 Update average
rate (and PF
element)
 Delete (column/row)
from the utility
matrix
August 4-8, 2008
26th APAN Meeting
8
Example
 A system of 3 MSs and 3 subchannels
 MS1: Queue size 60 bits, average data rate 5
bps
 MS2: Queue size 100 bits, average data rate
6 bps
 MS3: Queue size 100 bits, average data rate
3 bps
 Each subchannel has 8 time slots
 Each time slot is 1 second
 A packet has 1 bit
August 4-8, 2008
26th APAN Meeting
9
Example
(cont.)
 A utility matrix
MS 1
Subchannel 1
Subchannel 2
Subchannel 3
August 4-8, 2008
10
 5
8
5
7
 5
26th APAN Meeting
MS 2
MS 3
7 
6
3
9
5 
6
3
5 10 
6
3
8
10
Example
(cont.)
MS1
60 bits
Avg rate: 5 bps
MS2
100 bits
Avg rate: 6 bps
0 bits
7.5 bps
10 88 7 7 
10
 55 66 6.53 
 88 99 5 5 
 7 55 5 66 106.53 
7
5
10
 55 66 6.53
MS3
100 bits
Avg rate: 3 bps
August 4-8, 2008
20 bits
6.5 bps
26th APAN Meeting
11
Example
(cont.)
MS1
60 bits
Avg rate: 5 bps
MS2
100 bits
Avg rate: 6 bps
0 bits
7.5 bps
10
 77..55
8
28 bits 
77..55

7.5 bps
 7 77..55
88
76.5
99
66.5
55
66.5
77 
66..55 
55 
66..55 
10 
10
66..5
MS3
100 bits
Avg rate: 3 bps
August 4-8, 2008
20 bits
6.5 bps
26th APAN Meeting
12
Simulation
Cell diameter
1 km
Number of MSs
48
Number of subcarriers/subchannel
48
Number of subchannels
4
Number of DL slots/subchannel
80
Frame duration
0.005 sec
User initial location
Uniformly distributed
User speed
Uniformly distributed [3,100] km/hr
Simulation time
20,000 frames
August 4-8, 2008
26th APAN Meeting
13
System Throughput
August 4-8, 2008
26th APAN Meeting
14
System Queue Size
August 4-8, 2008
26th APAN Meeting
15
Maximum Difference
 Maximum difference of
throughput per user
August 4-8, 2008
 Maximum difference of
queue size per user
26th APAN Meeting
16
Throughput Fairness Index
August 4-8, 2008
26th APAN Meeting
17
Computational Complexity
Scheduling scheme
Complexity
MaxC/I
O(M2N)
OFPF-MSMA
O(M2N2)
OFPF
O(M2N2)
PF
O(M2N3)
Max-min
O(M2N2)
August 4-8, 2008
26th APAN Meeting
18
Conclusion
 Centralized scheduler for OFDMA-TDD system
 To maximize system throughput and to provide
fairness with a consideration of queue status
 Utility function bases on proportional fairness
with modified simple moving averaging
 Utility matrix-based scheduling exploits multiuser multi-channel diversity with a
consideration of computational complexity
 Simulation results show improvement in
system throughput, queue length (queuing
delay), and fairness (throughput difference,
queue length difference
August 4-8, 2008
26th APAN Meeting
19
Thank you very much
 Questions and Answers