1. QoS Aware AdaptiveQoS Aware Adaptive
Subcarrier AllocationSubcarrier Allocation
in OFDMA Systemsin OFDMA Systems
Mustafa Ergen & Sinem Coleri
{ergen,csinem}@eecs.berkeley.edu
University of California Berkeley

2. Introduction
 Motivation
 Orthogonal Frequency Division Multiple Access(OFDMA)
 OFDMA System
 Resource Allocation Problem
 Algorithms
 Optimal
 Suboptimal
 Simulation
 Conclusion

3. Motivation
 Broadband Wireless Access
Ex: IEEE 802.16, Wireless MAN
 OFDM
Eliminates InterSymbol Interference
 OFDMA

4. OFDM Diagram

5. Multiuser OFDM
 OFDM-TDMA
 OFDM-FDMA
 OFDMA
User 1
User 2
User 3
Subcarrier
Time
OFDM-TDMA
Subcarrier
Time
OFDM-FDMA
Subcarrier
Time
OFDMA
…
…

6. Resource Allocation
Goals:
 Dynamic subcarrier selection
 Improve system performance with adaptive
modulation
 More bits transmitted in large channel gain carriers
 Provide QoS
 Rate and BER

7. Resource Allocation
Assumptions:
 Base station knows
the channel
 Base station informs
the mobiles for
allocation
Base
Station
subcarrier
user

8. System
Application
Network
Resource Allocation
Physical Layer
rQoS=[rR,rBER] oQoS=[oR,oBER,oCoS]
oCoS=Ptotal for downlink
oCoS=Pu for uplink
[User x Subcarrier]

9. OFDMA

10. Resource Allocation
64-QAM
16-QAM
4-QAM
Channel
Subcarrier
User
RATE: [12 6 6 8 ]
BER: [1e-2 1e-2 1e-4 1e-4]
QoS
Resource Allocation

11. Notation
)12()
4
(
3
)(:
2
,
:
},...,1,0{
,
:
},...,1{:
},...,1{:
)(
:
2
1
2
,
,
,
−





=−
∈
∈
∈
=
− c
nk
nkkc
nk
BER
Q
No
cfQAMM
nk
gainchannel
M
nk
cbitassigned
Nnsubcarrier
Kkuser
cf
PPowerTransmit
α
α

12. Optimal
 Integer Programming
∑∑
∑∑
∑∑∑
= =
= =
= = =
≤≤
=
∈
K
k
M
c
cnk
cnk
N
n
M
c
nkk
cnkcnk
K
k
N
n
M
c nk
nk
nallforand
kallforcRtosubject
for
cf
cnk
1 1
,,
,,
1 1
,
,,,,
1 1 1
2
,
,
.,10
,.
}1,0{
)(
min
,,
γ
γ
γγ
αγ
Subcarrier
User
Subcarrier
User
Subcarrier
User
Subcarrier
Use
Pc2
Pc3
Pc1

13. Motivation for Sub-optimal
Algorithms
 IP is complex
 Allocation should be done within the
coherence time
 Time increases exponentially with the
number of constraints

14. Current Suboptimal Algorithms
2-step:
 Subcarrier Allocation
Assume the data rate for all subcarriers
Assume modulation rate is fixed
Assign the subcarriers
 Bit Loading
Greedy approach to assign the bits of user

15. Current Suboptimal Algorithms
 Subcarrier Allocation
 Hungarian algorithm
 Optimal, very complex
 LP approximation to IP
problem
 Close to optimal
 Bit Loading
Subcarrier
User
Subcarrier
User
Subcarrier
User).(
1
)(minarg
:,
,,
,,
,,
nknk
nknk
nknk
Sn
k
cPevaluate
cc
cPn
timesRfollowingtherepeatkeachFor
k
∆
+=
∆=
∈

16. Problems in Current Suboptimal
Algorithms
 Subcarrier assignment and bit loading are
separated
Users with bad channels may need higher
number of subcarriers
 Not iterative subcarrier assignment

17. Iterative Algorithm
Iterative algorithm based on
 Assignment of bits according to highest
modulation
 Finding the best places
 Distributing the assigned bits to other
subcarriers or to non-assigned subcarriers
 Exchanging the subcarriers among user
pairs for power reduction.

18. Iterative Algorithm
 Fair Selection(FS)
 Greedy Release(GR)
 Horizontal Swaping(HS)
 Vertical Swaping(VS)

19. Iterative Algorithm
FAIR
SELECTIONPtotal<Pmax
GREEDY
RELEASE
Start
Modulation--
HORIZONTALSWAP
VERTICALSWAP
ASSIGNMENT ITERATION

20. Simulation Environment
Build the OFDMA system
 Modulations:4-QAM,16-QAM,64-QAM
 Independent Rayleigh fading channel
to each user
 Number of subcarriers =128
 Nodes are perfectly synchronized

21. CDF of total transmit power
without Pmax constraint

22. CDF of total transmit power with
Pmax constraint

23. Average bit SNR vs. RMS delay
spread
As RMS delay spread increases, the fading variation increases
hence higher gains are obtained by adaptive allocation

24. Average bit SNR vs. number of
users
As the number of users increases, the probability of obtaining
good channel at a subcarrier increases

25. Instantaneous Average bit SNR
vs Time
Iterative Algorithm improves its Average Bit SNR by the time.

26. Conclusion
 OFDMA
 Broadband Wireless Access
 Resource Allocation
 Channel Information
 QoS Requirement
 Optimal Algorithms
 complex
 Iterative Algorithms