Transcript Performance Evaluation of Adaptive sub-carrier Allocation Scheme for OFDMA

HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Performance evaluation of adaptive
sub-carrier allocation scheme for
OFDMA
Thesis presentation
16th Jan 2007
Author: Li Xiao
Supervisor: Professor Riku Jäntti
Instructor: Lic.Sc Boris Makarevitch
Place: Communications Laboratory
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Agenda
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Introduction
Overview of OFDM
OFDM based multiple access schemes
Adaptive sub-carrier allocation algorithm
Simulation
Conclusions
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Introduction
Background
 Multi-carrier transmission methods attract much focus to support high
speed and reliable wireless communications
 A good OFDMA sub-carrier allocation scheme should use spectral as
efficiently as possible and achieve minimum cost of service based upon
user’s QoS requirement
Objectives
 Transmission power minimization as cost of service in Downlink and
Uplink
 Performance evaluation of adaptive sub-carrier allocation for OFDMA
Methodology
 Adaptive OFDMA sub-carrier allocation algorithm implementation in
Matlab
 Performance comparison among adaptive OFDMA sub-carrier allocation
scheme and other static schemes
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
OFDM
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Dividing the total bandwidth into a number of sub-carriers
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OFDM realization
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Intersymbol interference
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Intercarrier interference
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Cyclic prefix
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OFDM Based Multiple Access Schemes
Advantage
Disadvantage
OFDM-TDMA
Easiest
implementation
Simple resource allocation
No intra-cell MAI
Low processing requirement
Power saving
Low signaling overhead
High
OFDM-CDMA
Spectral
efficiency
Frequency diversity
MAI and inter-cell interference resistance
Highest flexibility
Simple resource allocation
Low signaling overhead
Implementation
OFDMA
Simple
Inter-cell interference
implementation
Resource allocation flexibility
Adaptation to channel characteristics
(adaptive scheme)
Better BER performance (adaptive scheme)
latency
Lowest flexibility
High peak to average power ratio
complexity
Requirement of power control
Only coherent modulation possible
Intra-cell interference
High peak to average power ratio
Low
spectral efficiency
High peak to average power ratio
Signaling overhead (adaptive
scheme)
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
OFDMA
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Each user transmits on a certain number of OFDM sub-carriers during all
time slots
Static sub-carriers assignment and dynamic sub-carriers assignment
Multirate system
Multiuser diversity
Adaptive modulation (bit rate, transmission power, channel coding rate or
scheme)
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Mobile WiMAX
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Extension of WiMAX for fixed
access
Scalable OFDMA
High data rate
Quality of Service
Scalability
Security
Mobility
Parameters
Values
System Channel Bandwidth
(MHz)
1.25
5
10
20
Sampling Frequency (MHz)
1.4
5.6
11.2
22.4
FFT Size
128
512
1024
2048
Number of Sub-Channels
2
8
16
32
Sub-Carrier Frequency
Spacing
10.94kHz
Useful Symbol Time (Tb =
1/f)
91.4 us
Guard Time (Tg = Tb/8)
11.4 us
OFDMA symbol Duration (Ts
= Tb+Tg)
102.9 us
Number of OFDMA Symbols
in 5ms Frame
48
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Adaptive sub-carrier allocation algorithm
Adaptive means
 Number of sub-carriers each user needs is adaptive
 Sub-carriers allocation among users is adaptive
 Bit loading to sub-carriers is adaptive
 Adaptive modulation scheme for each sub-carrier
Users’ QoS requirement
 Minimum Reserved Rate
 Bit Error Rate
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Downlink system structure of OFDMA
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BS has the perfect knowledge
of instantaneous channel
information for all users
Bandwidth of each sub-carrier
is smaller than channel
coherence bandwidth
Each sub-carrier can only be
occupied by one user
No free sub-carrier left
f1
User 1
f2
User 2
.
.
.
User K
Sub-carrier
allocation and
bit loading
.
.
.
IFFT
.
.
.
P/S
Add
cyclic
prefix
fN
BS transmitter
Sub-carrier power
based allocation
algorithm
User k
Sub-carrier
selector and
P/S
Channel state
information
.
.
.
FFT
.
.
.
S/P
Remove
cyclic
prefix
Receiver of user k
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Adaptive sub-carrier allocation algorithm
Objective function
 Transmission power minimization
 Downlink: Minimize the interference from BS in question to the MSs
in other cells
 Uplink: MS battery saving
Constraints
 Bit rate (bit/symbol)
 BER requirement
Three sub-algorithms
 Number of sub-carriers determination
 Sub-carriers allocation
 Bit loading
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Start
Number of sub-carriers determination
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Inputs: Each user’s bit rate constraint and
average channel gain for each user
Output: Number of sub-carriers each user gets
assigned
For k = 1,…, K
 Rk 
mk   min 
 Rmax 
Is
N
K
m
k 1
N
k
?
Y
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Two types of sub-carriers: Minimum required
sub-carrier and Extra sub-carrier
Minimum required sub-carriers are to fulfill the
user’s bit rate constraint in the case that
maximum amount of bits will be transmitted in
each sub-carrier
Extra sub-carriers will share bits with minimum
required sub-carriers so that the loaded bits in
each sub-carrier can be reduced and with an
adaptive modulation scheme transmission power
to all user can decrease
No free sub-carrier left
k *  arg min mk
1 k  K
mk *  0
K
Is
m
k 1
k
N
N
?
Y
mk 1
m
k
k
f ( Rmin
/( mk  1))  k f ( Rmin
/ mk )
Gk
Gk
k  1,..., K
l  arg min  k
k 
1 k  K
ml  ml  1
exit
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Start
Sub-carrier allocation
Is
N
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
Inputs: Channel State Information for
each user and number of sub-carriers each
user gets assigned
Output: sub-carriers allocation
n 1
 mk
k ,n
k  1,2,..., K 
?
Y
k=1
Is
Y
k>K
Phase 1: Constructive initial allocation
1.
List the sub-carriers for each user in
descend order according to channel gain
2.
Check sub-carriers user by user if the
number of sub-carrier each user gets is
achieved or the sub-carrier has already
been assigned to some users
3.
If both are NO, assign the sub-carrier to
this user, otherwise skip this user to next
user
?
N
n*  arg max Gk , n
nS
Are
N

n 1
K
and

k 1
 mk
k ,n
0
k , n*
?
Y
 
S  S  n*
S k  S k  n * 
 k ,n  1
*
k=k+1
exit
N
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Start
Sub-carrier allocation
(i, j )  arg max Pi , j
1i  K
1 j  K
i j
Phase 1 may achieve only a local minimum
but not total minimum transmission power
Is
Phase 2: Iterative improvement
 For every iteration, swap a pair of subcarriers allocated to two users such that the
result power can be reduced further
 Power reduction factor is the cost function
in order to select the pair of users and pair
of sub-carriers which can reduce power
most
 Iteration is over when the maximum
possible power reduction is less than zero
max Pi , j  0
?
Y
swap (nij , n ji )
Update sub-carrier allocation
list for each user
(i, j )  arg max Pi , j
1i  K
1 j  K
i j
exit
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Start
Bit loading
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ck ,n  0,
n  Sk
1 k  K
R0
Inputs: Sub-carriers allocation, channel gain
and bit rate constraint
Output: Bits loaded to achieve each user’s bit
rate constraint
Evaluate
Pk ,n (c k ,n ),
n  Sk
1 k  K
Y
Is
R  RT
?
Levin-Campello algorithm
1.
Each time selecting the sub-carrier that requires
the least additional power to add one more bit
2.
Check if the maximum amount of bits loaded in
this sub-carrier has already been achieved and if
this user’s bit rate constraint has been fulfilled
3.
If both are NO, loading one more bit to this subcarrier, otherwise selecting the sub-carrier which
requires second least additional power and
repeat 2
N
n*  arg min Pk ,n (ck ,n )
nSk
1k  K
Find
k*
Which makes
n*  S k *
ck * ,n*  ck * ,n*  1
R  R 1
If
c k * , n*  M n
?
N
evaluate
Pk * ,n* (ck * ,n* )
Exit
Y
Pk * ,n* (ck * ,n* )  
HELSINKI UNIVERSITY OF TECHNOLOGY
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Required bit per symbol
Simulation
60
Bandwidth (MHz)
5
Sampling
Frequency (MHz)
5.6
FFT size (NFFT)
128
Number of users K
2-10
Symbol time (us)
25.81
Channel Sets
200
40
20
0
1
2
3
4
5
6
7
8
Users
required BER
0.01
0.008
0.006
0.004
0.002
0
1
2
3
4
5
6
7
8
Users
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Simulation results:
Number of sub-carriers determination
25
Minimum Required Sub-carriers
Extra Sub-carriers
User
Allocated
subcarriers
Minimum Extra subrequired
carriers
subcarriers
1
19
7
12
2
13
7
6
3
17
8
9
4
18
8
10
5
9
4
5
6
9
5
4
7
24
7
17
8
19
8
11
Number of Sub-carriers
20
15
10
5
0
1
2
3
4
5
Users
6
7
8
HELSINKI UNIVERSITY OF TECHNOLOGY
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Simulation results:
Sub-carriers allocation
Channel Set = 50
1
10
10
0
0
10
-1
10
-2
10
-3
20
40
60
80
Subcarrier index
User1 Channel
User2 Channel
User3 Channel
User4 Channel
User5 Channel
User6 Channel
User7 Channel
User8 Channel
User1 Sub-carriers
User2 Sub-carriers
User3 Sub-carriers
User4 Sub-carriers
User5 Sub-carriers
User6 Sub-carriers
User7 Sub-carriers
User8 Sub-carriers
100
120
Channel Gain
Channel Gain
10
10
Channel Set = 100
1
-1
10
-2
10
-3
10
20
40
60
80
Subcarrier index
100
120
HELSINKI UNIVERSITY OF TECHNOLOGY
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Simulation results:
Bit loading
0
50
100
Subcarrier index
Sub-carrier allocation for user 2
4
2
0
40 60 80 100 120
Subcarrier index
Bit Loading for user 2
6
0
0
10
20
0
50
100
Subcarrier index
Sub-carrier allocation for user 6
6
4
2
0
20
40 60 80 100 120
Subcarrier index
Bit Loading for user 6
6
0
10
Bit Loading for user 5
Number of bits
6
Channel Gain
0
10
Sub-carrier allocation for user 5
Bit Loading for user 1
Number of bits
Channel Gain
Sub-carrier allocation for user 1
10
0
50
100
4
4
2
2
0
Sub-carrier allocation for user 3
20
40
60
80
100 120
Bit Loading for user 3
6
0
0
50
100
Sub-carrier allocation for user 7
20
40
60
80
100 120
Bit Loading for user 7
6
0
10
0
10
0
50
100
4
4
2
2
0
Sub-carrier allocation for user 4
20
40
60
80
100 120
Bit Loading for user 4
6
0
0
50
100
Sub-carrier allocation for user 8
20
40
60
80
100 120
Bit Loading for user 8
6
0
10
0
10
0
50
100
4
4
2
2
0
20
40
60
80
100 120
0
50
100
0
20
40
60
80
100 120
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Simulation results:
BER performance
0
10

-1
Bit Error Rate
10
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-2
10
-3
10
-4
10
-5
10
-10
Adaptive
allocation
with Extra
Sub-carriers
Adaptive
allocation
without Extra
Sub-carriers
OFDM-TDMA
OFDM-FDMA
OFDM
Interleave-FDMA
-5
0
5
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10
15
20
Average Bit SNR (dB)
25
30
35
Minimum 11.33dB gain in SNR using
Adaptive allocation OFDM without
extra sub-carriers over OFDM
Interleave-FDMA
11.84dB gain over OFDM-TDMA
14.35dB gain over OFDM-FDMA
6.91dB gain from extra sub-carrier
presence compared with no extra
sub-carrier case
HELSINKI UNIVERSITY OF TECHNOLOGY
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Simulation results:
Convergence of algorithm
33
30
32
25
Number of iterations
bit SNR
31
30
29
15
10
28
27
20
5
10
15
20
Iteration
25
30
35
5
1
2
3
4
5
6
7
Number of users
8
9
10
11
HELSINKI UNIVERSITY OF TECHNOLOGY
Communications Laboratory
Conclusions
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Adaptive sub-carriers allocation algorithm can enhance the BER
performance compared with static schemes
The use of extra sub-carriers can improve the BER performance and
decrease the total transmission power further
Speed of the algorithm (convergence speed) is fast to meet the real time
application requirements
The speed of algorithm is not affected by the number of users much which
guaranttes it perform well in high load system
BS could use algorithm to increase the total number of users that can be
accommodated for a given power budget
HELSINKI UNIVERSITY OF TECHNOLOGY
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Future study
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Minimization of transmission power in Uplink
Scalable OFDMA
Thank you!