SINR analysis

1. <Fundamentals and PHY>#1570146193
SINR Analysis of OFDM Systems Using a Geometry-Based
Underwater Acoustic Channel Model
Do Viet Ha∗ , Nguyen Van Duc∗ , Matthias Pätzold†
∗Hanoi University of Science and Technology, Ha Noi, Viet Nam
†University of Agder P.O. Box 509, 4898 Grimstad, Norway

2. Outline
▪Motivation & Research Objectives
▪UWA Geometry-based channel model
▪ICI and Noise Analysis
▪Numerical results
▪Conclusions
2

3. Motivation and Objectives
▪ Underwater acoustic channel models
▪ The ICI has strong effect in UAC systems
▪ The ambient noise is not white noise
▪ SINR analysis: the ICI effect in combination with
ambient noise
▪ Models for simulation studies
3

4. UWA Geometry-based channel model [1]
▪ For a shallow water
environment.
▪ Randomly distributed
scatterers.
▪ Method of equally spaced
scatterers (MESS) 2,
T
nD
2,n
2
T
y
1
T
y
1,
T
nD
1,n
2,nS
0D
,l n
Sy
0
1,
R
nD
0
xT
2
R
y
1
R
y
R
V
2,n
1,n
xR
x
RV
2,
R
nD
D
4
Geometry-based shallow UWA
channel model
,
1
2
i n
i
D
x n
N
 
  
 
[1] M. Naderi, M. Pätzold, and A. G. Zajic, “A geometry-based channel model for shallow underwater acoustic channels under rough surface and scattering
conditions,” in Proc. 5th International Conference on Communication and Electronics, ICCE 2014. Da Nang City, Vietnam, pp. 112–117, Aug. / Sep. 2014.

5. ICI Analysis of UWA-OFDM systems
▪ Using the geometry-based UWA channel model
▪ Doppler effect in UWA-OFDM systems
▪ SIR analysis
▪ SINR analysis
5

6. SIR calculation
▪ Analyze the desired
signal and the
interference signal
▪ Using the time
correlation function.
▪ Not depend on transmit
power
6
   
     
1
1
1 1
2 /
0, 1
[ ]
N
HH
p N
k N N
j m k p N
HH
m m k p N
N p R pT
SIR f
N p R pT e 

 
 

   


  

 
SIR S
I
P
P

Desired signal power
Interference power
Time correlation function

7. SIR Analysis
▪ SIR increases with
▪ Larger bandwidth
▪ Lower Doppler
frequency
SIR for various values of the maximum Doppler
frequency.
7

8. SINR calculation
▪ Both the ICI and ambient noise effect
▪ SINR calculation
▪ Depend on transmit power
8
SINR
R
S
R
I N
P
P P


Desired signal power
Interference power Noise power

9. Transmit power
▪ Need to be carefully determined
▪ which SNR should be achieved ?
9
   
 
 
 
 
3
3
0 3
1
SNR
,
B D
T
B D
W f df
P D B D
A D f df



PSD of ambient noise
Acoustic attenuation
3 dB Bandwidth
Given SNR
Transmission
distance

10. SINR versus SNR
▪ Proper SNR to restrict
the ICI effect.
▪ Threshold of SNR: 20dB
SINR for various values of the maximum Doppler
frequency
10

11. Transmit power
▪ Long transmission
distance  low carrier
frequency.
Required transmit power versus transmission distance for
different carrier frequencies
11

12. Ambient Noise Power
▪ Depend on
▪ Signal frequency
▪ Boat activity, the speed
of wind
12
 
2
2
c
c
B
f
N
B
f
P W f df


 
[2] A. Abdollah Doosti, J. Mohammad Javad, and V. Vahid Tabataba, “Design and simulation of a secure and robust
underwater acoustic communication system in the persian gulf,” Communications and Network, vol. 3, no.2, 2011
Ambient noise level for different frequency domains [2].

13. The ICI and Ambient noise power
▪ Increased bandwidth
▪ ICI power decreases
▪ Noise power increases
Noise power and ICI power for different values of the
maximum Doppler frequency
13

14. SINR analysis
▪ Doppler effect is strong in
narrow bandwidth.
▪ Chose suitable bandwidths
▪ Channel capacity
consideration
▪ Trade bandwidth for SINR
and vice versa. SINR for various values of the maximum Doppler
frequency
14

15. Conclusion
▪ UWA channels : characteristics, ambient noise,
Doppler effect
▪ Analyze both the ICI and the noise effect.
▪ Practical guidelines for UWA-OFDM system
design.
15

16. Thank you for your attention
Q&A
16