PLNC-LOG
DFSO-LOG
Figure 4.2: Comparison of outage probability between different systems
(Solid line represents lower bound of analytical results while ∗ sign indicates simulation results).
performance.
Data rate (bps)
3 4 5 6 7 8 9 10
Outage probability
10
-210
-110
0PLNC
OSM-DFTWR
Figure 4.3: Comparison of upper bound on outage performance with respect to data rate
(Solid line represents γloss = 0 dB analytical results, o sign indicates γloss = 0 dB simulation results, dashed line indicatesγloss= 3 dB analytical results and x sign indicatesγloss= 3 dB simulation results).
For different SNR loss factors,γloss=0 dB, γloss=3 dB and γloss=6 dB, the lower bounds on outage probabilities are shown in Fig. 4.4. The target data rate is 3 bps and the SNR at relay node is equal to the SNR at the source nodes. It can be observed from the graphs that increase in SNR loss factor TH-2298_156102008
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degrades the system performance due to increase in inter-laser optical interference. The analytical and simulation results are validated by asymptotic results also and it is observed that the asymptotic results merge with the analytical and simulation results for high SNR values, thereby justifying our analysis.
The increase in self-interference causes an increase in outage probability. For example, for SNR=20 dB, the outage probability value forγloss=0 dB is 0.08, outage probability value for γloss=3 dB is 0.09, while forγloss=6 dB, the value is 0.13. Thus we can observe that the outage probability value increases with increase in SNR loss factor. The analysis can be interpreted in a different manner. As the SNR loss factor increases, it means there is more interference at the relay node due to simultaneous transmission from the source nodes. Hence reception of message by the relay node in the first time slot is not correctly done. The relay is incapable of transmitting the message correctly in the second time slot in presence of interference, leading to more chances of error. Thus the outage probability performance becomes worse with increase in SNR loss factor.
SNR (dB)
0 10 20 30 40
Outage probability
10
-410
-310
-210
-110
0γ
loss=0, 3, 6 dB
Figure 4.4: Comparison of outage performance of the system with different SNR loss factors
(Solid line represents analytical results, ∗ sign indicates simulation results and dashed line represents asymptotic results).
In Fig. 4.5, the performance of OSM based DFTWR is analyzed in terms of link distance. It is evident from the graph that there is an increment in outage probability value with an increment in link distance (as distance between source nodes and relay is increased), thereby leading to inferior system performance. Atmospheric turbulence causes fading which increases with an increase in distance. As the distance increases, the LOS path is blocked due to presence of more obstacles. The optical signal also has to travel through more turbulences. The light rays undergo more scattering and refraction as
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the turbulence increases, thereby resulting in reception of poor signal at the receiver located far away.
This is the reason for poor performance of the system at large link distances. The analytical results are justified by means of simulation results. The asymptotic results converge with the analytical and simulation results for high SNR values, thereby justifying our analysis.
SNR (dB)
0 10 20 30 40
Outage probability
10
-310
-210
-110
0L=2, 6, 8
Figure 4.5: Effect of link distance on the lower bound of outage performance of the system
(Solid line represents analytical results, ∗ sign indicates simulation results and dashed line represents asymptotic results).
The performance of OSM-DFTWR is verified by Monte Carlo simulations for different atmospheric conditions in Fig. 4.6. The simulation results are in close accordance with the analytical results. The asymptotic results also show close match with the analytical and simulation results at high SNR values, thereby justifying our analysis. This system gives reasonably good performance even under strong and moderate atmospheric turbulences where fluctuations in atmosphere are much more. The outage probability is maximum for strong atmospheric turbulence while it is least for weak condition. Hence it is concluded that G-G channel yields optimum performance even in harsh atmospheric conditions. It is pertinent to note that as the atmospheric turbulence increases, the Rytov variance value increases due to increase in value of the constant Cn2. Accordingly, the value of αG and βG changes to denote the presence of more scattering effects. This hampers the optical signal propagation, leading to more error for higher degrees of turbulence. During daytime when the air gets heated up and the hot air being lighter rises up, more turbulence effect is created leading to increase in Cn2 value. This also degrades the performance of our proposed system. Again during night, the value of Cn2 is the least leading to weak turbulence effect, thereby improving our system performance. Fog and snow also influence the TH-2298_156102008
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turbulence conditions, thereby changing the system performance accordingly. Thus it can be inferred that the amount of turbulence plays a key role in determining the system performance. We have broadly categorized the varying turbulence conditions into three categories, however for other conditions, values of αG and βG can be calculated and accordingly the system performance can be compared.
SNR(dB)
0 10 20 30 40
Outage probability