5.5.0.1 Simulation Scenario A
In this scenario the average throughput performance as a function of time horizon was studied. Fig. 5.2 shows the simulation results of which the throughput performance under access decision based on belief vector and that of access decision based on the end-to-end distortion are compared. Fig.5.2 shows the average throughput performance for three dif- ferent cases. In the first case it is assumed that the channel access decision is based on the perfect knowledge of the system (optimal channel access decision). This is an ideal condition and as it can be seen from Fig. 5.2 that the average throughput performance increases with time reaching 2.17 in 10 seconds. In the second case, the channel access decision is based on the belief vector of the POMDP solution. This belief vector is the probability distribution over system state where the optimal decision can be read from the value function for any belief state. This channel access decision method does not perform well when transmitting real-time traffic such as video. As shown in Fig. 5.2, the throughput performance 1.9 in 10 seconds which is the difference of about 0.27 from the ideal case. However, for real time ap- plications such as video, the throughput performance can be improved using channel access decision based on end-to-end video distortion (proposed scheme). Thus, in the third case the throughput performance is improved to about 2.2. This generally shows that for real time traffic such as video, the channel access decision based on end-to end decision performs much better (in terms of average throughput) as compared to channel access decision based on the belief vector.
5.5.0.2 Simulation Scenario B
In this simulation scenario we aimed at studying the spectral efficiency performance as a function of prescribed collision probability for the proposed scheme. The perfect optimal channel access decision was compared with the channel access decision based on the end- to-end distortion. The simulation results show that at large values of collision probability the overall spectral efficiency performs poorly. The reason for this is that, by increasing the
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Average Throughput of SU (bits per slot)
Perfect optimal decision (ideal case) Decision based on belief vector
Decision based on end−to−end distortion
Fig. 5.2: Throughput performance for the proposed system under different channel access decision.
chances of collision the effective usage of spectrum is affected since the secondary users will not transmit due to collision. However, there there is an optimal value of collision probability of which the spectral efficiency approaches that of the perfect channel access decision. Thus, the simulation results in Fig. 5.3 indicates that at the prescribed collision probability of about 0.2, the spectral efficiency approaches that of the optimal channel access decision.
However, beyond the collision probability of about 0.2, the spectral efficiency falls due to the effects of collision. Thus, the proposed scheme achieves its optimal value of spectral efficiency at the prescribed probability of collision of about 0.2.
5.5.0.3 Simulation Scenario C
In this scenario we aimed at studying the throughput performance of the proposed system in terms of prescribed collision probability as a function of average throughput. We make
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Prescribed probability of collision
Spectrum efficiency (bits/slot/Hz)
Perfect optimal channel access decision
Proposed channel access decision based on end−to−end distortion
Fig. 5.3: Spectral efficiency as a function of the prescribed collision probability.
comparison between the channel access decision based on the perfect optimal scheme and the channel access decision based on the end-to-end video distortion. As it can be seen from Fig. 5.4 that the average throughput increases with the prescribed probability of collision. From the simulation results it is noted that the proposed scheme perform much better than that of optimal decision in terms of average throughput. Thus, the scheme performs better at the interval of prescribed collision probability of about 0.1 to about 0.4 and then the throughput starts to fall as the collision probability increases.The reason for this is that, at low values of collision probability the channel is likely to be unoccupied and hence the successful transmission by secondary user is possible. On the other hand, increased prescribe collision probability, unsuccessful transmission by secondary user is likely to happen and hence the average throughput is affected. However, we need to find an optimal point where the throughput and the spectral efficiency are optimal because increasing the average
throughput while jeopardising the spectral efficiency is contrary to the role of cognitive radio. On the other hand, throughput has a significant effects to the QoS for multimedia applications such as video applications in cognitive radio networks.
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Average throughput(bits/slot)
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Proposed channel access decision based on end−to−end distortion
Fig. 5.4: Throughput performance as a function of prescribed collision probability.
5.5.0.4 Simulation Scenario D
In this simulation scenario, we aimed at showing the average throughput and the spectral efficiency both as a function of prescribed collision probability. As it can be seen from Fig.
5.5 that both average throughput and the spectral efficiency are highly affected by increased collision probability. However, at the prescribed collision probability of about 0.2, the scheme achieves the maximum average throughput and maximum spectral efficiency.
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Average throughput(bits/slot)
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Access decision based on end−to−end distortion
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Spectrum efficiency (bits/slot/Hz)
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Access decision based on end−to−end distortion
Fig. 5.5: Probability of miss detection vs average throughput and spectral efficiency perfor- mance comparisons.