## 5 Simulation Results and Performance Evaluation
### Simulations Results and Discussion
In Figure 8, we illustrate the total interest as a function of the transmission delay with varying values of the outage probability parameter \(\xi\), which is the probability for the actual transmission delay to be less or equal to the required transmission delay. A greater value of \(\xi\) means a stricter requirement on the delay performance. It is observed that an increasing \(\xi\) leads to a reduced user interest. This is because a higher \(\xi\) implies that there is less tolerance to random delay outage. In addition, it is interesting to see that a high user interest with a small transmission delay o \begin{table}
\begin{tabular}{c c} \hline \hline
**Simulation Parameter** & **Parameter Value** \\ \hline Initial temperature \(T_{0}\) & 0.5 \\ Cooling method & \(T_{i+1}=\beta T_{i}\), \(\beta=0.9\) \\ Maximum number of iterations & 500 \\ Population size & 30 \\ Crossover percentage & 0.5 \\ Mutation percentage & 0.4 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation settings for simulated annealing (SA) and genetic algorithm (GA). Figure 6: The total user interest as a function of the transmission delay with different algorithms (\(P_{T}=2W\), \(\xi=0.9\) and \(\lambda=0.5\)). when the outage probability parameter \(\xi=0.6\). This implies that, in practice, a system designer should aim to strike a balance by jointly choosing proper values for \(\xi\) and the transmission delay. Furthermore, Figure 9 demonstrates the impact of the BS power constraint on the trade-off performance. Intuitively, the overall user interest is observed to increase with increasing power. When the power is large, an ideal solution with low transmission delay and high user interest could be achieved. However, increasing the power supply indefinitely will have diminishing returns in terms of energy efficiency. We further note that the aspect of intercell interference is not addressed in this paper. In practice, high BS power will drive the capacity to the interference-limited region, where the energy efficiency can be arbitrarily low. In practice, the power constraint should be properly chosen according to a targeted interest-delay trade-off performance. Finally, Figure 10 demonstrates how the proposed system can be used to effectively differentiate users' QoE/QoS. As shown in Equation (21), our system supports customized user QoS by allowing different users to have different delay constraints. The proposed radio resource allocation algorithm allocates a user's data rate to be inversely proportional to its delay. As a result, high-priority users with low transmission delay will be allocated with more radio resources and will hence enjoy better user  
Figure 8: The total user interest as a function of the transmission delay with varying outage probability \(\xi\) (\(P_{T}=2W\) and \(\lambda=0.5\)). Figure 7: The total user interest as a function of the transmission delay with varying user arrival rate \(\lambda\) (\(P_{T}=2W\) and \(\xi=0.9\)). QoS/QoE. A proper measure of the QoE is the individual user's interest (instead of the sum interest). Figure 10 shows the individual user's interest as a function of the traffic arrival rate \(\lambda\) with varying user delay constraints. It is observed that the user interests can be effectively differentiated by setting different delay constraints \(\tau_{u}\). In addition, Figure 10 also evaluates the joint impacts of traffic density \(\lambda\) and outage probability threshold \(\xi\) by varying both parameters together. Intuitively, it is observed that the user interest decreases with increasing density and outage threshold. However, it is interesting to see that, when the outage threshold is relatively low (i.e., more tolerance on outage), the user interests remain steady with increasing traffic density until \(\lambda\) reaches a certain threshold. In other words, a smaller outage threshold corresponding to a higher traffic density threshold, below which changing the traffic density has a marginal impact on the user interest.