## 4 Federated System
### Simulation Setup
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Slice Type** & **MEC CPU** & **MEC RAM** & **MEC Storage** & **MEC BW** & **RAN R** & **RAN L** \\ \hline
1 & 4 cores & 16 GB & 100 GB & 40 Mbps & 50 Mbps & 20 ms \\ \hline
2 & 4 cores & 32 GB & 100 GB & 100 Mbps & 30 Mbps & 30 ms \\ \hline
3 & 8 cores & 16 GB & 32 GB & 80 Mbps & 20 Mbps & 1 ms \\ \hline
4 & 4 cores & 8 GB & 16 GB & 50 Mbps & 25 Mbps & 5 ms \\ \hline
5 & 2 cores & 8 GB & 32 GB & 40 Mbps & 10 Mbps & 10 ms \\ \hline
6 & 2 cores & 8 GB & 32 GB & 40 Mbps & 5 Mbps & 40 ms \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Slice requirements. The \(\epsilon\)-decay function is mathematically defined as follows:  
\[\epsilon_{t}=\epsilon_{0}\cdot e^{-\lambda t} \tag{18}\]  
where the following are defined:  
* \(\epsilon_{t}\) is the exploration rate at timestep \(t\). * \(\epsilon_{0}\) is the initial exploration rate (\(0.25,0.5\), or \(0.75\)). * \(\lambda\) is the decay rate, determining how fast exploration decreases. * \(t\) is the current training timestep. This approach ensures that exploration gradually reduces over time, transitioning smoothly into a purely exploitative phase. The best-performing configuration was found with \(\epsilon_{0}=0.25\), dedicating 25% of the training period to exploration before switching to full exploitation. Table 4 summarizes the configuration parameters that yielded optimal performance during the centralized training stage of the proposed model. The scenario setup was divided into two parts, with the first part focusing on configuring the radio resources and the second part focusing on configuring the MEC resources. To conduct the RAN simulation, a channel bandwidth of 100 MHz was assumed, resulting in two BWPs of 50 MHz each, with different numerologies, to allocate PRBs to slice requests requiring low latency or not, respectively. BWP1 was configured with a 15 kHz SCS, while BWP2 used a 30 kHz SCS. The guardband applied to each side of the carrier corresponds to the numerology immediately adjacent to the guardband, resulting in a 692.5 kHz guard for BWP1 and a 1045 kHz guard for BWP2. The spectral efficiency, denoted by \(\eta\), was assumed to be that corresponding to 64-QAM modulation with a code rate of 873/1024. The threshold value used to determine whether a request is latency sensitive was set to 10 ms, so slice request radio resources whose latency demand is below this value will be allocated in BWP2. Regarding the resource configuration of the MEC platform, reserved resources are allocated for each slice defined in the configuration, as outlined in Table 5. This approach ensures isolation between different types of slices in terms of available resources. For the FL system, the participating clients were configured to receive commands from the server in the format expected by Stable Baselines3 implementations and respond with the requested parameters correctly. On the other hand, the server was configured to use the FedAvg aggregation strategy, which was selected because of its favorable behavior in environments such as the proposed system [22]. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Hidden neurons & 32 \\ \hline Buffer size & 150,000 \\ \hline Learning rate & 0.01 \\ \hline Batch size & 64 \\ \hline Gamma & 0.99 \\ \hline Training timesteps & 500,000 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation training hyperparameters.