# An Improved Dynamic Joint Resource Allocation Algorithm Based on SFR
## 4 Simulation  
In this section, we investigate the performance of proposed JPFA algorithm, static FFR, static FFR, and traditional dynamic joint resource allocation algorithm (ASFR) [16]. We consider a 19-cell downlink cellular network where service area consists of all 19 cells, the interior radius and the cell radius is equal to 600 and 750, respectively, each cell owns 50 RBs. There are 20 users in each cell and the lowest throughput requirement is 0.8 Mbps rate per user. A detailed description of simulation parameters is shown in Table 2.  
In static FFR, we divided 50 physical RBs into two groups, Group 1 contains 30 which are shared by edge users with a cell-edge reuse factor of 3, and Group 2 is for the center region with a reuse factor of 1. The transmit power of each RBs is the same. In static SFR, 48 physical RBs are shared by edge users with a reuse factor of 3 and the power ratio factor is 0.5.  
Figure 3 shows the user distribution in 19 cells under one simulation. Figure 4 compares the cell-edge RBs distribution of proposed DJRA with the aforementioned static SFR (SSFR) in one Monte Carlo simulation. As seen from Figure 4, a total of 16 sub-resources are available to edge users in SSFR. However, as the users are randomly distributed in each scenario, the resource allocation predetermined scheme can not obtain the best system performance. Compared with the static resource allocation, our dynamic joint resource allocation approach breaks the original fixed patterns  
Figure 2: Interior sector partition.  
In Figure 5, we plot the cumulative distribution function (CDF) to show data rate achieved by each user. As seen from the figure, the performance of SFFR is the worst. This is because SFFR sacrifices the spectrum efficiency to suppress ICI. Despite SSFR being superior to SFFR, the fixed resource allocation pattern still limits its performance improvement. ASFR and our scheme achieve a superior rate. As expected, the best results are provided by our scheme and there are significant improvement benefits from adopting the sector partition method in the center region.  
Table 3 is the numerical analysis of Figure 5. It is obvious that our scheme gives a better solution to the cell-edge user interference and the data rate of DJRA is 0.2 Mbps higher than ASFR algorithm.  
We contrast the average throughput for a single cell and the average data rate achieved by each edge-user in Figure 6. Tables 4 and 5 are the numerical analysis of Figure 6a,b. Comparing the DJRA algorithm with the ASFR algorithm, we can conclude that applying the sector partition method in the center region is an effective way to improve the system sum rate. This is because the center user interference mainly comes from the edge users in neighboring cells, and the edge user interference mainly comes from the center users in neighboring cells. Thus, eliminating cell-center users 'interference is equal to suppressing the edge users' interference in its adjacent cells. Thereby, our approach can also achieve a better behavior for cell-edge users.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**DJRA** & **ASFR** & **SSFR** & **SFFR** \\ \hline
1.369–3.245 & 1.169–3.044 & 0.805–2.844 & 0.622–2.385 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Numerical analysis (Mbps).  
Figure 5: Data rate achieved by each user under different schemes.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**DJRA** & **ASFR** & **SSFR** & **SFFR** \\ \hline
1.809 & 1.503 & 1.332 & 0.901 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Edge-user date rate numerical analysis (Mbps).