# Radio Network Planning towards 5G mmWave Standalone Small-Cell Architectures
## 3 Radio Network Planning Results  
Uniformly distributed CNs in the service area represented the area coverage and capacity criterion. An initial throughput requirement was allocated at each CN, which gradually increased. At relatively low capacity requirements, microcells with omnidirectional antenna patterns were uniformly placedby the optimization algorithm, as seen in Figure 4a, in order for each microcell to serve all neighbor CNs (shown in Figure 4a with black stars). The SINR distribution (Figure 4b) also followed this regular pattern. Note that although the received power fell sharply with distance due to the relatively high frequency, the SINR did not fall as rapidly due to the equivalent reduction of the interference from other cells.  
Microcells with omnidirectional patterns were then replaced by tri-sectored microcells, with each sector being a separate gNB in order to offer increased spatially selective throughput. Note that the EIRP of the transmitting BS antennas remained the same for sector and omnidirectional antennas (60 dBm), while a sector could be switched off, if it was not needed, in order to keep interference levels low. Hence, in the results depicted in Figure 5, there was a microcell with only one operating sector, and another microcell with two transmitting sectors. The rest of the microcells were placed as far apart as possible in order for all three sectors to be transmitting and covering a wider area.  
As the throughput requirements increased, denser grids of microcells were deployed. As can be seen in Figure 6a, for high-capacity requirements with the ultra-dense networks, only microcells close to the CNs were transmitting, with only one sector pointing directly towards the corresponding CN. As a consequence, in Figure 6b, the positions not close to a sector antenna pointing directly towards them had very low SINR due to increased interference from the dense transmitting antenna grid. However,  
Figure 4: (**a**) Received power (dBm) and (**b**) SINR distribution in the service area for a dense omnidirectional micro gNB deployment.  
Figure 5: (**a**) Received power (dBm) and (**b**) SINR distribution in the service area for a dense tri-sector micro gNB deployment.  
due to the optimization algorithm, the antenna position was such that there was no CN in a position of low SINR. With such optimal placement, the maximum throughput for the 25 CNs in the area reached as high as almost 16 Gbps/Km\({}^{2}\).  
Overall, comparing the performance of the various network configurations that resulted from the optimization algorithm, it was evident that the denser the microcell deployment, the higher the area throughput (see Figure 7). Moreover, with tri-sector microcells, the throughput almost doubled at the ultra-dense networks with respect to that of dense networks, either with omnidirectional or sector antennas. At these scenarios, as seen in Figure 6, most of the times each microcell had only one sector antenna operating and hence, the advantage with respect to the omnidirectional deployment was due to interference reduction to adjacent cells.  
Figure 8 provides an insight into how dense 5G networks with standalone small-cell architectures can actually get. Even for the omnidirectional reference scenario, the cell radius did not get higher than 400 m, while for the ultra-dense network the cell radius further decreased down to 120 m. The spectral efficiency achieved now was 9.5 bps/Hz/Km\({}^{2}\), approximately three times lower than the 5G target of 30 bps/Hz, although no MIMO/beamforming was considered in our generic analysis. If this is also considered, then it becomes obvious that the spectral efficiency goal will be easily exceeded.  
Figure 6: (a) Received power (dBm) and (b) SINR distribution in the service area for an ultra-dense tri-sector micro gNB deployment.  
Figure 7: Throughput per Km\({}^{2}\) for different network densities with omnidirectional and tri-sector micro gNBs.