# Fronthaul Design for Wireless Networks
## 4 Fronthaul Design Study Results
### Network Assessment
#### 4.2.2 Urban Environment  
Figure 10 presents, for each of the considered test scenarios, the obtained results for the urban environment. As can be observed, the distribution of technology usage regarding the RRH-BBU links can be categorized into two groups, according to the visibility conditions: (1) low fog intensity scenarios, where the FSO technology usage is largely dominant (roughly 90-98%) and FO systems account for the remaining RRH-BBU links, with a usage percentage that increases along with the increase of the rain  
Figure 9: Network costs and technology usage for the rural environment.  
intensity (particularly because the performance of FSO systems is also impaired by the presence of rain, as seen in Section 4.1); and (2) high fog intensity scenarios, in which the distribution of technology usage is practically unaffected by the rain intensity and almost all RRH-BBUs links (about 99%) are served by FO systems. Still regarding the latter group, it is important to notice that even in the presence of harsh visibility conditions in the respective scenarios, FSO systems were adopted for the remaining RRH-BBU links (i.e., approximately for 1% of the cases); this occurred because, unlike the rural environment, some of the RRH-BBU link lengths were always very small (notably less than 200 m) due to the higher RRH density of the urban environment.  
Turning the attention now to the network costs, the results showed that the visibility conditions also have a major impact on the urban fronthaul costs: not only high fog intensities led to more expensive networks, but also cheaper ones were obtained when there was low fog intensity; in particular, the possibility of exploiting FSO systems when the visibility conditions were favorable led to a cost reduction of 23% in rainy scenarios (cf. S(r_h/f_h) vs. S(r_h/f_l)), whereas a cost reduction of 38% was verified under non-rainy scenarios (cf. S(r_l/f_h) vs. S(r_l/f_l)). It is also worth to point out that, regardless of the rain intensity, the network costs were very similar whenever the fog intensity was high (cf. S(r_l/f_h) vs. S(r_h/f_h)), mainly because MRT systems were not adopted; in any case, although it is unnoticeable in Figure 10, the costs were slightly cheaper in S(r_h/f_l) than in S(r_l/f_l)) owing to a non-negligible performance increase of FSO systems when the rain intensity decreased, which in turn slightly increased the FSO technology usage.  
With respect to the average number of required BBUs, although the lowest value was obtained for the scenario that yielded the lowest average network costs (i.e., S(r_l/f_l)), the opposite was not true, as the highest number of required BBUs occurred for the second cheapest scenario (i.e., S(r_h/f_l)). This shows that the number of required BBUs on its own is not sufficient to have an estimate regarding the final network costs also in urban environments. Finally, notice that although colocated BBUs with RRHs were never adopted as cost-effective solutions regarding the urban environment results, in practice, it may compensate economical to change the placement of a BBU (which was initially suggested by preliminary cost-effectiveness studies) in order for it to match the position of a nearby RRH (for instance, if the initial distance between them is below 20 m), thus saving, e.g., site rental costs.  
Figure 10: Network costs and technology usage for the urban environment.