# Self-Organizing Networks for 5G and Beyond: A View from the Top
## 3 SON Applications
### The Key SON Applications Leading to Full Automation
#### 3.2.6 SON MLB and TS Applications--Conflicts among MLB and MRO (Mobility Robustness Optimization)  
As expected, the manual handling of load balancing and setting of optimum handover and reselection parameters in real time is extremely difficult due to the constant mobility of users that cannot be predicted. The only exception concerns the cases of mass event handling such as planned concerts or athletic events where operators can approximately predict the load/capacity demands of the network and plan/tune the network accordingly by using specific network features or by adding extra equipment (mobile base stations). Based on these factors, SON MLB applications are considered as one of the most critical SON functions, while their impact has been regarded as one of the most basic for UMTS and LTE networks [22; 23]. The same stands for 5G as well. MLB operation can overcome load balancing issues but needs careful tuning since rapid MLB parameter changes increase the Physical Uplink Shared Channel (PUSCH) interference level in the uplink channel and decrease average the Channel Quality Indicator (CQI) in the downlink for the LTE case [74].  
Furthermore, SON MLB goes hand in hand with another application called SON MRO (Mobility Robustness Optimization), an application that aims to optimize cell reselection in idle mode and handovers in connected mode. However, it has been noticed that MRO operation creates conflicts with MLB and vice versa, since the same mobility parameters are handled by both SON functions. As an example, after MLB changes, handover performance degradation might be noticed and, as expected, the MRO application finds that user mobility problems exist [22; 23; 75]. Figure 8 depicts the conflicts that might be created in mobility thresholds (idle and connected modes) through MLB and MRO applications since both applications interact with idle and connected mode thresholds, and thus conflicts can easily occur.  
The authors of [76] proposed a solution so that these conflicts are avoided through a scheme where MLB is based only on cell reselection instead of handover since there is no conflict between the cell reseelection parameters changed by MRO and MLB. Instead of changing mobility thresholds, an alternative approach for MLB applications which is widely followed by SON vendors is based on the changing of the antenna tilt (either downtilt or up-tilt) since this action affects the coverage area of cells and traffic can be shifted to a neighbor cell that is less loaded. Additionally, the authors of [77] approached MLB operation through antenna tilt changes and concluded on the importance of antenna vertical beamwidth and the addition of an extra handover offset so that a minimum difference in the received power between the serving and neighbor cells is ensured before handover. No matter which technique is used, the aim is to enable subscribers to move and camp in non-congested cells.  
Future research for 5G includes the determination of load by considering the backhaul state as well. A variety of MLB and MRO algorithms have been proposed; however, the former might fail in case backhaul capacity limitations occur. This is very critical for future 5G networks where base station backhaul limitations might lead to low rates for bandwidth intensive services [78]. Finally, the authors of [79] presented a SON load balancing algorithm that considers the backhaul restrictions and proposes the future consideration of backhaul restriction in SON MRO algorithms.