# A Modular Web-Based Software Solution for Mobile Networks Planning, Operation and Optimization
## 3 Radio Access Network Algorithms
### Network Diagnosis  
The purpose of the network diagnosis algorithms is to evaluate network performance, in terms of QoS, and to identify cells causing performance degradation to User Equipments (UEs). To this end, four algorithms are presented: the detection of overshooting, pilot pollution, coverage holes, and an algorithm to identify and extrapolate network capacity. Overall, these algorithms evaluate, on a cell basis, the existence and magnitude of each of the above sub performance scenarios.  
The capacity algorithm aims to derive capacity models, specific for each network cell, measuring the UEs throughput by considering the cell specific RF environment, namely the interference levels. Multiple Linear Regression (MLR) is used to estimate the cell total throughput based on high-resolution network Key Performance Indicators (KPIs), such as Channel Quality Indicator (CQI), Modulation and Coding Scheme (MCS), and others. With the corresponding cell capacity model, the maximum capacity (throughput) is estimated. With such a reference, the headroom capacity, i.e., the difference between the cell average and its maximum, is estimated, allowing to identify and predict cells whose capacity limit is being reached [21].  
The overshooting algorithm identifies cells whose coverage reaches beyond what is planned, occurring as an \"island\" of coverage in the service area of another cell. The pilot pollution algorithm detects scenarios where too many pilots (or reference signals) are received in the same area, while lacking a dominant one. Finally, the coverage holes algorithm was developed to find areas where the pilot (or reference) signal power is in between the lowest network access threshold and the lowest value required for assigning full coverage. Even though being independent algorithms, they share the same structure (see Figure 2).  
Figure 1: RAN automation algorithms.  
The overshooting, coverage holes, and the pilot pollution algorithms [22] exploit scanner DT data, and by associating the DT measurements to the respective cells of the mobile network (Cell Footprint block of Figure 2), identify DT measurements corresponding to overshooting, pilot pollution or lack of coverage scenarios. This process, specific for each scenario, is conducted by the Self-Diagnosis block of Figure 2, according to the received power and interference level of each DT measurement. This evaluation requires the user to define power and interference thresholds. Then, the geographical disposition of the identified DT measurements is evaluated by its division into clusters, based on their relative distance (corresponds to the Cluster Partitioning block in Figure 2). It allows to identify prevalent performance degradation and discard isolated behaviors. Finally, the Statistical Analysis block supports the calculation of a severity index, measuring the degree of network performance degradation for each of the involved cells and clusters.  
The capacity algorithm can be applied to 4 th Generation (4G) and to 5G networks [21], while the remaining algorithms only include the legacy networks [22].