Self-optimization process is defined as the process where UE & eNB measurements and performance measurements are used to autotune the network. The self-optimization process collects measurement information from UE and eNB and optimization tool, it auto-tune the configuration data to optimize the network. To maximize network performance, optimizing the configuration while taking into account regional characteristics of radio propagation, traffic and UE mobility in the service area is effective. However, optimization has not been frequently applied because it typically entails a heavy workload for site surveys, analysis of the performance statistics and decision of the optimal parameters. SON automates these tasks by using measurements from network equipments. Optimization is required for ensure that once a cell has been installed it operates to its best level of efficiency.
Types of self-optimizing network functionality. There are a number of areas where self-optimisation of the network is undertaken.
Specifically, it substitutes measurements from eNodeB and UE for the site survey data. It detects problems with quality, identifies the root cause, and automatically takes remedial actions on the basis of the measurement and performance statistics from the OMC. This autonomous optimization allows problems to be handled faster and network performance to be improved. As depicted in Figure 4, NEC’s selfoptimization includes:
· Neighbor list optimization This optimization automatically reconfigures a neighbor list so that the list contains the minimum set of cells necessary for handover. The neighbor list can be dynamically updated on the basis of UE measurement reports. For example, newly reported cells are added, and cells with very few handover attempts or frequent handover failures are removed from the list. These operations can be decided while considering operator’s individual requirements managed in the OMC.
· Coverage and capacity optimization This optimization aims at maximizing the system capacity and ensuring there is an appropriate overlapping area between adjacent cells. The optimal parameter setting is acquired by cooperatively adjusting antenna tilt and pilot power among the related cells. This optimization should operate with some effect even if the measurement reports from UE do not include their data on their own location.
· Mobility robustness optimization To eliminate unnecessary handover and to provide appropriate handover timing, this optimization automatically adjusts the thresholds related to cell reselection and handover. The adjustment is triggered by the related KPI degradation's and is processed while identifying the root causes of the degradation's such as a handover that is too early or too late or the ping-pong effect.
· Mobility load balancing optimization This optimization automatically gets some UEs in the edge of a congested cell re-select or hand over to the less congested adjacent cells by adjusting the thresholds related to cell reselection and handover. Load balancing should be done by using a minimum number of cell reselection or handover without causing the problem of mobility. Also it should minimize total investment in capacity by taking into account the different sides of load such as radio load, transport network load and HW processing load.
Types of self-optimizing network functionality. There are a number of areas where self-optimisation of the network is undertaken.
- Mobility robustness optimisation
- Mobility load balancing and traffic steering
- Energy saving
- Coverage and capacity optimisation
- RACH optimisation
