pplications Traditional SON Primary Benefits/ Primary Data Used Typical Update Applications Description Secondary Benefits for SON Decisions Frequencies Dynamically assigns the Minimize dropped Mobile reported Minutes neighbor list, and priority list calls neighbor cell priority per cell measurement results Load balancing Measure the load across cells/ Minimize congestion, Radio network reported Seconds radios/sites and balancing when lower Capex load per radio near congestion Antenna Dynamically adjust antenna tilts Coverage/quality/ Mobile reported quality Hours-days optimization to optimize coverage/lower self-healing from site cell measurement interference outages results Energy savings Turn down active transmitters Lower Opex Radio network reported Hours during off-peak times load per radio Self- Self-populate initial site Lower Opex/quality Network topology, configuration parameters and neighbors for closest cells new sites/radios The above historical SON description was only an illustration of the benefits on what were 3G UMTS networks at the time, and as networks become more dense (more cells/area), have higher bandwidths deployed, consist of multiple technologies, the scale/complexity and opportunity will increase. It is expected that in 5G, SON will "not only apply to physical networks but to balance load across multiple networks/vendors," and as before it will apply to "traffic steering" and "dynamic spectrum allocation." Finally, with respect to the "data layers," this SON was only deployed for the radio access layer; and future SON's will have access to the full data layer stack giving the ability for much greater scale of optimization. Implementing SON closed-loop automation applications in the ONAP framework could con- ceptually be done by designing and implementing an MS that defines the data collection from the network, analytics processing, and actions to be taken utilizing DCAE and ONAP implementing the various SON functions. As an example, Figure 8.18 and Table 8.8 illustrate how MS functions 