Performance assessments of the 5G network by considering connectivity and capacity analysis of the three 5G communication paradigms with particular attention to the mMTC which is the solution for IoT applications. Performance analysis includes traffic management by “Network Slicing” virtualization techniques and IoT search engine methodologies in order to define suitable model for the acquisition, management and processing of data belonging to energy sector scenarios.
5G evaluations in terms of experimental trials and simulative analysis will represent and useful instrument for the energy sector to obtain information on 5G services availability, performance and connectivity reachable to promote innovative services in this sector such as, advanced power grid monitoring (smart grid application) or end-users effective monitoring consumption thanks to the capillarity of IoT applications (smart meter application).
Preliminary 5G performance analysis have been investigated in this study in order to define suitable “network slicing” paradigm for different type of energy applications.
This evaluation has been provided by defining a proprietary Network System elaboration developed by FUB in the NS-3 environment, named as “5G Planning Tool”, obtained by considering the 5G network architecture composed into several levels: the service level, for the network functions definition in accordance with the desired Key Performance Indicators (KPIs) of the specific energy application; the control level, for the correspondence between the needed requirements of the application and the “orchestration” of physical resources; the physical level, for the identification of all physical resources useful for the service implementation, by considering that physical resources used in the evaluation are based on both high capacity above 6 GHz, and high coverage below 6 GHz.
In practice, the scope of our work is to investigate the 5G connectivity capability for typical energy scenarios in terms of maximum troughput achieved and maximum latency allowable. Subsequently, the obtained results have been used to verify data traffic management policies, based on an SDN approach. Specifically, SDN approach has been investigated in both cases: low data traffic situation to efficiently manage the medium access (i.e. optimization of resources), or heavy data traffic situation to timely enable isolation of a flow of interest (i.e. guarantee of QoS). Performance evaluations showed a remarkable improvement compared to current LTE technology and therefore to be able to meet the connectivity (mMTC), capacity (eMBB) and latency (uRLLC) requirements needed for the different innovative energy services effectively implementation.