By Pietro Cassarà, Alberto Gotta, and Abraham Gebrehiwot, CNR-ISTI, CNR IIT, Italy
Integrating Non-Terrestrial-Network (NTN) with the 5G-based Terrestrial Network (TN) extends existing network telemetry infrastructures’ coverage, reliability, and bandwidth. Non-terrestrial platforms act as components of the Radio Access Network (RAN); indeed, the 3GPP is committed to defining standards and architectural solutions to integrate the NTN into the 5G infrastructure.
Even though the NTN provide the enhancements for the communication infrastructures discussed above, we must address some challenges to integrate these with the 5G-based infrastructure. Non-terrestrial platforms such as UAV, LEO, and MEO move reciprocally and respect the UE, posing the issue of how to manage the changing of the topology of the RAN.
In a 5G ecosystem, all the controlling operations related to network management are achieved by a centralized controller placed in the core network; this core-centered approach can make it difficult to adopt an NTN-Based RAN for the above reasons.
A possible solution to address this problem is to move part of the controlling operations closer to the UE evenly in a distributed manner. To address this issue, we aim to investigate traffic monitoring and AI-based procedures for managing network resources and QoS for defining a framework to monitor the traffic parameters on the service, inter-satellite, and feeder links of the scenario depicted below. We investigate architectural solutions to perform traffic monitoring, which helps extract analytics on the status of the network, which, in turn, we can use to feed learning-based procedures for optimizing the provisioning of the network resources (path, radio channels, QoS levels). The learning-based procedures represent one of the main tools to support the development of optimizing procedures involving the cooperation of network entities, such as core and UE, but making analytics available becomes mandatory.
One technological solution for designing traffic monitoring tools for the 5G-NTN communication scenario considered here is provided by In-Band Network Telemetry (INT) operating on the data plane (UP) of the 5G ecosystem. We want to study INT to exploit the ability of this approach to embed metadata in user packets to extract analytics for providing optimized real-time network management for Service Level Agreement (SLA), user experience enhancement, route enforcement, and resource allocation. INT doesn’t require interfacing with the core, working at the UP, allowing more streamlined monitoring operations.
As the network becomes increasingly complex, such as the scenario considered here, traditional Operations Administration and Maintenance (OAM) approaches may not meet the requirements for monitoring and measurement operations, INT is emerging to provide high-precision flow insight and real-time notifications to support network management and maintenance optimized for the users and applications also for complex network scenarios. This is possible because INT can be accomplished using extensions of the tunneling protocols, such as GTP-U, or even new routing protocols, such as SRv6, according to the protocol stack proposed above. Against the pros introduced above, the cons of the INT approach are due to the transportation of data telemetry over the data links (paths), which lowers the available bandwidth. This problem can be mitigated by adopting such a mechanism for the rate adaptation of the rate to send to data telemetry. However, in the 5G ecosystem, where several layers of virtualization and encapsulation are commonly used, the overhead due to the telemetry may be irrelevant to the KPIs of the system.
Finally, to address the performance measurements for the 5G-NT ecosystem, we refer to the 3GPP technical specification, TS 28.552. In particular, in section 5.1, the performance measurements for the NG-RAN are defined, and in section 5.1.1.13, those related to the QoS flows. Note that some of the definitions for layer 2 in TS 28.552 are inherited from TS 38.314 and recalled in TS 38.331. The performance measurements for 5GC are defined in TS 28.552 from sections 5.2 to 5.6. Instead, the 3GPP’s documents, TS 28.554 and TS 32.404, define Key Performance Indicators and the measurement template, respectively.