5g Core Networks Powering Digitalization Pdf Download

Banking 4.0 uses IT technologies to provide customers with banking services anytime, anywhere. To achieve this, a distributed transformation of the core financial system is necessary. Traditional centralized architecture is hard to expand, slow to deliver, and expensive to upgrade or expand (in terms of capacity). In contrast, distributed architecture delivers a 99.999 percent system availability and supports over 10,000 servers (compared to 10 hosts). The communication between servers migrates from internal buses to network buses, and applications can be deployed across regions and data centers. However, distributed financial architecture also poses new requirements for financial networks, including high-quality lossless transmission and fast deployment of micro-services across data centers.

The first major step of virtualization was to migrate those application-specific blades to virtualized resources such as virtual machines (VMs) and later containers. ETSI NFV (Network Function Virtualisation) and OPNFV was created to facilitate and drive virtualization of the telecoms networks by harmonizing the approach across operators. The network element could then be realized as an application that is distributed among several virtual hosts. Because the application was no longer constrained by the resources and capacity of a physical chassis, this step allows much greater flexibility of deployment and for harmonization of the installed hardware. For example, the operator can deploy much larger (or even much smaller) instances of the network element. This first step was also mainly for proving that a virtualized host environment could scale appropriately to meet the subscriber and capacity demands of today's mobile core. However, most applications in this phase are like a 2-Tier application design wherein the second (Logic) tier the application itself was tightly coupled to state storage it required. The storage design to maintain state was ported from physical systems where individual blades had their own memories.

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One of the main drivers for the evolution of the core network is the vision to deliver networks that take advantage of automation technologies. Across the wider ICT domain, Machine Learning, Artificial Intelligence and Automation are driving greater efficiencies in how systems are built and operated. Within the 3GPP domains, automation within Release 15 and Release 16 refer mainly to Self-Organising Networks (SON), which provide Self-Configuration, Self-Optimisation and Self-Healing. These three concepts hold the promise of greater reliability for end-users and less downtime for service providers. These technologies minimize lifecycle costs of mobile networks through eliminating manual configuration of network elements as well as dynamic optimization and troubleshooting.

5G holds unique challenges, however, which makes automation of configuration, optimization and healing a core part of any service providers network. The drivers for this include the complexity of having multiple radio networks running and connecting to different cores simultaneously, the breadth of infrastructure rollouts required and the introduction of concepts such as network slicing, dynamic spectrum management, predictive resource allocation and the automation of the deployment of virtualization resources outlined above.

The 5G Core, however, brought a mindset shift aiming to define an access-independent interface to be used with any relevant access technology as well as technologies not specified by 3GPP such as fixed access. It is also, therefore, intended to be as future-proof as possible. The 5G Core architecture does not include support for interfaces or protocols towards legacy radio access networks (S1 for LTE, Iu-PS for WCDMA and Gb for GSM/GPRS). It instead comes with a new set of interfaces defined for the interaction between radio networks and the core network. These interfaces are referred to as N2 and N3 for the signaling and user data parts respectively. The N2/N3 protocols are based on the S1 protocols defined by 3GPP for 4G LTE (S1-AP and GTP-U), but efforts have been made to generalize them in the 5G System with the intention to make them as generic and future proof as possible. N2/N3 are described in Section 3.5.

While this is within the scope of 3GPP specifications in Release-15, it remains to be seen if any LTE networks will actually be converted to connect to the 5GC core network, or if service providers will instead rely on maintaining the S1 connection to EPC combined with interworking between EPC and 5GC, a solution we will describe further in Section 3.8.

In conjunction with extending the new 5G architecture to not only include NR access but also LTE access, a parallel track was started in the 3GPP Release 15 work. This was driven by a widely established view in the telecom industry that there was a need for a more rapid and less disruptive way to launch early 5G services. Instead of relying on a new 5G architecture for radio and core networks, therefore, a solution was developed that maximizes the reuse of the 4G architecture. In practice it relies on LTE radio access for all signaling between the devices and the network, and on an EPC network enhanced with a few selected features to support 5G. The NR radio access is only used for user data transmission, and only when the device is in coverage. See Fig. 3.1.

Traditionally, few cores integrated on a single chip allow for simple bus interconnect strategies, where one sender broadcasts data onto the bus, and the intended receiver reads the bus line. As the number of cores scales, the bus quickly becomes a bottleneck as more cores are trying to communicate on the bus. While this consists of minimal overhead, network congestion leads to high latency and low throughput. Latency is defined as the amount of time that passes when the sending core sends out data to the point in which the receiving core obtains that data. Throughput is defined as the total amount of data moving at any one given instant of time within the NoC. An example of a 16-core bus network can be seen in Fig. 1.1a. Direct extensions of the bus network include multibus and hierarchical-bus networks (Thepayasuwan et al., 2004). Multiple busses can be added into the network so a single core is not able to congest the entire network, allowing additional cores to be able to transfer their data as well.

A continuation of the bus network is the ring and star-ring networks, seen in Fig. 1.1b and c, respectively. For a ring, each core is connected to its own individual network switch and the network switches are connected to two neighbors. In the case of the star-ring an additional central network switch connects to all other switches. The dedicated switch in the star-ring network allows the core to send its data and do other tasks while the network switches take care of data delivery. An insufficiency with the ring network is that the average hop count between cores is relatively high as can be seen in Table 1.1. Hop count is the number of links that data has to traverse before arriving at the destination core from the sending core considering uniform random traffic. The more cores that are inserted into the ring network, on average, the more number of hops it takes to reach any other core. The star-ring network was created to introduce shortcuts into the network to try and reduce the average hop count within the network, reducing the average hop count from 6.2 to 3.8 for a 16-core network, as seen in Table 1.1. However, this requires a very large network switch, with N ports, for an N core network to be built that has to connect to each of the other network switches. Although the central switch reduces the average hop count, it also creates a traffic bottleneck; all of the traffic will try to use this network switch as it creates shortcuts in the network. 006ab0faaa