Ping-Heng Kuo and Alain Mourad,InterDigital Europe Ltd., London, UK

To support the large diversity of services envisioned in future wireless networks, the co-existence of different radio access technologies (RATs) both legacy and new is foreseen in the same local service area. The tight interworking and cooperation amongst these RATs will thus become a must. Such cooperation takes a new spin through the emerging paradigm of offering data services out of context information that may be collected from the devices and nodes in each RAT. The main objective of this paper is to introduce a novel concept and framework for multi-RAT convergence, where such convergence is approached from the new angle of exchanging data services. This exchange is envisioned through a common edge and fog system consolidating all the networking, computing, and storage resources available in the local service area. This novel concept is pioneered by the H2020 Europe-Taiwan 5G-CORAL project.

1. Introduction

The fifth-generation (5G) mobile communications has promised to offer diverse types of services. In particular, there are three main pillars of 5G, including enhanced mobile broadband (eMBB) services, ultra-reliable low-latency communications (URLLC), and support of Massive-Connections for machine type communications. This in turn implies that the user devices in 5G will range from sophisticated handset such as a smartphone/laptop, automated vehicles such as a connected car/drone, to capability-constrained devices such as a sensor/actuator. Although many efforts have been made within 5G cellular network in a bid to handle heterogeneous user terminals using a single radio access technology (RAT), it is undoubtable that the future network will not be governed by one RAT alone. Instead, multiple RATs will co-exist in the same area [1] to support connectivity of a multitude of devices with different requirements.

Thus, it is indeed plausible that a user device may be exposed to multiple RATs simultaneously in 5G networks and beyond. Apart from both macro cells and small cells of cellular RATs such as 4G and 5G, the user devices may potentially establish further connections with other RATs including WiFi. Moreover, IoT-oriented connectivity technologies including LoRA, ZigBee, and Bluetooth may also play crucial roles for future devices to report various types of sensor readings. Finally, the interfaces enabling direct communications between devices, including D2D, V2V, and ITS/DSRC, offer another way for the devices to sustain the connection to the network. Clearly, it is envisaged that the landscape of future radio access network will be comprised with diverse classes of user devices and co-existence of heterogenous RATs, as illustrated in Figure 1.

Based on such a foreseeable trend, it becomes necessary to address the interworking and cooperation amongst the multiple RATs co-existing in the same local service area. Such cooperation will obviously lead to improved overall network and spectrum efficiency. This is known as multi-RATs convergence, in which different RATs interwork for the sake of improving quality-of-services (QoS). Notable research and standardization activities have been conducted in the last decade to address multi-RATs convergence for both cellular and WiFi networks, but they often require significant changes in the specifications. This paper aims to introduce a new approach for multi-RATs convergence, which exploits the emerging paradigm of edge and fog computing, wherein context information from different RATs is collected, processed and offered as data services to help determine how best these RATs may cooperate to serve the various end users.

In the remainder of the paper, we will first review some existing schemes of multi-RATs convergence, as well as the arising concept of edge and fog computing for 5G. Then, we will delve into the details of the proposed solution of multi-RATs convergence via an integrated edge and fog system, which is essentially the concept pioneered by the 5G-CORAL project [2], a H2020 5G-PPP EU-Taiwan collaborative research project launched in 2017.

Fig 1 Various types of radio access technologies (RATs) may co-exist in the same service area to support diverse services and categories of devices

2. Review of Multi-RATs Convergence

Coordination between different RATs is not a particularly new notion. In general, the existing Multi-RATs convergence solutions can be classified into two categories, namely “intra-cellular convergence” and “cellular-WiFi convergence”.

The category of intra-cellular convergence is typically referred to the cases of interworking between different generations within the family of cellular networks, such as 2G, 3G, HSPA, LTE-A, and 5G. A most notable example is obviously the first version of 5G (3GPP Rel-15) approved recently, in which 5G New Radio (NR) operates in a non-standalone (NSA) fashion as it still relies on sharing the 4G core network (i.e. Evolved Packet Core or EPC) with a LTE-based RAT [3]. In such cases, the user device is simultaneously connected to 4G LTE and 5G NR, respectively handling control-plane signalling and partial (if not full) user-plane traffic. Alternatively, it is also envisioned that inter-working between 4G and 5G can be achieved by embedding LTE radio under a 5G core (5GC) network in a later phase of the 5G system rollout.

The category of Cellular-WiFi convergence, on the other hand, is relating to how cellular networks can coordinate with WiFi networks. Various types of cellular-WiFi coordination have been studied in different releases of 3GPP technologies. Notably, earlier efforts have been focused on interworking in the core network level, but the trend is gradually moving toward radio-level convergence in recent years. In particular, 3GPP has introduced LTE-WLAN Aggregation (LWA) [4], which permits WiFi access points to process and transmit some of the Packet Data Convergence Protocol (PDCP) PDUs on behalf of the LTE eNodeB. At the receiver side, the UE is able to reorder packets transmitted by LTE and WiFi, so the data throughput can be enhanced. Note that a LWA adaptation protocol (LWAAP) is needed to translate PDCP PDUs prior to further processing by WiFi radio.

3. Trend of Edge/Fog Computing

In order to support various types of applications requiring high data volume processing and storage, Cloud computing has been introduced by the IT industry and is already a commercial reality. The Cloud however is typically far away from the end-user devices, which clearly raises a challenge for latency-sensitive applications.

To complement the Cloud and address its shortcomings, there has been a recent trend to bring some computing power at the edge, thus closer to the end-users. The quintessential examples of “Edge” include data centres less sophisticated than the conventional Cloud, which are deployed typically in big cities near or jointly with RAN entities such as base stations or aggregation points. The ETSI standard body has been developing the framework of Mobile Edge Computing (MEC) [5] since 2012. MEC has been re-branded recently as Multi-Access Edge Computing [6] to reflect its potential for support of various types of access networks not just mobile communications.

The “Fog”, on the other hand, is a broader term that covers everything in the continuum between things and Cloud, as introduced by the OpenFog consortium [7]. Whilst by-definition Fog includes Edge, and all aggregations of the Edge towards the Cloud, the most appealing value of Fog has been in complementing the Edge by extending it further down to the very distributed computing substrate of volatile, mobile and constrained devices. This may include for example on-board computing hardware of cars or trains, PCs, smartphones, robots, drones, etc. It may also include servers attached to access points and small cell base stations.

These fog nodes can handle some lightweight but latency sensitive computational tasks. As compared to Cloud and Edge, wherein constant power supply and wired (cable or fibre) inter-connections are usually presumed, fog computing resources could be battery-powered mobile devices with more constrained capabilities that are wirelessly connected in most cases. Apparently, the mobility and volatile nature of fog devices make it more challenging if one tries to utilize their resources, which in turn leads to several new open problems requiring further research.

4. 5G-CORAL: A Project Overview

Based on the above review and trends, we make the following three observations: (1) Multiple RATs (not only cellular and WiFi) will co-exist in 5G; (2) The scope of Multi-RATs convergence has so far been mostly focused on cellular and WiFi integration; and (3) Edge/Fog computing will be pervasive deep into the access including on end-user terminals.

Following on these observations, we envision a new way of tackling multi-RATs convergence by (1) creating a unified system consolidating all the networking, computing and storage resources in the Edge and Fog; and (2) enabling all the RATs in the coverage area of that Edge and Fog system to provide their data services; and (3) enabling applications and functions wherever they run to consume instantly these multi-RAT data services in order to optimize performance.

Such a vision represents a new way of interworking between RATs based on context information sharing. This complements the conventional approach of Intra-Cellular and Cellular-WiFi integration and harmonization. The 5G-PPP Project entitled “A 5G Convergent Virtualized Radio Access Network Living at the Edge”, or simply 5G-CORAL, has launched in 2017 with a goal to realize this new paradigm of Multi-RATs convergence through a unified Edge and Fog system. In this section, we outline the 5G-CORAL solution as developed so far, along with the proofs of concept and trials planned in the project.

4.1 Concept and Building Blocks
5G-CORAL targets to integrate networking, computing and storage resources in the Edge and Fog, thus forming a unified logical system in proximity to the end-users, while maintaining interactions with the distant tier of the Cloud. As illustrated in Figure 2, 5G-CORAL solution is comprised with two main building blocks, namely Edge/Fog System (EFS) and Orchestration & Control System (OCS). The details of these two building blocks are given below.

Edge/Fog System (EFS): The EFS is essentially a logical system that is first constructed by pooling and consolidating the edge and fog resources, and next by providing a Service Platform for exchange of data services, and last by hosting applications and functions that may consume these services and run on top of the Edge and Fog substrate. In general, EFS functions are computing tasks deployed or instantiated on behalf of the networking infrastructure for the sake of connectivity. Therefore, virtualized network functions (VNF) such as virtualized baseband units (vBBU), and network performance optimization algorithms such as multi-RATs management, are all belonging to the category of functions. On the other hand, applications are computing tasks deployed for the end-users or third-parties. User applications may include computation-demanding tasks such as augmented reality (AR) and virtual reality (VR), which can be offloaded to EFS by less-capable user devices. The third-party applications may be deployed by different verticals to provide services such as car collision avoidance or a gateway for internet-of-things (IoT). Finally, the service platform plays a critical role that allows applications and functions to share and exchange context information, based on certain publish-subscribe messaging protocols.
Orchestration and Control System (OCS): The main responsibility of an OCS is to coordinate the computing, storage, and networking resources that compose the EFS. In particular, the design of OCS is compliant to ETSI NFV standard, which comprises an orchestrator, a VNF manager, and a virtualization infrastructure manager (VIM).Basically, the OCS should discover available resources and integrate them to form an EFS. To stitch edge and fog resources pertaining to different physical entities together, it should monitor and measure the available resources persistently, in a bid to establish and control the inter-connectivity among the resources. The OCS is also in charge of managing applications and functions running on the EFS. Specifically, if these computing tasks in the EFS are composed via chaining among multiple entities, the connectivity among these entities should be controlled by the OCS. Moreover, the OCS should determine the placement and migration of EFS applications and functions, which is crucial due to the volatile nature of fog resources. Finally, the OCS may coordinate the interactions between EFS elements and any external entities (e.g. another EFS or applications running on non-EFS platforms).

Fig 2 A high-level illustration of 5G-CORAL solution

4.2 Testbed Scenarios
In order to showcase how 5G-CORAL solutions can fulfil 5G-KPIs in different use cases, the project has planned three different testbed scenarios with different levels of expected user mobility. Particularly, the proof-of-concepts trials will be conducted in this project in scenarios of shopping mall, connected cars, and high speed train, as shown in Figure 3. These scenarios correspond to low, medium, and high user mobility respectively.

• Shopping mall trial will showcase network and computing offloading in a multi-RAT environment with the active involvement of EFS and OCS. For instance, AR-based navigation will benefit from EFS services of localisation and multi-RAT context information. In addition, IoT gateway and AR applications will take advantage of the vicinity of computing resources for offloading heavy processing tasks from end user devices/sensors to the fog/edge while leveraging the low latency communication offered by 5G-CORAL. Additionally, robotic use cases in the shopping mall will also be examined, where the robots can be controlled and coordinated using intelligence hosted in the EFS, to perform certain tasks such as cleaning and merchandise moving, which may require real-time coordination among multiple robots. Such a scenario may involve multiple RATs including cellular, WiFi, and IoT-oriented connectivity.
• Connected car trial will showcase the specific latency-sensitive scenarios of car vicinity alert, or any other kind of alert which can be based on EFS localization service (i.e., based on GPS information). An additional scenario is the offloading of V2X and X2V computation-intensive applications (e.g., real-time surveillance, video analytics) to the EFS. Commercially available LTE connections do not offer the required latency for car safety applications. Therefore, ad-hoc small cells and associated network infrastructure will be leveraged to guarantee such latency requirements. The use cases in this scenario would include on-board infotainment and various connected-car safety applications.
• High-speed train trial will focus on the specific use case of mobility scenarios where massive signaling from frequent handovers are expected due to the large number of end users and sensors on-board the train. Therefore, local virtual MMEs will be deployed on the Fog as part of the EFS to cope with the huge amount of signaling envisioned at such a high-speed. Such computing devices are deployed on-board the train and can also be used to host some specific core functions, such as local breakouts, to enable the storage and consumption of content locally without the need of going through the train’s backhaul connection.

Fig 3 The three testbed scenarios planned in 5G-CORAL project.

5. Concluding Remarks

In this paper, we have reviewed some state-of-the-arts relating to multi-RATs convergence, and discussed the recent trend of Edge and Fog computing. Most importantly, we have introduced the key concept of 5G-CORAL project, which is a new paradigm of multi-RATs convergence framework leveraging on the pervasiveness of computing resources in the Edge and Fog tiers. Particularly, by allowing different RATs to offer context aware data services through a common integrated Edge and Fog system, a new dimension of multi-RAT convergence becomes possible leading to improved connectivity and spectrum efficiency in the local service area. It is worth pointing out that, such a multi-RATs convergence approach is complementary to the conventional approaches of protocol stack harmonization or gateway-based interworking. The newly proposed approach promises to reap the benefits of multi-RATs convergence in each local service area, thus customized bottom-up, leading to overall performance improvement across the wider deployment. This approach helps in fulfilling several of the 5G KPIs, including latency, reliability, area traffic capacity, spectrum efficiency, positioning accuracy, and mobility. These KPIs will be measured in real-world trials as planned in the 5G-CORAL project.

Acknowledgment

This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586).

References

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