Quality of Service and prioritisation for emergency services in the LTE RAN stack

Project Information

Q4HEALTH

Grant agreement ID: 688624

DOI

10.3030/688624

Project closed

EC signature date 21 October 2015

Start date 1 January 2016

End date 28 February 2018

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Total cost

€ 855 037,00

EU contribution

€ 728 176,00

Coordinated by

REDZINC SERVICES LIMITED
Ireland

Periodic Reporting for period 2 - Q4HEALTH (Quality of Service and prioritisation for emergency services in the LTE RAN stack)

Reporting period: 2017-01-01 to 2018-02-28

Summary of the context and overall objectives of the project

The Q4HEALTH project is an innovation action in the Horizon 2020 program focused on the optimization of real time video for emergency services over LTE. The project is implemented as a set of experiments conducted over the Future Internet Research and Experimentation platforms PerformNetworks and OpenAirInterface. The motivation is to study video performance in scenarios with wearable live video for first responders, improving its response with a particular innovation focus on 3GPP release 12 and future 5G technologies.

Q4HEALTH faces different challenges: the inability of applications to negotiate a QoS agreement with the network, the delays introduced on live video, the appropriate scheduling algorithms on the access nodes, the service availability on indoor scenarios and the communication between geographically correlated entities.

These challenges are approached from different perspectives: on one hand the application will be optimized following the market trends, on the other the different experimental platforms will be extended to provide proof of concept of future 5G communications. This approaches are followed in all the components of the network, the base stations will be extended to support application aware LTE MAC schedulers, several APIs will be implemented in the EPC to provide access to QoS enforcement functionality as well as to enable low latency and optimized multicast communications following the edge computing and SDN paradigms. On the UE side the optimization process will be applied to select the most appropriate antennas as well the optimal UE for the given video application.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

There are six experiments defined for the project. Three experiments for the evolved packet core, two experiments for the radio side and one integrated experiment. During the first year of the project the main work has been setting up the testbed for the experiments and obtaining baseline measurements. Two additional experiments have also been defined targeting the UE evaluation and the battery life analysis.
From the point of view of the wearable video prototypes were built using breadboard components and tested. These included wearable Internet of Things processor, 4G LTE modem and long life battery in a package which can be mounted on the belt of the paramedic in addition there is a point of view camera connected to safety glasses worn by the paramedic. The system was deployed to the Malaga testbed and tested. Subsequently a printed circuit board version was built tested and deployed to the Malaga testbed.

A virtual path slice engine has been deployed to the Malaga testbed to support network slicing. Two levels of slicing are supported. Radio bearer slicing and slicing of the distribution network.
Several activities around the latency reduction techniques have been carried out. Three different designs have been provided covering the provision of fog communications with and without data plane analysis. An engine to create a S1 user database have been implemented and a prototype of one of the fog computing solutions based on data plane solutions is being developed.

To support the evaluation of the different UEs as well as of the proposed solutions the team has developed several tools that provide statistics of the signalling procedures as well as of the time split of the data plane. Two different UEs have been evaluated using the LTE/LTE-A emulators as well as channel emulators to introduce impairments on the uplink.

We also consider the Enabling of Programmability in the eNodeB using the SDN design paradigm. In the eNodeB side, OAI now provides the FlexRAN framework which is the first open-source SD-RAN platform. FlexRAN incorporates an API to separate control and data planes that is tailored for the mobile RAN. FlexRAN controller design and implementation factors in the need to make real-time RAN control applications feasible.

The FlexRAN framework is responsible for the dynamic on demand adjustment of the eNodeB MAC scheduling, in order to give the necessary priorities to the users. In the devised approach we exploit virtualization of the of the physical resource blocks (VRB), by adding an abstraction layer.

All these entities harmonically operate in order to realize the scheduling principle that will eventually satisfy the QCI as established for the VELOX bearers. Various comparison of off the shelf modems and printed 4G antennas were subjected to a range of performance tests.

Work on dissemination has been also carried out covering meetings with potential stakeholders and scientific publications in congress, journals and books.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The Q4HEALTH project experiments are motivated to study video performance in a scenario where immersive wearable live video assists first responders in public safety applications such as an ambulance paramedic attending to patient. During the ‘golden hour’ after the incident, pre-hospital actions taken are crucial and potentially lifesaving. “Eyes on’ live video from the first responder to the hospital or clinical oversight centre can help make more rapid decision. Medical policy makers are considering how to harness advances in ICT to enhance patient care and outcome. Responding to eHealth market demands, RedZinc, an SME, has developed an interactive wearable video platform for ambulances and paramedics. The platform enables emergency doctors located in the hospital to remotely see a pre-hospital patient with acute medical conditions and to provide additional treatment capability for that patient. During the ‘golden hour’ rapid diagnosis and earlier treatment has the potential to enhance patient outcome (e.g. more rapid delivery of clot busting drugs).

The PerformNetworks testbed is being upgrade during the project in order to support advanced 5G prototypes supporting QoS slicing, low latency communications and multicast communications. The latency reduction prototypes are fully compatible with standard LTE networks, aim to provide a unique playground for testing commercial platforms in future 5G environments, and also where to evaluate fog computing services. The slicing is provided by the use of the Rx interface by external applications. Multicast communications are being explored using SDN technologies.

The main difference with the classical 4G architecture is the way we enable in the OAI system virtualization of the of the physical resource blocks (VRB) and allow for allocation of VRBs per different tenant (in our case the normal users and the VELOX users). This is achieved by adding an abstraction layer, which acts as an interface between the shared Physical Resource Block (PRB) and the tenant -specific Resource mapper (SRM). The resource mapping exposes information to each SRM regarding buffer status in both Uplink and Downlink for each logical channels and users. In the current status we implemented a downlink UE scheduler for the agent-side that supports the dynamic introduction of new tenant to the RAN and the on-demand modification of the scheduling policy per operator. This is a major innovation towards building programmable ran elements and to the best of our knowledge is the first open-source offering.
All the activities carried out in the project can help to assess how these experimental platforms can enhance readiness for market applications.

Q4Health Experiments

Q4Health Experiments

Q4Health Innovation Ecosystem Impact

Q4Health Scenario with Wearable Video