Next Generation Wireless (5G and Unlicensed)

Multi-Access Edge Computing (5G & Wi-Fi)

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PROGRAM OVERVIEW

PROJECT LEADERS

PROJECT DESCRIPTION

Project information

WBA’s 5G Project identified the evolution of Mobile Edge Computing towards Multi-Access Edge Computing (MEC) to better reflect non-cellular operators’ requirements, including Wi-Fi.

MEC Computing provides an IT service environment and cloud-computing capabilities at the edge of the mobile network, within the Radio Access Network (RAN) and in close proximity to mobile subscribers. The aim is to reduce latency, ensure highly efficient network operation and service delivery, and offer an improved user experience.

WBA is taking the leading role to define a set of services for Wi-Fi and working with ETSI MEC ISG to ensure that the MEC APIs are suitable for supporting Wi-Fi use cases.

Outcomes / Target Audience

In this project,  WBA will include the analysis of the use cases that necessitate the exposure of radio network related information from Wi-Fi access networks, and possible definition of an RNIS API for supporting Wi-Fi use cases.  The industry will be benefited with the finding of issues associated with exposing and/or normalizing different delays and/or averaging algorithms  which will likely need cross industry analysis.

The scope of this project:

Focus on the a practical MEC objective and deliverable

WBA statement on the MEC arena, setting the scene for future work

Project to align with ETSI MEC to maximize its impact and deliverables

Keywords

5G, Wi-Fi, Wi-Fi Virtualization, API, Use Cases, RAN optimization, Multi access

Business objectives

  • Expand WBA actuation to new areas and take the lead in defining a set of services for Wi-Fi
  • Grow WBA members business and protect Wi-Fi propositions

MAIN AREAS COVERED

  • Include analysis of the use cases that necessitate the exposure of radio network related information from Wi-Fi access networks
  • Possible definition of an RNIS API for supporting Wi-Fi use cases
  • Issues associated with exposing and/or normalizing different delays and/or averaging algorithms will likely need cross industry analysis