Towards a flexible harmonised 5G air interface with multi-service, multi-connectivity support

Current 4G air interfaces (AIs), by which we mean existing and emerging cellular and WLAN standards, lack the flexibility required for support of multiple and diverse services envisaged for 5G (such as Massive Machine-Type Communications mMTC, Ultra-reliable Machine-Type Communications uMTC, and Extreme Mobile Broadband xMBB), with their diverging and sometimes conflicting requirements. Evolutions of 4G AIs might meet the KPIs of individual 5G services, but not the key 5G requirement to natively integrate multi service support. The evolutionary alternative would hence result in the deployment of multiple 4G AI evolutions, leading to a very heterogeneous system a mix of different RATs (Radio Access Technologies). As an illustration, when a single user has device(s) supporting multiple services, the different service data flows diverge at a very high level of the protocol stack, resulting in the need to rely on inter RAT handover. This increases latency, implementation complexity and signalling load in the network, and results in potential loss of coordination and efficiency. With ambitious 5G goals for support of services with different (and often diverging) requirements, a highly flexible 5G air interface design will be required to answer this demand. One way to solve these issues is to harmonize the air interface variants with the goal to find an optimal compromise between potentially highly specialized solutions for specific services, and the broader goal to only have one air interface supporting multiple services. This paper will describe the approach adopted by EU H2020 5G PPP project METIS II for a harmonized 5G AI and its impact on protocol stack level. In particular, we will: Show how AIs in currently deployed networks do not meet many of the 5G performance requirements, such as multi-connectivity, support for a wide range of frequencies, and multi-service support; Elaborate the concept of harmonisation of different AIs towards a common user plane design and capture our key design principles; Present the most promising set of AI variants with respect to identified KPIs and identify potential AI variants to be integrated in the 5G system; and Perform an initial analysis of harmonisation possibilities.