This paper presents a baseline roadmap for the evolution of 5G new radio over the next decade. Three timescales are considered, namely short-term (2022-ish), medium-term (2025-ish), and long-term (2030-ish). The evolution of the target key performance indicators (KPIs) is first analyzed by accounting for forecasts on the emerging use cases and their requirements, together with assumptions on the pace of technology advancements. The baseline roadmap is derived next by capturing the top-10 and next the top-5 technology trends envisioned to bring significant added value at each timescale. Being intrinsically predictive, our proposed baseline roadmap cannot assert with certainty the values of the target KPIs and the shortlisting of the technology trends. It is, however, aimed at driving discussions and collecting feedback from the wireless research community for future tuning and refinement as the 5G evolution journey progresses.

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The plethora of wireless devices resulting in a humongous data usage has already pushed the current mobile networks to their limit. Therefore the research and development of the next generation mobile network must take place now. In this regard a mobile network operator has a pivotal role in understanding the required performance of the coming fifth generation network, and also influencing its final design. This paper presents some network research topics seen from an operator's point of view. It provides an overview of some recent results within the following areas: network architecture utilizing network function virtualization and software defined networks, performance of deploying self-organized network functions, spectrum sharing, inter-cell interference reduction methods, and backhaul with gigabit radio links.

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Different methods for network-based mobile positioning were compared experimentally. The Cell-id and TA method provided limited accuracy, the uncertainty ranging from 500 m to 3000 m for the median, dependant on area type. This could be reduced up to 25% by using alternative radii based on observations in the "doughnut" shaped prediction area. The Planning tool method improved the accuracy by approximately 30-50 % compared to this in urban area. The Forced handover method provided the best overall performance. In rural area the improvement was approximately 40-55 % compared to Cell-id and TA.