The paper elaborates on the technological and architectural innovations researched and developed by 5G-PPP Phase 1 projects and covering innovation areas such as 5G system design and evaluation, novel air interfaces, network management and security as well as virtualization and service deployment aspects.

Communication networks are undergoing their next evolutionary step toward 5G. The 5G networks are envisioned to provide a flexible, scalable, agile, and programmable network platform over which different services with varying requirements can be deployed and managed within strict performance bounds. In order to address these challenges, a paradigm shift is taking place in the technologies that drive the networks, and thus their architecture. Innovative concepts and techniques are being developed to power the next generation mobile networks. At the heart of this development lie Network Function Virtualization and Software Defined Networking technologies, which are now recognized as being two of the key technology enablers for realizing 5G networks, and which have introduced a major change in the way network services are deployed and operated. For interested readers that are new to the field of SDN and NFV, this paper provides an overview of both these technologies with reference to the 5G networks. Most importantly, it describes how the two technologies complement each other and how they are expected to drive the networks of near future.

In this paper we present results from an extensive measurement study of various hardware and (virtualized) software routers using several queueing strategies, i.e. First-Come-First-Served and Fair Queueing. In addition to well-known metrics such as packet forwarding performance, per packet processing time, and jitter, we apply network calculus models for performance analysis. This includes the Guaranteed Rate model for Integrated Services as well as the Packet Scale Rate Guarantee model for Differentiated Services. Using a measurement approach that provides a means to estimate rate and error term of a real node, we propose an interpretation of router performance based on these parameters taking packet queueing and scheduling into account. Such estimated parameters should be used to make the analysis of real networks more accurate. We underpin the applicability of this approach by comparing analytical results of concatenated routers to real world measurements.

The distributed coordination function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on quality of service in mind. In this paper we provide an accurate model for the fairness of the DCF. Given M greedy stations we assume fairness if a tagged station contributes a share of 1/M to the overall number of packets transmitted. We derive the probability distribution of fairness deviations and support our analytical results by an extensive set of measurements. We find a closed-form expression for the improvement of long-term over short-term fairness. Regarding the random countdown values we quantify the significance of their distribution whereas we discover that fairness is largely insensitive to the distribution parameters. Based on our findings we view the DCF as emulating an ideal fair queuing system to quantify the deviations from a fair rate allocation. We deduce a stochastic service curve model for the DCF to predict packet delays in IEEE 802.11. We show how a station can estimate its fair bandwidth share from passive measurements of its traffic arrivals and departures.