Network softwarization is a major paradigm shift, which enables programmable and flexible system operation in challenging use cases. In the fifth-generation (5G) mobile networks, the more advanced scenarios envision transfer of high-rate mission-critical traffic. Achieving end-to-end reliability of these stringent sessions requires support from multiple radio access technologies and calls for dynamic orchestration of resources across both radio access and core network segments. Emerging 5G systems can already offer network slicing, multi-connectivity, and end-to-end quality provisioning mechanisms for critical data transfers within a single software-controlled network. Whereas these individual enablers are already in active development, a holistic perspective on how to construct a unified, service-ready system as well as understand the implications of critical traffic on serving other user sessions is not yet available. Against this background, this paper first introduces a softwarized 5G architecture for end-to-end reliability of the mission-critical traffic. Then, a mathematical framework is contributed to model the process of critical session transfers in a softwarized 5G access network, and the corresponding impact on other user sessions is quantified. Finally, a prototype hardware implementation is completed to investigate the practical effects of supporting mission-critical data in a softwarized 5G core network, as well as substantiate the key system design choices.

Splitting functionalities of radio access network (RAN) and cloudification of such functionalities is considered as one of the key enablers of the next generation mobile and wireless networking, i.e. 5G, and is often referred to as software-defined RAN, virtualized RAN or Cloud RAN. Defining the splitting point, and maintaining the tight interaction between different functionalities in the RAN is, however, critical. Success of such cloudification depends on the availability of high speed fronthaul, while high speed fronthauling is costly. In this paper we experiment splitting MAC and PHY layer with fronthauling through Ethernet that allows using commodity and low-cost industry standard equipment. We examine the effect of packetization on latency, and study the pros and cons of splitting MAC and PHY layer, within a hardware-based testbed.

Leveraging multiple simultaneous small cell connections is an emerging and promising solution to enhance session continuity in millimeter-wave (mmWave) cellular systems that suffer from frequent link interruptions due to blockage in ultra-dense urban deployments. However, the available performance benefits of feasible multi-connectivity strategies as well as the tentative service quality gains that they promise remain an open research question. Addressing it requires the development of a novel performance evaluation methodology, which should consider: 1) the intricacies of mmWave radio propagation in realistic urban environments; 2) the dynamic mmWave link blockage due to human mobility; and 3) the multi-connectivity network behavior to preserve session continuity. In this paper, we construct this much needed methodology by combining the methods from queuing theory, stochastic geometry, as well as ray-based and system-level simulations. With this integrated framework, both user- and network-centric performance indicators together with their underlying scaling laws can be quantified in representative mmWave scenarios. To ensure modeling accuracy, the components of our methodology are carefully cross verified and calibrated against the current considerations in the standards. Building on this, a thorough comparison of alternative multi-connectivity strategies is conducted, as this paper reveals that even simpler multi-connectivity schemes bring notable improvements to session-level mmWave operation in realistic environments. These findings may become an important reference point for subsequent standardization in this area.

Maintaining multiple wireless connections is a promising solution to boost capacity in fifth-generation (5G) networks, where user equipment is able to consume radio resources of several serving cells simultaneously and potentially aggregate bandwidth across all of them. The emerging dual connectivity paradigm can be regarded as an attractive access mechanism in dense heterogeneous 5G networks, where bandwidth sharing and cooperative techniques are evolving to meet the increased capacity requirements. Dual connectivity in the uplink remained highly controversial, since the user device has a limited power budget to share between two different access points, especially when located close to the cell edge. On the other hand, in an attempt to enhance the uplink communications performance, the concept of uplink and downlink decoupling has recently been introduced. Leveraging these latest developments, this paper significantly advances prior art by proposing and investigating the concept of flexible cell association in dual connectivity scenarios, where users are able to aggregate resources from more than one serving cell. In this setup, the preferred association policies for the uplink may differ from those for the downlink, thereby allowing for a truly decoupled access. With the use of stochastic geometry, the dual connectivity association regions for decoupled access are derived, and the resultant performance is evaluated in terms of capacity gains over the conventional downlink received power access policies.

Carrier Aggregation (CA) is one of the key features introduced in LTE Release 10 to achieve higher levels of throughput. Two or more component carriers (CCs) are aggregated and user equipments (UEs) simultaneously transmit in more than one. The use of non-contiguous resource allocation in the uplink (UL) implies higher peak to average power ratio, so power de-rating is essential to avoid inter-modulation distortion and adjacent channel leakage-power ratio. CC selection is a key radio resource management procedure by which the eNB assigns UEs to CCs. While most CC selection algorithms deal with downlink, existing literature lacks efforts on UL CA. Moreover the mechanism is determinant on the UL performance. Given the UE power limitation, different criteria must be used in each link. This work proposes a novel CC selection algorithm that distinguishes between power limited and non-power limited UEs. In particular it is proposed to introduce information on maximum power reduction in selection decisions. Besides, UEs are not directly rejected if they are power limited, an acceptance margin is defined. This contains information on throughput variations between the allocation in several or just one CCs. This novel approach is contrasted with other CC selection techniques. Results show cell edge throughput improvements and the benefit of allowing bandwidth aggregation in a subset of power limited users.