Optimal Virtualized Inter-Tenant Resource Sharing for Device-to-Device Communications in 5G Networks

Device-to-Device (D2D) communication is expected to enable a number of new services and applications in future mobile networks and has attracted significant research interest over the last few years. Remarkably, little attention has been placed on the issue of D2D communication for users belonging to different operators. In this paper, we focus on this aspect for D2D users that belong to different tenants (virtual network operators), assuming virtualized and programmable future 5G wireless networks. Under the assumption of a cross-tenant orchestrator, we show that significant gains can be achieved in terms of network performance by optimizing resource sharing from the different tenants, i.e., slices of the substrate physical network topology. To this end, a sum-rate optimization framework is proposed for optimal sharing of the virtualized resources. Via a wide site of numerical investigations, we prove the efficacy of the proposed solution and the achievable gains compared to legacy approaches.Comment: 10 pages, 7 figure

Device association for RAN slicing based on hybrid federated deep reinforcement learning

Network slicing (NS) has been widely identified as a key architectural technology for 5G-and-beyond systems by supporting divergent requirements in a sustainable way. In radio access network (RAN) slicing, due to the device-base station (BS)-NS three layer association relationship, device association (including access control and handoff management) becomes an essential yet challenging issue. With the increasing concerns on stringent data security and device privacy, exploiting local resources to solve device association problem while enforcing data security and device privacy becomes attractive. Fortunately, recently emerging federated learning (FL), a distributed learning paradigm with data protection, provides an effective tool to address this type of issues in mobile networks. In this paper, we propose an efficient device association scheme for RAN slicing by exploiting a hybrid FL reinforcement learning (HDRL) framework, with the aim to improve network throughput while reducing handoff cost. In our proposed framework, individual smart devices train a local machine learning model based on local data and then send the model features to the serving BS/encrypted party for aggregation, so as to efficiently reduce bandwidth consumption for learning while enforcing data privacy. Specifically, we use deep reinforcement learning to train the local model on smart devices under a hybrid FL framework, where horizontal FL is employed for parameter aggregation on BS, while vertical FL is employed for NS/BS pair selection aggregation on the encrypted party. Numerical results show that the proposed HDRL scheme can achieve significant performance gain in terms of network throughput and communication efficiency incomparison with some state-of-the-art solutions

Network Slicing Based 5G and Future Mobile Networks: Mobility, Resource Management, and Challenges

5G networks are expected to be able to satisfy users' different QoS requirements. Network slicing is a promising technology for 5G networks to provide services tailored for users' specific QoS demands. Driven by the increased massive wireless data traffic from different application scenarios, efficient resource allocation schemes should be exploited to improve the flexibility of network resource allocation and capacity of 5G networks based on network slicing. Due to the diversity of 5G application scenarios, new mobility management schemes are greatly needed to guarantee seamless handover in network-slicing-based 5G systems. In this article, we introduce a logical architecture for network-slicing-based 5G systems, and present a scheme for managing mobility between different access networks, as well as a joint power and subchannel allocation scheme in spectrum-sharing two-tier systems based on network slicing, where both the co-tier interference and cross-tier interference are taken into account. Simulation results demonstrate that the proposed resource allocation scheme can flexibly allocate network resources between different slices in 5G systems. Finally, several open issues and challenges in network-slicing-based 5G networks are discussed, including network reconstruction, network slicing management, and cooperation with other 5G technologies

Resource slicing in virtual wireless networks: a survey

New architectural and design approaches for radio access networks have appeared with the introduction of network virtualization in the wireless domain. One of these approaches splits the wireless network infrastructure into isolated virtual slices under their own management, requirements, and characteristics. Despite the advances in wireless virtualization, there are still many open issues regarding the resource allocation and isolation of wireless slices. Because of the dynamics and shared nature of the wireless medium, guaranteeing that the traffic on one slice will not affect the traffic on the others has proven to be difficult. In this paper, we focus on the detailed definition of the problem, discussing its challenges. We also provide a review of existing works that deal with the problem, analyzing how new trends such as software defined networking and network function virtualization can assist in the slicing. We will finally describe some research challenges on this topic.Peer ReviewedPostprint (author's final draft

Progressive introduction of network softwarization in operational telecom networks: advances at architectural, service and transport levels

Technological paradigms such as Software Defined Networking, Network Function Virtualization and Network Slicing are altogether offering new ways of providing services. This process is widely known as Network Softwarization, where traditional operational networks adopt capabilities and mechanisms inherit form the computing world, such as programmability, virtualization and multi-tenancy. This adoption brings a number of challenges, both from the technological and operational perspectives. On the other hand, they provide an unprecedented flexibility opening opportunities to developing new services and new ways of exploiting and consuming telecom networks. This Thesis first overviews the implications of the progressive introduction of network softwarization in operational networks for later on detail some advances at different levels, namely architectural, service and transport levels. It is done through specific exemplary use cases and evolution scenarios, with the goal of illustrating both new possibilities and existing gaps for the ongoing transition towards an advanced future mode of operation. This is performed from the perspective of a telecom operator, paying special attention on how to integrate all these paradigms into operational networks for assisting on their evolution targeting new, more sophisticated service demands.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Eduardo Juan Jacob Taquet.- Secretario: Francisco Valera Pintor.- Vocal: Jorge López Vizcaín