Role of satellite communications in 5G ecosystem: perspectives and challenges

The next generation of mobile radio communication systems – so-called 5G – will provide some major changes to those generations to date. The ability to cope with huge increases in data traffic at reduced latencies and improved quality of user experience together with a major reduction in energy usage are big challenges. In addition, future systems will need to embody connections to billions of objects – the so-called Internet of Things (IoT) which raises new challenges.Visions of 5G are now available from regions across the world and research is ongoing towards new standards. The consensus is a flatter architecture that adds a dense network of small cells operating in the millimetre wave bands and which are adaptable and software controlled. But what is the place for satellites in such a vision? The chapter examines several potential roles for satellites in 5G including coverage extension, IoT, providing resilience, content caching and multi-cast, and the integrated architecture. Furthermore, the recent advances in satellite communications together with the challenges associated with the use of satellite in the integrated satellite-terrestrial architecture are also discussed

Backhaul-Aware Dimensioning and Planning of Millimeter-Wave Small Cell Networks

The massive deployment of Small Cells (SCs) is increasingly being adopted by mobile operators to face the exponentially growing traffic demand. Using the millimeter-wave (mmWave) band in the access and backhaul networks will be key to provide the capacity that meets such demand. However, dimensioning and planning have become complex tasks, because the capacity requirements for mmWave links can significantly vary with the SC location. In this work, we address the problem of SC planning considering the backhaul constraints, assuming that a line-of-sight (LOS) between the nodes is required to reliably support the traffic demand. Such a LOS condition reduces the set of potential site locations. Simulation results show that, under certain conditions, the proposed algorithm is effective in finding solutions and strongly efficient in computational cost when compared to exhaustive search approaches.H2020 research and innovation project 5G-CLARITY 871428Spanish Ministry of Science, Innovation and Universities PID2019-108713RB-C5

Max-Min Fair Resource Allocation in Millimetre-Wave Backhauls

5G mobile networks are expected to provide pervasive high speed wireless connectivity, to support increasingly resource intensive user applications. Network hyper-densification therefore becomes necessary, though connecting to the Internet tens of thousands of base stations is non-trivial, especially in urban scenarios where optical fibre is difficult and costly to deploy. The millimetre wave (mm-wave) spectrum is a promising candidate for inexpensive multi-Gbps wireless backhauling, but exploiting this band for effective multi-hop data communications is challenging. In particular, resource allocation and scheduling of very narrow transmission/ reception beams requires to overcome terminal deafness and link blockage problems, while managing fairness issues that arise when flows encounter dissimilar competition and traverse different numbers of links with heterogeneous quality. In this paper, we propose WiHaul, an airtime allocation and scheduling mechanism that overcomes these challenges specific to multi-hop mm-wave networks, guarantees max-min fairness among traffic flows, and ensures the overall available backhaul resources are fully utilised. We evaluate the proposed WiHaul scheme over a broad range of practical network conditions, and demonstrate up to 5 times individual throughput gains and a fivefold improvement in terms of measurable fairness, over recent mm-wave scheduling solutions

Optimizing total cost of ownership (TCO) for 5G multi-tenant mobile backhaul (MBH) optical transport networks

Legacy network elements are reaching end-of-life and packet-based transport networks are not efficiently optimized. In particular, high density cell architecture in future 5G networks will face big technical and financial challenges due to avalanche of traffic volume and massive growth in connected devices. Raising density and ever-increasing traffic demand within future 5G Heterogeneous Networks (HetNets) will result in huge deployment, expansion and operating costs for upcoming Mobile BackHaul (MBH) networks with flat revenue generation. Thus, the goal of this dissertation is to provide an efficient physical network planning mechanism and an optimized resource engineering tool in order to reduce the Total Cost of Ownership (TCO) and increase the generated revenues. This will help Service Providers (SPs) and Mobile Network Operators (MNOs) to improve their network scalability and maintain positive Project Profit Margins (PPM). In order to meet this goal, three key issues are required to be addressed in our framework and are summarized as follows: i) how to design and migrate to a scalable and reliable MBH network in an optimal cost?, ii) how to control the deployment and activation of the network resources in such MBH based on required traffic demand in an efficient and cost-effective way?, and iii) how to enhance the resource sharing in such network and maximize the profit margins in an efficient way? As part of our contributions to address the first issue highlighted above and to plan the MBH with reduced network TCO and improved scalability, we propose a comprehensive migration plan towards an End-to-End Integrated-Optical-Packet-Network (E2-IOPN) for SP optical transport networks. We review various empirical challenges faced by a real SP during the transformation process towards E2-IOPN as well as the implementation of an as-built plan and a high-level design (HLD) for migrating towards lower cost-per-bit GPON, MPLS-TP, OTN and next-generation DWDM technologies. Then, we propose a longer-term strategy based on SDN and NFV approach that will offer rapid end-to-end service provisioning with costefficient centralized network control. We define CapEx and OpEx cost models and drive a cost comparative study that shows the benefit and financial impact of introducing new low-cost packet-based technologies to carry traffic from legacy and new services. To address the second issue, we first introduce an algorithm based on a stochastic geometry model (Voronoi Tessellation) to more precisely define MBH zones within a geographical area and more accurately calculate required traffic demands and related MBH infrastructure. In order to optimize the deployment and activation of the network resources in the MBH in an efficient and cost-effective way, we propose a novel method called BackHauling-as-a-Service (BHaaS) for network planning and Total Cost of Ownership (TCO) analysis based on required traffic demand and a "You-pay-only-for-what-you-use" approach. Furthermore, we enhance BHaaS performance by introducing a more service-aware method called Traffic-Profile-asa- Service (TPaaS) to further drive down the costs based on yearly activated traffic profiles. Results show that BHaaS and TPaaS may enhance by 22% the project benefit compared to traditional TCO model. Finally, we introduce a new cost (CapEx and OpEx) models for 5G multi-tenant Virtualized MBH (V-MBH) as part of our contribution to address the third issue. In fact, in order to enhance the resource sharing and maximize the network profits, we drive a novel pay-as-yougrow and optimization model for the V-MBH called Virtual-Backhaul-as-a-Service (VBaaS). VBaaS can serve as a planning tool to optimize the Project Profit Margin (PPM) while considering the TCO and the yearly generated Return-on-Investment (ROI). We formulate an MNO Pricing Game (MPG) for TCO optimization to calculate the optimal Pareto-Equilibrium pricing strategy for offered Tenant Service Instances (TSI). Then, we compare CapEx, OpEx, TCO, ROI and PPM for a specific use-case known in the industry as CORD project using Traditional MBH (T-MBH) versus Virtualized MBH (V-MBH) as well as using randomized versus Pareto-Equilibrium pricing strategies. The results of our framework offer SPs and MNOs a more precise estimation of traffic demand, an optimized infrastructure planning and yearly resource deployment as well as an optimized TCO analysis (CapEx and OpEx) with enhanced pricing strategy and generated ROI. Numerical results show more than three times increase in network profitability using our proposed solutions compared with Traditional MBH (T-MBH) methods

On Topology Optimization and Routing in Integrated Access and Backhaul Networks: A Genetic Algorithm-Based Approach

In this paper, we study the problem of topology optimization and routing in integrated access and backhaul (IAB) networks, as one of the promising techniques for evolving 5G networks. We study the problem from different perspectives. We develop efficient genetic algorithm-based schemes for both IAB node placement and non-IAB backhaul link distribution, and evaluate the effect of routing on bypassing temporal blockages. Here, concentrating on millimeter wave-based communications, we study the service coverage probability, defined as the probability of the event that the user equipments\u27 (UEs) minimum rate requirements are satisfied. Moreover, we study the effect of different parameters such as the antenna gain, blockage, and tree foliage on the system performance. Finally, we summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on routing in IAB networks, and discuss the main challenges for enabling mesh-based IAB networks. As we show, with a proper network topology, IAB is an attractive approach to enable the network densification required by 5G and beyond