Optimal and Approximation Algorithms for Joint Routing and Scheduling in Millimeter-Wave Cellular Networks

Millimeter-wave (mmWave) communication is a promising technology to cope with the exponential increase in 5G data traffic. Such networks typically require a very dense deployment of base stations. A subset of those, so-called macro base stations, feature high-bandwidth connection to the core network, while relay base stations are connected wirelessly. To reduce cost and increase flexibility, wireless backhauling is needed to connect both macro to relay as well as relay to relay base stations. The characteristics of mmWave communication mandates new paradigms for routing and scheduling. The paper investigates scheduling algorithms under different interference models. To showcase the scheduling methods, we study the maximum throughput fair scheduling problem. Yet the proposed algorithms can be easily extended to other problems. For a full-duplex network under the no interference model, we propose an efficient polynomial-time scheduling method, the {\em schedule-oriented optimization}. Further, we prove that the problem is NP-hard if we assume pairwise link interference model or half-duplex radios. Fractional weighted coloring based approximation algorithms are proposed for these NP-hard cases. Moreover, the approximation algorithm parallel data stream scheduling is proposed for the case of half-duplex network under the no interference model. It has better approximation ratio than the fractional weighted coloring based algorithms and even attains the optimal solution for the special case of uniform orthogonal backhaul networks.Comment: accepted for publish in the IEEE/ACM Transactions on Networkin

Optimal Meshing Degree Performance Analysis in a mmWave FWA 5G Network Deployment

Fifth-generation technologies have reached a stage where it is now feasible to consider deployments that extend beyond traditional public networks. Central to this process is the application of Fixed Wireless Access (FWA) in 5G Non-public Networks (NPNs) that can utilise a novel combination of radio technologies to deploy an infrastructure on top of 5G NR or entirely from scratch. However, the use of FWA backhaul faces many challenges in relation to the trade-offs for reduced costs and a relatively simple deployment. Specifically, the use of meshed deployments is critical as it provides resilience against a temporary loss of connectivity due to link errors. In this paper, we examine the use of meshing in a FWA backhaul to determine if an optimal trade-off exists between the deployment of more nodes/links to provide multiple paths to the nearest Point of Presence (POP) and the performance of the network. Using a real 5G NPN deployment as a basis, we have conducted a simulated analysis of increasing network densities to determine the optimal configuration. Our results show a clear advantage for meshing in general, but there is also a performance trade-off to consider between overall network throughput and stability

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

5G and beyond networks

This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications

Software-defined wireless transport networks for flexible mobile backhaul in 5G systems

Traditionally microwave backhaul has been configured and operated in a static manner by means of vendor specific management systems. This mode of operation will be difficult to adapt to the new challenges originated by 5G networks. New mechanisms for adaptation and flexibility are required also in this network segment. The usage of a signaled control plane solution (based on OpenFlow) will facilitate the operation and will provide means for automation of actions on the wireless transport network segment. In addition to that, a standard control plane helps to reach the multi-vendor approach reducing complexity and variety of current per-vendor operation. This paper presents the motivation for the introduction of programmability concepts in wireless transport networks and illustrate the applicability of such control plane with two relevant use cases for dynamically controlling wireless transport nodes in 5G networks. Extensions to OpenFlow protocol are also introduced for building Software Defined Wireless Transport Networks (SDWTNs).This research was (partially) funded by the Office of the Chief Scientist of the Israel Ministry of Economy under the Neptune generic research project (the Israeli consortium for network programming). This work has been also (partially) funded by the EU H2020 Xhaul Project (grant no. 671598)

Topology Management for Wireless Mesh Self-Organizing Mobile Backhauls

The mobile data consumption is increasing exponentially, creating demand for more capacity from the network. Cell densification with small cells, also known as Heterogeneous networks, is seen as a solution for the capacity problem. On the downside, this creates a problem for providing a cost-effective backhaul connection to these small cells. The Self-optimizing Wireless Mesh Network (SWMN) backhaul has been proposed as a backhaul solution for small cells. In SWMN, the nodes form a partial mesh topology, where routing and data transmission is based on pre-computed prioritized set of routes and link-schedules. Hence, an entity that handles topology management functionalities is required, which enables automatic network configuration, network monitoring, optimization and management. The main aim of this thesis is to verify the topology management functionalities. The work involved development of a simulator for creating test topology scenarios. Additionally, the task involved verifying the feasibility of functionalities in the proof-of-concept system

A Free Space Optic/Optical Wireless Communication: A Survey

The exponential demand for the next generation of services over free space optic and wireless optic communication is a necessity to approve new guidelines in this range. In this review article, we bring together an earlier study associated with these schemes to help us implement a multiple input/multiple output flexible platform for the next generation in an efficient manner. OWC/FSO is a complement clarification to radiofrequency technologies. Notably, they are providing various gains such as unrestricted authorizing, varied volume, essential safekeeping, and immunity to interference.

Resource management in future mobile networks: from millimetre-wave backhauls to airborne access networks

The next generation of mobile networks will connect vast numbers of devices and support services with diverse requirements. Enabling technologies such as millimetre-wave (mm-wave) backhauling and network slicing allow for increased wireless capacities and logical partitioning of physical deployments, yet introduce a number of challenges. These include among others the precise and rapid allocation of network resources among applications, elucidating the interactions between new mobile networking technology and widely used protocols, and the agile control of mobile infrastructure, to provide users with reliable wireless connectivity in extreme scenarios. This thesis presents several original contributions that address these challenges. In particular, I will first describe the design and evaluation of an airtime allocation and scheduling mechanism devised specifically for mm-wave backhauls, explicitly addressing inter-flow fairness and capturing the unique characteristics of mm-wave communications. Simulation results will demonstrate 5x throughput gains and a 5-fold improvement in fairness over recent mm-wave scheduling solutions. Second, I will introduce a utility optimisation framework targeting virtually sliced mm-wave backhauls that are shared by a number of applications with distinct requirements. Based on this framework, I will present a deep learning solution that can be trained within minutes, following which it computes rate allocations that match those obtained with state-of-the-art global optimisation algorithms. The proposed solution outperforms a baseline greedy approach by up to 62%, in terms of network utility, while running orders of magnitude faster. Third, the thesis investigates the behaviour of the Transport Control Protocol (TCP) in Long-Term Evolution (LTE) networks and discusses the implications of employing Radio Link Control (RLC) acknowledgements under different link qualities, on the performance of transport protocols. Fourth, I will introduce a reinforcement learning approach to optimising the performance of airborne cellular networks serving users in emergency settings, demonstrating rapid convergence (approx. 2.5 hours on a desktop machine) and a 5dB improvement of the median Signal-to-Noise-plus-Interference-Ratio (SINR) perceived by users, over a heuristic based benchmark solution. Finally, the thesis discusses promising future research directions that follow from the results obtained throughout this PhD project