A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks

The densification of small-cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small-cell base stations. This involves efficient association and placement of the backhaul hubs that connects these small-cells with the core network. Terrestrial hubs suffer from an inefficient non line of sight link limitations and unavailability of a proper infrastructure in an urban area. Seeing the popularity of flying platforms, we employ here an idea of using networked flying platform (NFP) such as unmanned aerial vehicles (UAVs), drones, unmanned balloons flying at different altitudes, as aerial backhaul hubs. The association problem of these NFP-hubs and small-cell base stations is formulated considering backhaul link and NFP related limitations such as maximum number of supported links and bandwidth. Then, this paper presents an efficient and distributed solution of the designed problem, which performs a greedy search in order to maximize the sum rate of the overall network. A favorable performance is observed via a numerical comparison of our proposed method with optimal exhaustive search algorithm in terms of sum rate and run-time speed.Comment: Submitted to IEEE GLOBECOM 2017, 7 pages and 4 figure

Distributed drone base station positioning for emergency cellular networks using reinforcement learning

Due to the unpredictability of natural disasters, whenever a catastrophe happens, it is vital that not only emergency rescue teams are prepared, but also that there is a functional communication network infrastructure. Hence, in order to prevent additional losses of human lives, it is crucial that network operators are able to deploy an emergency infrastructure as fast as possible. In this sense, the deployment of an intelligent, mobile, and adaptable network, through the usage of drones—unmanned aerial vehicles—is being considered as one possible alternative for emergency situations. In this paper, an intelligent solution based on reinforcement learning is proposed in order to find the best position of multiple drone small cells (DSCs) in an emergency scenario. The proposed solution’s main goal is to maximize the amount of users covered by the system, while drones are limited by both backhaul and radio access network constraints. Results show that the proposed Q-learning solution largely outperforms all other approaches with respect to all metrics considered. Hence, intelligent DSCs are considered a good alternative in order to enable the rapid and efficient deployment of an emergency communication network

PaFiR : Particle Filter Routing – a predictive relaying scheme for UAV-assisted IoT communications in future innovated networks

Increasing urbanization, smart cities and other cutting-edge technologies offer the prospect of providing more functions to benefit citizens by relying on the substantial data processing and exchange capabilities now possible. This can generate significant unpredictable and unbalanced data loads for the bearing IoT network to support its application and service demands. We thus propose a wireless routing scheme designed to use the Particle Filter algorithm to empower portable smart devices with intelligent capacities for the radio communication system. This facilitates the offloading of traffic from traditional wireless networks and enables the IoT system to adopt unmanned aerial vehicles, thus also offering further innovation to flying network platforms. The proposed PaFiR routing protocol offers the network more scalability, tolerance and resilience, to achieve the goal of smart relaying. Simulation results that demonstrate the routing algorithm designed offers excellent performance when compared with existing wireless relaying schemes. It provides delivery ratios that are improved by up to 40% without unmanageable increases in latency or overheads

Association of networked flying platforms with small cells for network centric 5G+ C-RAN

5G+ systems expect enhancement in data rate and coverage area under limited power constraint. Such requirements can be fulfilled by the densification of small cells (SCs). However, a major challenge is the management of fronthaul links connected with an ultra dense network of SCs. A cost effective and scalable idea of using network flying platforms (NFPs) is employed here, where the NFPs are used as fronthaul hubs that connect the SCs to the core network. The association problem of NFPs and SCs is formulated considering a number of practical constraints such as backhaul data rate limit, maximum supported links and bandwidth by NFPs and quality of service requirement of the system. The network centric case of the system is considered that aims to maximize the number of associated SCs without any biasing, i.e., no preference for high priority SCs. Then, two new efficient greedy algorithms are designed to solve the presented association problem. Numerical results show a favorable performance of our proposed methods in comparison to exhaustive search.Comment: Submitted to IEEE PIMRC 2017, 7 pages and 5 figure

A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G Innovations, and Experimental Advancements

As an emerging field of aerial robotics, Unmanned Aerial Vehicles (UAVs) have gained significant research interest within the wireless networking research community. As soon as national legislations allow UAVs to fly autonomously, we will see swarms of UAV populating the sky of our smart cities to accomplish different missions: parcel delivery, infrastructure monitoring, event filming, surveillance, tracking, etc. The UAV ecosystem can benefit from existing 5G/B5G cellular networks, which can be exploited in different ways to enhance UAV communications. Because of the inherent characteristics of UAV pertaining to flexible mobility in 3D space, autonomous operation and intelligent placement, these smart devices cater to wide range of wireless applications and use cases. This work aims at presenting an in-depth exploration of integration synergies between 5G/B5G cellular systems and UAV technology, where the UAV is integrated as a new aerial User Equipment (UE) to existing cellular networks. In this integration, the UAVs perform the role of flying users within cellular coverage, thus they are termed as cellular-connected UAVs (a.k.a. UAV-UE, drone-UE, 5G-connected drone, or aerial user). The main focus of this work is to present an extensive study of integration challenges along with key 5G/B5G technological innovations and ongoing efforts in design prototyping and field trials corroborating cellular-connected UAVs. This study highlights recent progress updates with respect to 3GPP standardization and emphasizes socio-economic concerns that must be accounted before successful adoption of this promising technology. Various open problems paving the path to future research opportunities are also discussed.Comment: 30 pages, 18 figures, 9 tables, 102 references, journal submissio

A Speculative Study on 6G

While 5G is being tested worldwide and anticipated to be rolled out gradually in 2019, researchers around the world are beginning to turn their attention to what 6G might be in 10+ years time, and there are already initiatives in various countries focusing on the research of possible 6G technologies. This article aims to extend the vision of 5G to more ambitious scenarios in a more distant future and speculates on the visionary technologies that could provide the step changes needed for enabling 6G.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version mayno longer be accessibl

Flying mobile edge computing towards 5G and beyond: an overview on current use cases and challenges

The increasing computational capacity of multiple devices, the advent of complex applications, and data generation create new challenges of scalability, ubiquity, and seamless services to meet the most diverse network demands and requirements, such as reliability, latency, battery lifetime. For this reason, the 5th Generation (5G) network comes to mitigate the most diverse challenges inherent to the current dynamic mobile networks and their increasing data rates. Unmanned Aerial Vehicles (UAVs) have also been considered as communication relays or mobile base stations to assist mobile users with limited or no available wireless infrastructure. They can provide connections for mobile users in hard-to-reach areas, replacing damaged or overloaded ground infrastructure and working as mobile clouds, providing low but increasing computational power. However, the feasibility of a Flying Edge Computing requires special attention in terms of resource allocation techniques, cooperation with existing ground units and among multiple UAVs, coordination with user mobility, computation efficiency, collision avoidance, and recharging approaches. Thus, the cooperation among UAVs and the current terrestrial Mobile Edge Computing can be relevant in some cases once the computation power of a single UAV might be insufficient. It is important to understand the feasibility of current proposals and establish new approaches that consider the usage of multiple UAVs and recharging approaches. In this paper we discuss the challenges of a 5G extended network through the help of UAVs. The proposed multi-tier architecture employs UAVs with different mobility models, providing support to ground nodes. Moreover, the support of the UAVs as edge nodes will also be evaluated.publishe