Browsing by Author "Hellaoui, Hamed"

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Aerial Control System for Spectrum Efficiency in UAV-to-Cellular Communications
(2018-10-01) Hellaoui, Hamed; Bekkouche, Oussama; Bagaa, Miloud; Taleb, Tarik
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The next generation of mobile systems, 5G, will be the communication standard that accommodates the proliferation of the Internet of Things (IoT). Unmanned aerial vehicles (UAVs) are envisioned to support many applications in providing 5G connectivity to the IoT, by extending highspeed connectivity from the sky to objects on the ground, or even by carrying onboard some IoT devices. However, given their critical nature, the management of UAVs induces high exchange of control messages with the ground control station, resulting in the crowded spectrum used by cellular networks. The authors raise the problem of degrading the network spectrum with UAVs' management messages, and discuss the need for an efficient orchestration system. In this article, they propose a novel scheme, dubbed the aerial control system, which is based on separating the data plane from the control plane of UAVs, and pushing the latter to be performed in the air by UAVs. The solution provides an orchestration logic that takes advantage of the autonomous nature of UAVs to organize UAVs in one or several clusters. UAV-to-UAV communication enables spectrum reuse and avoids crowding the network with management messages, while dedicating more 5G spectrum for ensuring more bandwidth to the IoT through UAV-to-infrastructure communication.
Ahead-Me Coverage (AMC): On Maintaining Enhanced Mobile Network Coverage for UAVs
(2023-01-11) Hellaoui, Hamed; Yang, Bin; Taleb, Tarik; Manner, Jukka
A4 Artikkeli konferenssijulkaisussa
This paper proposes the concept of Ahead-Me Cov-erage (AMC) aiming to get the coverage of a cellular network ahead of the mobile users for maintaining enhanced Quality- of-Service (QoS) in cellular-connected unmanned aerial vehicle (UAV) networks. In such networks, each base station (BS) with an intelligent logic can automatically tilt the direction of its radio antennas based on the trajectory of UAV s. For this purpose, we first formulate AMC as an integer optimization problem for maximizing the minimum transmission rate of UAVs by jointly optimizing the angles of the different radio antenna, the resource allocation and the selection of the appropriate serving BS for the UAVs throughout their path. For this complex optimization problem, we then propose a solution based on Deep Reinforcement Learning (DRL) to solve it. Under this solution, we adopt a multi-heterogeneous agent-based approach (MHA-DRL) including two types of agents, namely the UAV agents and the BS agents. Each agent implements an Advantage Actor Critic (A2C) to learn optimal policies. Specifically, the BS agents aim to tilt their antennas to get ahead of the UAV s throughout their mobility, and the UAV agents target selecting the appropriate serving BSs along with resource allocation. Performance evaluations are presented to validate the effectiveness of the proposed approach.
Efficient Steering Mechanism for Mobile Network-enabled UAVs
(2019) Hellaoui, Hamed; Chelli, Ali; Bagaa, Miloud; Taleb, Tarik
A4 Artikkeli konferenssijulkaisussa
The consideration of mobile networks as a communication infrastructure for unmanned aerial vehicles (UAVs)creates a new plethora of emerging services and opportunities.In particular, the availability of different mobile network operators (MNOs) can be exploited by the UAVs to steer connection tothe MNO ensuring the best quality of experience (QoE). While the concept of traffic steering is more known at the networkside, extending it to the device level would allow meeting theemerging requirements of today’s applications. In this vein, an efficient steering solutions that take into account the nature and the characteristics of this new type of communication is highly needed. The authors introduce, in this paper, a mechanism for steering the connection in mobile network-enabled UAVs. The proposed solution considers a realistic communication model that accounts for most of the propagation phenomena experienced by wireless signals. Moreover, given the complexity of the related optimization problem, which is inherent from this realistic model, the authors propose a solution based on coalitional game. The goal is to form UAVs in coalitions around the MNOs, in a way to enhance their QoE. The conducted performance evaluations show the potential of using several MNOs to enhance the QoE for mobile network-enabled UAVs and prove the effectiveness of the proposed solution.
Energy Efficiency in Security of 5G-Based IoT: An End-to-End Adaptive Approach
(2020-07) Hellaoui, Hamed; Koudil, Mouloud; Bouabdallah, Abdelmadjid
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The challenging problem of energy efficiency in security of the Internet of Things (IoT) is tackled in this article. The authors consider the upcoming generation of mobile networks, 5G, as a communication architecture for the IoT. The concept of adaptive security is adopted, which is based on adjusting the security level as per the changing context. It has the potential of reducing energy consumption by adapting security rather than always considering the worst case, which is energy consuming. The consideration of 5G introduces new dynamics that can be exploited to perform more adaptation. The proposed solution introduces an intelligence in the application of security, from the establishment phase to the use phase (end-to-end). The security level related to the used cryptographic algorithm/key is adapted for each node during the establishment phase, so to match with the duration of the provided services. A new strategy is formulated that considers both IoT and 5G characteristics. In addition, a solution based on the framework of the coalitional game is proposed in order to associate the deployed objects with the optimized security levels. Moreover, the application of security is also adapted during the use phase according to the threat level. Trust management is used to evaluate the threat level among the network nodes, while existing works focus on performing the adaptation during the use phase. The proposed approach achieves more adaptation through the consideration of both IoT and 5G dynamics. The analysis and performance evaluations are conducted to show the effectiveness of the proposed end-to-end approach.
Enhancing the Performance of UAV Communications in Cellular Networks
(2022) Hellaoui, Hamed
School of Electrical Engineering | Doctoral dissertation (article-based)
The use of cellular networks as a communication infrastructure for Unmanned Aerial Vehicles (UAVs) has become the current trend. This would mainly enable beyond visual line-of-sight applications and allow UAVs to benefit from the latest evolutions achieved in cellular networks.Despite the advantages that cellular networks can bring to UAVs, several issues still need to be addressed. Indeed, cellular networks are deployed to serve ground user equipment (UEs), whereas UAVs' aerial communications are characterized by different channel conditions. Field evaluations have shown that flying UAVs can experience poor link quality, or even negatively affect ground communication. In addition, UAV applications can be deployed in a challenging environment characterized by different types of QoS (Quality of Services). For instance, UAVs can be deployed to provide network connectivity to ground devices, whereas each one of the latter requires sending two types of traffics with different QoS, at the same time. Furthermore, the consideration of cellular networks for UAVs can bring more opportunities that merit to be explored to enhance the communications, mainly in terms of taking advantage of the presence of several UAVs and Mobile Network Operators (MNOs). The main objective of the dissertation is to contribute to enhancing the performance of UAV communications in cellular networks. The contributions of this dissertation can be divided into six categories. First, as aerial communication presents different channel conditions, we are interested in modeling UAV communications in cellular networks and deriving expressions that define the performance indicators. All the contributions build from these expressions, and target performing network optimization to enhance UAV communications in cellular networks. Second, we consider a cellular network deployed to serve both UEs and UAVs, and we investigate their co-existence by enhancing their underlying performances. Next, we focus on supporting the co-existence of several QoS types in UAV communications. To this end, we consider the scenario where UAVs are deployed to provide network connectivity to ground devices, where each one of the latter requires two different QoS types. In the fourth and the fifth categories, we focus on new opportunities that cellular networks can bring to UAV communications. In particular, we investigate the possibility of taking advantage of the presence of several UAVs and MNOs in a way to enhance the performance of UAV communications. Finally, we explore the use of machine learning in order to enable fast optimization and enhance the performance of UAV communications. All the contributions of this dissertation have been validated with a series of performance evaluations.
Generative AI for Immersive Communication : The Next Frontier in Internet-of-Senses Through 6G
(2024-10-23) Sehad, Nassim; Bariah, Lina; Hamidouche, Wassim; Hellaoui, Hamed; Jantti, Riku; Debbah, Merouane
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Over the past two decades, the Internet-of-things (IoT) has become a transformative concept, and as we approach 2030, a new paradigm known as the Internet of senses (IoS) is emerging. Unlike conventional virtual reality (VR), IoS seeks to provide multi-sensory experiences, acknowledging that in our physical reality, our perception extends far beyond just sight and sound; it encompasses a range of senses. This article explores the existing technologies driving immersive multi-sensory media, delving into their capabilities and potential applications. This exploration includes a comparative analysis between conventional immersive media streaming and a proposed use case that leverages semantic communication empowered by generative artificial intelligence (AI). The focal point of this analysis is the substantial reduction in bandwidth consumption by 99.93% in the proposed scheme. Through this comparison, we aim to underscore the practical applications of generative AI for immersive media. Concurrently addressing major challenges in this field, such as temporal synchronization of multiple media, ensuring high throughput, minimizing the end-to-end (E2E) latency, and robustness to low bandwidth while outlining future trajectories.
Joint Sub-carrier and Power Allocation for Efficient Communication of Cellular UAVs
(2020-12) Hellaoui, Hamed; Bagaa, Miloud; Chelli, Ali; Taleb, Tarik
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Cellular networks are expected to be the main communication infrastructure to support the expanding applications of Unmanned Aerial Vehicles (UAVs). As these networks are deployed to serve ground User Equipment (UEs), several issues need to be addressed to enhance cellular UAVs’ services. In this paper, we propose a realistic communication model on the downlink, and we show that the Quality of Service (QoS) for the users is affected by the number of interfering BSs and the impact they cause. The joint problem of sub-carrier and power allocation is therefore addressed. Given its complexity, which is known to be NP-hard, we introduce a solution based on game theory. First, we argue that separating between UAVs and UEs in terms of the assigned sub-carriers reduces the interference impact on the users. This is materialized through a matching game. Moreover, in order to boost the partition, we propose a coalitional game that considers the outcome of the first one and enables users to change their coalitions and enhance their QoS. Furthermore, a power optimization solution is introduced, which is considered in the two games. Performance evaluations are conducted, and the obtained results demonstrate the effectiveness of the propositions.
On Supporting Multiservices in UAV-Enabled Aerial Communication for Internet of Things
(2023-08-01) Hellaoui, Hamed; Bagaa, Miloud; Chelli, Ali; Taleb, Tarik; Yang, Bin
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Multiservices are of fundamental importance in unmanned aerial vehicle (UAV)-enabled aerial communications for the Internet of Things (IoT). However, the multiservices are challenging in terms of requirements and use of shared resources such that the traditional solutions for a single service are unsuitable for the multiservices. In this article, we consider a UAV-enabled aerial access network for ground IoT devices, each of which requires two types of services, namely, ultrareliable low-latency communication (uRLLC) and enhanced mobile broadband (eMBB), measured by transmission delay and effective rate, respectively. We first consider a communication model that accounts for most of the propagation phenomena experienced by wireless signals. Then, we derive the expressions of the effective rate and the transmission delay, and formulate each service type as an optimization problem with the constraints of resource allocation and UAV deployment to enable multiservice support for the IoT. These two optimization problems are nonlinear and nonconvex and are generally difficult to be solved. To this end, we transform them into linear optimization problems, and propose two iterative algorithms to solve them. Based on them, we further propose a linear program algorithm to jointly optimize the two service types, which achieves a tradeoff of the effective rate and the transmission delay. Extensive performance evaluations have been conducted to demonstrate the effectiveness of the proposed approach in reaching a tradeoff optimization that enhances the two services.
On Supporting UAV Based Services in 5G and beyond Mobile Systems
(2021-07-05) Taleb, Tarik; Ksentini, Adlen; Hellaoui, Hamed; Bekkouche, Oussama
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
While Unmanned Aerial Vehicles (UAVs) are expected to introduce disruptive innovations in our society, it is foreseen that the used communication technology is the key factor that can unlock their potential. To this end, the upcoming generation of mobile networks, 5G-and-beyond, are envisioned to be the communication standards to support diverse UAV applications. This will also enable UAVs to benefit from the limitless progress achieved in mobile systems. To facilitate the support of UAV services in 5G-and-beyond networks, this article introduces a framework that links the mobile telecommunication domain to the UAV domain. The proposed framework reflects an operational view enabling UAV operators to prepare and deploy their applications over different 5G mobile telecommunication networks. Moreover, the framework allows UAV operators to customize mobile systems in accordance with the specifications of their target services and to constantly receive analytical and statistical data on their running applications. Furthermore, in order to ensure network services (dedicated to UAV applications) over heterogeneous mobile systems, this article also discusses the federation of 5G networks.
Orchestration and Performance Evaluation of 5G-based Drone Applications
(2023-01-23) Amir, Ahmad
Sähkötekniikan korkeakoulu | Master's thesis
5G has seen unprecedented growth in recent times. Its features are paving the way for new opportunities, and Network slicing is one of them. Slicing enables virtualization across the entire provider network architecture to create on-demand network slices that meet service requirements. Because of network slices, new verticals are deployed on top of 5G networks. One such vertical that is gaining popularity because of its use cases is 5G drones. The 5G-based drone application runs on a container orchestration platform while the UAV is connected to the 5G network. Remote management of UAV applications running on top of a 5G network is challenging. Monitoring KPIs related to the cloud and 5G network in near real-time will facilitate the management of UAV applications running in a network slice. In this thesis, we deployed a monitoring stack comprising Prometheus, Zabbix, and ELK stack to monitor, store and visualize KPIs. Prometheus collects metrics from an application deployed on Kubernetes, while Zabbix gathers metrics from the 5G network parallelly in near-real time. The monitoring stack successfully gathers and visualizes the KPIs of a 5G-based drone application for remote management. The deployed monitoring stack will provide insight to a service provider and drone players.
Seamless Replacement of UAV-BSs Providing Connectivity to the IoT
(2023-01-11) Hellaoui, Hamed; Yang, Bin; Taleb, Tarik; Manner, Jukka
A4 Artikkeli konferenssijulkaisussa
This paper considers the scenario of Unmanned Aerial Vehicles (UAVs) acting as flying base stations (UAV-BSs) to provide network connectivity to ground Internet of Things (IoT) devices. More precisely, we investigate the issue where a UAV-BS needs to be replaced by a new one in a seamless way. First, we formulate the issue as an optimization problem aiming to maximize the minimum transmission rate of the served IoT devices during the UAV-BS replacement process. This is translated into jointly optimizing the trajectory of the source UAV-BS (the one to be replaced) and the target UAV-BS (the replacing one), while pushing the IoT devices to seamlessly transfer their connections to the target UAV-BS. We therefore consider a target replacement zone where the UAV-BS replacement can happen, along with IoT connections transfer. Furthermore, we propose a solution based on Deep Reinforcement Learning (DRL). More precisely, we introduce a Multi-Heterogeneous Agent-based approach (MHA-DRL), where two types of agents are considered, namely the UAV-BS agents and the IoT agents. Each agent implements a DQN (Deep Q-Learning) algorithm, where UAV-BS agents learn optimal policies to perform replacement while IoT agents learn optimal policies to transfer their connections to the target UAV-BS. The conducted performance evaluations show that the proposed approach can achieve near optimal optimization.
Supporting Unmanned Aerial Vehicle Services in 5G Networks: New High-Level Architecture Integrating 5G With U-Space
(2021-03) Si-Mohammed, Samir; Bouaziz, Maha; Hellaoui, Hamed; Bekkouche, Oussama; Ksentini, Adlen; Taleb, Tarik; Tomaszewski, Lechoslaw; Lutz, Thomas; Srinivasan, Gokul; Jarvet, Tanel; Montowtt, Orange
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
To provide efficient, safe, and secure access to the airspace, the European Union has launched a set of new services called U-space that allow for the support of unmanned aerial vehicle (UAV) management and conflict prevention for flights in the airspace. These services are based on communication technology, which is expected to be the key enabler to unlock the underlying potential of UAV operations. In this regard, the 5G mobile network is envisioned to be the communication standard to support diverse UAV operations and applications. In this article, we propose a novel architecture that integrates 5G systems (5GSs) with U-space. The main aim consists of providing a reference design that demonstrates how 5G can support U-space services and shows the interactions among different stakeholders. Further, we introduce the 5G!Drones project, which relies on the proposed architecture to test UAV use-case scenarios on top of the 5G infrastructure.
Towards Efficient Control of Mobile Network-Enabled UAVs
(2019-04-01) Hellaoui, Hamed; Chelli, Ali; Bagaa, Miloud; Taleb, Tarik; Patzold, Matthias
A4 Artikkeli konferenssijulkaisussa
The efficient control of mobile network-enabled unmanned aerial vehicles (UAVs) is targeted in this paper. In particular, a downlink scenario is considered, in which control messages are sent to UAVs via cellular base stations (BSs). Unlike terrestrial user equipment (UEs), UAVs perceive a large number of BSs, which can lead to increased interference causing poor or even unacceptable throughput. This paper proposes a framework for efficient control of UAVs. First, a communication model is introduced for flying UAVs taking into account interference, path loss and fast fading. The characteristics of UAVs make such model different compared to traditional ones. Thereafter, in order to ensure the efficient control, a solution is proposed for reducing interference. This is achieved by efficiently assigning sub-carriers to the UAVs in a way to reduce interference. A maximum independent set formulation is proposed along with an algorithm for optimal sub-carrier allocation. The obtained results demonstrate the efficiency of the proposed solution in terms of enhancing the link quality of UAVs.
Towards Mitigating the Impact of UAVs on Cellular Communications
(2018) Hellaoui, Hamed; Chelli, Ali; Bagaa, Miloud; Taleb, Tarik
A4 Artikkeli konferenssijulkaisussa
The next generation of Unmanned Aerial Vehicles (UAVs) will rely on mobile networks as a communication infrastructure. Several issues need to be addressed to enable the expected potentials from this communication. In particular, it was demonstrated that flying UAVs perceive a high number of base stations (BSs), consequently causing more interferences on non-serving BSs. This unfortunately results in decreased throughput for ground user equipments (UEs) already connected. Such a problem could be a limiting factor for mobile network-enabled UAVs, due to its consequences on the quality of experience (QoE) of served UEs. This underpins the focus of this article, wherein the effect of UAVs' communication on ground UEs in the uplink scenario is studied. First, given the fact that the nature of flying UAVs introduces particularities that make the underlying communication models different from traditional ones, this work proposes a model for mobile network-enabled UAVs (considering interferences, path loss, and fast fading). Moreover, we also tackle the QoE issue and propose an optimization solution based on adjusting the transmission power of UAVs. Simulations are conducted to evaluate the mobile network performance in the presence of flying UAVs. Our results reveal that as the number of added UAVs increases, a significant increase in the outage is observed. We demonstrate that our power optimization strategy guarantees the QoE for UEs, offers good communication links for UAVs, and reduces the overall interference in the network.
Towards using Deep Reinforcement Learning for Connection Steering in Cellular UAVs
(2021) Hellaoui, Hamed; Yang, Bin; Taleb, Tarik
A4 Artikkeli konferenssijulkaisussa
This paper investigates the fundamental connection steering issue in cellular-enabled Unmanned Aerial Vehicles (UAVs), whereby a UAV steers the cellular connection across multiple Mobile Network Operators (MNOs) for ensuring enhanced Quality-of-Service (QoS). We first formulate the issue as an optimization problem for minimizing the maximum outage probability. This is a nonlinear and nonconvex problem that is generally difficult to be solved. To this end, we propose a new approach for solving the optimization problem based on Deep Reinforcement Learning (DRL), considering two important reinforcement learning algorithms (i.e., Deep Q-Learning (DQN) and Advantage Actor Critic (A2C)). Simulation results show that under the proposed approach, the UAVs can make optimal decisions to select the most suitable connection with MNOs for achieving the minimization of the maximum outage probability. Furthermore, the results also show that in our new approach, the A2C-based algorithm is better than the DQN-based one, especially when the number of MNOs increases, while the DQN-based algorithm can be executed in a shorter time.
Traffic Steering for Cellular-Enabled UAVs: A Federated Deep Reinforcement Learning Approach
(2023) Hellaoui, Hamed; Yang, Bin; Taleb, Tarik; Manner, Jukka
A4 Artikkeli konferenssijulkaisussa
This paper investigates the fundamental traffic steering issue for cellular-enabled unmanned aerial vehicles (UAVs), where each UAV needs to select one from different Mobile Network Operators (MNOs) to steer its traffic for improving the Quality-of-Service (QoS). To this end, we first formulate the issue as an optimization problem aiming to minimize the maximum outage probabilities of the UAVs. This problem is non-convex and non-linear, which is generally difficult to be solved. We propose a solution based on the framework of deep reinforcement learning (DRL) to solve it, in which we define the environment and the agent elements. Furthermore, to avoid sharing the learned experiences by the UAV in this solution, we further propose a federated deep reinforcement learning (FDRL)-based solution. Specifically, each UAV serves as a distributed agent to train separate model, and is then communicated to a special agent (dubbed coordinator) to aggregate all training models. Moreover, to optimize the aggregation process, we also introduce a FDRL with DRL-based aggregation (DRL2A) approach, in which the coordinator implements a DRL algorithm to learn optimal parameters of the aggregation. We consider deep Q-learning (DQN) algorithm for the distributed agents and Advantage Actor-Critic (A2C) for the coordinator. Simulation results are presented to validate the effectiveness of the proposed approach.
UAV Communication Strategies in the Next Generation of Mobile Networks
(2020-06) Hellaoui, Hamed; Chelli, Ali; Bagaa, Miloud; Taleb, Tarik
A4 Artikkeli konferenssijulkaisussa
The Next Generation of Mobile Networks (NGMN) alliance advocates the use of different means to support vehicular communications. This aims to cope with the massive data generated by these devices which could affect the Quality of Service (QoS) of the associated applications, but also the overall operation carried out by the vehicles. However, efficient communication strategies must be considered in order to select, for each vehicle, the communication mean ensuring the best QoS. In this paper, we tackle this issue and we propose efficient communication strategies for Unmanned Aerial Vehicles (UAVs). In addition to direct UAV-to-Infrastructure communications (U2I), we also consider UAV-to-UAV scheme (U2U) to transmit data via relay UAVs. The goal is to select for each UAV the best communication strategy and the relay node to maximize the spectral efficiency. The expressions of the effective rate are derived for the different strategies and the problem is formulated using linear programming. Performance evaluations are conducted and the obtained results demonstrate the effectiveness of the proposed solution.