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See detailQuantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, Sayed Junaid; Sharma, Shree Krishna UL; Wyne, Shurjeel et al

in IEEE Access (2019)

The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully ... [more ▼]

The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully-intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the 6th Generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performanceandservicetypes.Theincreasinglystringentperformancerequirementsofemergingnetworks may finally trigger the deployment of some interesting new technologies such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications and cell-free communications – tonameafew.Ourvisionfor6Gis–amassivelyconnectedcomplexnetworkcapableofrapidlyresponding to the users’ service calls through real-time learning of the network state as described by the network-edge (e.g., base-station locations, cache contents, etc.), air interface (e.g., radio spectrum, propagation channel, etc.), and the user-side (e.g., battery-life, locations, etc.). The multi-state, multi-dimensional nature of the network state, requiring real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of Machine Learning (ML), Quantum Computing (QC), and Quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensivereviewoftherelatedstate-of-the-artinthedomainsofML(includingdeeplearning),QCand QML, and identify their potential benefits, issues and use cases for their applications in the B5G networks. Subsequently,weproposeanovelQC-assistedandQML-basedframeworkfor6Gcommunicationnetworks whilearticulatingitschallengesandpotentialenablingtechnologiesatthenetwork-infrastructure,networkedge, air interface and user-end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed. [less ▲]

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See detailFPGA Acceleration for Computationally Efficient Symbol-Level Precoding in Multi-User Multi-Antenna Communication Systems
Krivochiza, Jevgenij UL; Merlano Duncan, Juan Carlos UL; Andrenacci, Stefano UL et al

in IEEE Access (2019)

In this paper, we demonstrate an FPGA accelerated design of the computationally efficient Symbol-Level Precoding (SLP) for high-throughput communication systems. The SLP technique recalculates optimal ... [more ▼]

In this paper, we demonstrate an FPGA accelerated design of the computationally efficient Symbol-Level Precoding (SLP) for high-throughput communication systems. The SLP technique recalculates optimal beam-forming vectors by solving a non-negative least squares (NNLS) problem per every set of transmitted symbols. It exploits the advantages of constructive inter-user interference to minimize the total transmitted power and increase service availability. The benefits of using SLP come with a substantially increased computational load at a gateway. The FPGA design enables the SLP technique to perform in realtime operation mode and provide a high symbol throughput for multiple receive terminals. We define the SLP technique in a closed-form algorithmic expression and translate it to Hardware Description Language (HDL) and build an optimized HDL core for an FPGA. We evaluate the FPGA resource occupation, which is required for high throughput multiple-input-multiple-output (MIMO) systems with sizeable dimensions. We describe the algorithmic code, the I/O ports mapping and the functional behavior of the HDL core. We deploy the IP core to an actual FPGA unit and benchmark the energy efficiency performance of SLP. The synthetic tests demonstrate a fair energy efficiency improvement of the proposed closed-form algorithm, also compared to the best results obtained through MATLAB numerical simulations. [less ▲]

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See detailOn the Application of Directional Antennas in Multi-Tier Unmanned Aerial Vehicle Networks
Zhang, J.; Xu, H.; Xiang, Lin UL et al

in IEEE Access (2019), 7

This paper evaluates the performance of downlink information transmission in three-dimensional (3D) unmanned aerial vehicle (UAV) networks, where multi-tier UAVs of different types and flying altitudes ... [more ▼]

This paper evaluates the performance of downlink information transmission in three-dimensional (3D) unmanned aerial vehicle (UAV) networks, where multi-tier UAVs of different types and flying altitudes employ directional antennas for communication with ground user equipments (UEs). We introduce a novel tractable antenna gain model, which is a nonlinear function of the elevation angle and the directivity factor, for directional antenna-based UAV communication. Since the transmission range of a UAV is limited by its antenna gain and the receiving threshold of the UEs, only UAVs located in a finite region in each tier can successfully communicate with the UEs. The communication connectivity, association probability as well as coverage probability of the considered multi-tier UAV networks are derived for both line-of-sight (LoS) and non-line-of-sight (NLoS) propagation scenarios. Our analytical results unveil that, for UAV networks employing directional antennas, a necessary tradeoff between connectivity and coverage probability exists. Consequently, UAVs flying at low altitudes require a large elevation angle in order to successfully serve the ground UEs. Moreover, by employing directional antennas an optimal directivity factor exists for maximizing the coverage probability of the multi-tier UAV networks. Simulation results validate the analytical derivations and suggest the application of high-gain directional antennas to improve downlink transmission in the multi-tier UAV networks. [less ▲]

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See detailAn Uplink UE Group-Based Scheduling Technique for 5G mMTC Systems Over LEO Satellite
Kodheli, Oltjon UL; Andrenacci, Stefano; Maturo, Nicola UL et al

in IEEE Access (2019)

Narrowband Internet of Things (NB-IoT) is one of the most promising IoT technology to support the massive machine-type communication (mMTC) scenarios of the fifth generation mobile communication (5G ... [more ▼]

Narrowband Internet of Things (NB-IoT) is one of the most promising IoT technology to support the massive machine-type communication (mMTC) scenarios of the fifth generation mobile communication (5G). While the aim of this technology is to provide global coverage to the low-cost IoT devices distributed all over the globe, the vital role of satellites to complement and extend the terrestrial IoT network in remote or under-served areas has been recognized. In the context of having the global IoT networks, low earth (LEO) orbits would be beneficial due to their smaller propagation signal loss, which for the low complexity, low power, and cheap IoT devices is of utmost importance to close the link-budget. However, while this would lessen the problem of large delay and signal loss in the geostationary (GEO) orbit, it would come up with increased Doppler effects. In this paper, we propose an uplink scheduling technique for a LEO satellite-based mMTC NB-IoT system, able to mitigate the level of the differential Doppler down to a value tolerable by the IoT devices. The performance of the proposed strategy is validated through numerical simulations and the achievable data rates of the considered scenario are shown, in order to emphasize the limitations of such systems coming from the presence of a satellite channel. [less ▲]

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See detailSDR Implementation of a Testbed for Real-Time Interference Detection with Signal Cancellation
Politis, Christos; Maleki, Sina UL; Merlano Duncan, Juan Carlos UL et al

in IEEE Access (2018)

Interference greatly affects the quality of service of wireless and satellite communications, having also a financial impact for the telecommunication operators. Therefore, as the interfering events ... [more ▼]

Interference greatly affects the quality of service of wireless and satellite communications, having also a financial impact for the telecommunication operators. Therefore, as the interfering events increase due to the deployment of new services, there is an increasing demand for the detection and mitigation of interference. There are several interference detectors in the literature, evaluated by using extensive simulations. However, this paper goes one step further, designing, implementing and evaluating the performance of the developed interference detection algorithms experimentally using a software defined radio, and particularly the universal software radio peripheral platform. A realistic communication system is implemented, consisting of a transmitter, a channel emulator and a receiver. Based on this system, we implement all the appropriate communications features such as pulse shaping, synchronization and demodulation. The real-time system implementation is validated and evaluated through signal and interference detection. We observe that the interference detection threshold is critical to the functioning of the system. Several existing interference detection techniques fail in practice due to this fact. In this paper, we propose a robust and practically implementable method the selection of threshold. Finally, we present real-time experimental results for the probabilities of false alarm and detection in order to verify the accuracy of our study and reinforce our theoretical analysis. [less ▲]

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See detailIntelligent Gaming for Mobile Crowd-Sensing Participants to Acquire Trustworthy Big Data in the Internet of Things
Pouryazdan, Maryam; Fiandrino, Claudio; Kantarci, Burak et al

in IEEE Access (2017), 5

In mobile crowd-sensing systems, the value of crowd-sensed big data can be increased by incentivizing the users appropriately. Since data acquisition is participatory, crowd-sensing systems face the ... [more ▼]

In mobile crowd-sensing systems, the value of crowd-sensed big data can be increased by incentivizing the users appropriately. Since data acquisition is participatory, crowd-sensing systems face the challenge of data trustworthiness and truthfulness assurance in the presence of adversaries whose motivation can be either manipulating sensed data or collaborating unfaithfully with the motivation of maximizing their income. This paper proposes a game theoretic methodology to ensure trustworthiness in user recruitment in mobile crowd-sensing systems. The proposed methodology is a platform-centric framework that consists of three phases: user recruitment, collaborative decision making on trust scores, and badge rewarding. In the proposed framework, users are incentivized by running sub-game perfect equilibrium and gami cation techniques. Through simulations, we showthat approximately 50% and a minimum of 15% improvement can be achieved by the proposed methodology in terms of platform and user utility, respectively, when compared with fully distributed and user-centric trustworthy crowd-sensing. [less ▲]

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See detailJoint Beamforming and Power Optimization with Iterative User Clustering for MISO-NOMA Systems
Liu, Zhengxuan; Lei, Lei UL; Zhang, Ningbo et al

in IEEE Access (2017)

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See detailLive Data Analytics with Collaborative Edge and Cloud Processing in Wireless IoT Network
Sharma, Shree Krishna UL; Wang, Xianbin

in IEEE Access (2017)

Recently, big data analytics has received important attention in a variety of application domains including business, finance, space science, healthcare, telecommunication and Internet of Things (IoT ... [more ▼]

Recently, big data analytics has received important attention in a variety of application domains including business, finance, space science, healthcare, telecommunication and Internet of Things (IoT). Among these areas, IoT is considered as an important platform in bringing people, processes, data and things/objects together in order to enhance the quality of our everyday lives. However, the key challenges are how to effectively extract useful features from the massive amount of heterogeneous data generated by resource-constrained IoT devices in order to provide real-time information and feedback to the endusers, and how to utilize this data-aware intelligence in enhancing the performance of wireless IoT networks. Although there are parallel advances in cloud computing and edge computing for addressing some issues in data analytics, they have their own benefits and limitations. The convergence of these two computing paradigms, i.e., massive virtually shared pool of computing and storage resources from the cloud and real-time data processing by edge computing, could effectively enable live data analytics in wireless IoT networks. In this regard, we propose a novel framework for coordinated processing between edge and cloud computing/processing by integrating advantages from both the platforms. The proposed framework can exploit the network-wide knowledge and historical information available at the cloud center to guide edge computing units towards satisfying various performance requirements of heterogeneous wireless IoT networks. Starting with the main features, key enablers and the challenges of big data analytics, we provide various synergies and distinctions between cloud and edge processing. More importantly, we identify and describe the potential key enablers for the proposed edge-cloud collaborative framework, the associated key challenges and some interesting future research directions. [less ▲]

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See detailOpen IoT Ecosystem for Sporting Event Management
Kubler, Sylvain UL; Robert, Jérémy UL; Främling, Kary et al

in IEEE Access (2017), 5(1), 7064-7079

By connecting devices, people, vehicles, and infrastructures everywhere in a city, governments and their partners can improve community well-being and other economic and financial aspects (e.g., cost and ... [more ▼]

By connecting devices, people, vehicles, and infrastructures everywhere in a city, governments and their partners can improve community well-being and other economic and financial aspects (e.g., cost and energy savings). Nonetheless, smart cities are complex ecosystems that comprise many different stakeholders (network operators, managed service providers, logistic centers, and so on), who must work together to provide the best services and unlock the commercial potential of the so-called Internet of Things (IoT). This is one of the major challenges that faces today’s smart city movement, and the emerging "API economy." Indeed, while new smart connected objects hit the market every day, they mostly feed "vertical silos" (e.g., vertical apps, siloed apps, and so on) that are closed to the rest of the IoT, thus hampering developers to produce new added value across multiple platforms and/or application domains. Within this context, the contribution of this paper is twofold: 1) present the strategic vision and ambition of the EU to overcome this critical vertical silos’ issue and 2) introduce the first building blocks underlying an open IoT ecosystem developed as part of an EU (Horizon 2020) Project and a joint project initiative (IoT-EPI). The practicability of this ecosystem, along with a performance analysis, is carried out considering a proof-of-concept for enhanced sporting event management in the context of the forthcoming FIFA World Cup 2022 in Qatar. [less ▲]

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See detailCrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments
Fiandrino, Claudio UL; Capponi, Andrea UL; Cacciatore, Giuseppe UL et al

in IEEE Access (2017)

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the ... [more ▼]

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic) and we present its applicability using a smart public street lighting scenario. [less ▲]

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See detailSelf-Powered Two-Way Cognitive Relay Networks: Protocol Design and Performance Analysis
Nguyen; Jayakody; Chatzinotas, Symeon UL et al

in IEEE Access (2017)

Detailed reference viewed: 45 (3 UL)