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Showing results 101 to 120 of 673
   Machine Learning for Radio Resource Management in Multibeam GEO Satellite SystemsOrtiz Gomez, Flor de Guadalupe  ; Lei, Lei ; Lagunas, Eva et alin Electronics (2022), 11(7), 992 Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and ... [more ▼] Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and changes in traffic demand diurnal. This problem is addressed by using flexible payload architectures, which allow payload resources to be flexibly allocated to meet the traffic demand of each beam. While optimization-based radio resource management (RRM) has shown significant performance gains, its intense computational complexity limits its practical implementation in real systems. In this paper, we discuss the architecture, implementation and applications of Machine Learning (ML) for resource management in multibeam GEO satellite systems. We mainly focus on two systems, one with power, bandwidth, and/or beamwidth flexibility, and the second with time flexibility, i.e., beam hopping. We analyze and compare different ML techniques that have been proposed for these architectures, emphasizing the use of Supervised Learning (SL) and Reinforcement Learning (RL). To this end, we define whether training should be conducted online or offline based on the characteristics and requirements of each proposed ML technique and discuss the most appropriate system architecture and the advantages and disadvantages of each approach. [less ▲] Detailed reference viewed: 80 (17 UL)Defeating Super-Reactive Jammers WithDeception Strategy: Modeling, SignalDetection, and Performance Analysis; ; et al in IEEE Transactions on Wireless Communications (2022), 21(9), 7374-7390 This paper aims to develop a novel framework to defeat a super-reactive jammer, one of the mostdifficult jamming attacks to deal with in practice. Specifically, the jammer has an unlimited power budgetand ... [more ▼] This paper aims to develop a novel framework to defeat a super-reactive jammer, one of the mostdifficult jamming attacks to deal with in practice. Specifically, the jammer has an unlimited power budgetand is equipped with the self-interference suppression capability to simultaneously attack and listen tothe transmitter’s activities. Consequently, dealing with super-reactive jammers is very challenging. Thus,we introduce a smart deception mechanism to attract the jammer to continuously attack the channel andthen leverage jamming signals to transmit data based on the ambient backscatter communication whichis resilient to radio interference/jamming. To decode the backscattered signals, the maximum likelihood(ML) detector can be adopted. However, the method is notorious for its high computational complexityand require a specific mathematical model for the communication system. Hence, we propose a deeplearning-based detector that can dynamically adapt to any channel and noise distributions. With the LongShort-Term Memory network, our detector can learn the received signals’ dependencies to achieve theperformance close to that of the optimal ML detector. Through simulation and theoretical results, wedemonstrate that with proposed approaches, the more power the jammer uses to attack the channel, thebetter bit error rate performance we can achieve [less ▲] Detailed reference viewed: 14 (3 UL)Bayesian Poisson Factorization with SideInformation for User Interest Prediction inHierarchical Edge-Caching Systems; Chatzinotas, Symeon in IEEE Open Journal of the Communications Society (2022), 3 Edge-caching is an effective solution to cope withthe unprecedented data traffic growth by storing contents inthe vicinity of end-users. In this paper, we formulate a hier-archical caching policy where ... [more ▼] Edge-caching is an effective solution to cope withthe unprecedented data traffic growth by storing contents inthe vicinity of end-users. In this paper, we formulate a hier-archical caching policy where the end-users and cellular basestation (BS) are equipped with limited cache capacity with theobjective of minimizing the total data traffic load in the network.The caching policy is a nonlinear combinatorial programmingproblem and difficult to solve. To tackle the issue, we design aheuristic algorithm as an approximate solution which can besolved efficiently. Moreover, to proactively serve the users, itis of high importance to extract useful information from datarequests and predict user interest about contents. In practice,the data often containimplicit feedbackfrom users which isquite noisy and complicates the reliable prediction of userinterest. In this regard, we introduce a Bayesian Poisson matrixfactorization model which utilizes the available side informationabout contents to effectively filter out the noise in the data andprovide accurate prediction. Subsequently, we design an efficientMarkov chain Monte Carlo (MCMC) method to perform theposterior approximation. Finally, a real-world dataset is appliedto the proposed proactive caching-prediction scheme and ourresults show significant improvement over several commonly-used methods. For example, when the BS and the users havecaches with storage of25%and10%of the total contents sizerespectively, our approach yields around8%improvement withrespect to the state-of-the-art approach in terms of cachingperformance. [less ▲] Detailed reference viewed: 12 (0 UL)Refracting RIS-Aided Hybrid Satellite-Terrestrial Relay Networks: Joint Beamforming Design and Optimization; ; et al in IEEE Transactions on Aerospace and Electronic Systems (2022) Reconfigurable intelligent surface (RIS) has been viewed as a promising solution in constructing reconfigurable radio environment of the propagation channel and boosting the received signal power by ... [more ▼] Reconfigurable intelligent surface (RIS) has been viewed as a promising solution in constructing reconfigurable radio environment of the propagation channel and boosting the received signal power by smartly coordinating the passive elements’ phase shifts at the RIS. Inspired by this emerging technique, this article focuses on joint beamforming design and optimization for RIS-aided hybrid satellite-terrestrial relay networks, where the links from the satellite and base station (BS) to multiple users are blocked. Specifically, a refracting RIS cooperates with a BS, where the latter operates as a half-duplex decode-and-forward relay, in order to strengthen the desired satellite signals at the blocked users. Considering the limited onboard power resource, the design objective is to minimize the total transmit power of both the satellite and BS while guaranteeing the rate requirements of users. Since the optimized beamforming weight vectors at the satellite and BS, and phase shifters at the RIS are coupled, leading to a mathematically intractable optimization problem, we propose an alternating optimization scheme by utilizing singular value decomposition and uplink–downlink duality to optimize beamforming weight vectors, and using Taylor expansion and penalty function methods to optimize phase shifters iteratively. Finally, simulation results are provided to verify the superiority of the proposed scheme compared to the benchmark schemes [less ▲] Detailed reference viewed: 18 (0 UL)Ambient Backscatter Assisted Co-Existence in Aerial-IRS Wireless NetworksSolanki, Sourabh ; ; et alin IEEE Open Journal of the Communications Society (2022), 3 Ambient backscatter communication (AmBC) is an emerging technology that has the potential to offer spectral- and energy-efficient solutions for the next generation wireless communications networks ... [more ▼] Ambient backscatter communication (AmBC) is an emerging technology that has the potential to offer spectral- and energy-efficient solutions for the next generation wireless communications networks, especially for the Internet of Things (IoT). Intelligent reflecting surfaces (IRSs) are also perceived to be an integral part of the beyond 5G systems to complement the traditional relaying scheme. To this end, this paper proposes a novel system design that enables the co-existence of a backscattering secondary system with the legacy primary system. This co-existence is primarily driven by leveraging the AmBC technique in IRS-assisted unmanned aerial vehicle (UAV) networks. More specifically, an aerial-IRS mounted on a UAV is considered to be employed for cooperatively relaying the transmitted signal from a terrestrial primary source node to a user equipment on the ground. Meanwhile, capitalizing on the AmBC technology, a backscatter capable terrestrial secondary node transmits its information to a terrestrial secondary receiver by modulating and backscattering the ambient relayed radio frequency signals from the UAV-IRS. We comprehensively analyze the performance of the proposed design framework with co-existing systems by deriving the outage probability and ergodic spectral efficiency expressions. Moreover, we also investigate the asymptotic behaviour of outage performance in high transmit power regimes for both primary and secondary systems. Importantly, we analyze the performance of the primary system by considering two different scenarios i.e., optimal phase shifts design and random phase shifting at IRS. Finally, based on the analytical performance assessment, we present numerical results to provide various useful insights and also provide simulation results to corroborate the derived theoretical results. [less ▲] Detailed reference viewed: 97 (24 UL)Dynamic Bandwidth Allocation and Precoding Design for Highly-Loaded Multiuser MISO in Beyond 5G NetworksVu, Thang Xuan ; Chatzinotas, Symeon ; Ottersten, Björn in IEEE Transactions on Wireless Communications (2022), 21(3), 1794-1805 Multiuser techniques play a central role in the fifth-generation (5G) and beyond 5G (B5G) wireless networks that exploit spatial diversity to serve multiple users simultaneously in the same frequency ... [more ▼] Multiuser techniques play a central role in the fifth-generation (5G) and beyond 5G (B5G) wireless networks that exploit spatial diversity to serve multiple users simultaneously in the same frequency resource. It is well known that a multi-antenna base station (BS) can efficiently serve a number of users not exceeding the number of antennas at the BS via precoding design. However, when there are more users than the number of antennas at the BS, conventional precoding design methods perform poorly because inter-user interference cannot be efficiently eliminated. In this paper, we investigate the performance of a highly-loaded multiuser system in which a BS simultaneously serves a number of users that is larger than the number of antennas. We propose a dynamic bandwidth allocation and precoding design framework and apply it to two important problems in multiuser systems: i) User fairness maximization and ii) Transmit power minimization, both subject to predefined quality of service (QoS) requirements. The premise of the proposed framework is to dynamically assign orthogonal frequency channels to different user groups and carefully design the precoding vectors within every user group. Since the formulated problems are non-convex, we propose two iterative algorithms based on successive convex approximations (SCA), whose convergence is theoretically guaranteed. Furthermore, we propose a low-complexity user grouping policy based on the singular value decomposition (SVD) to further improve the system performance. Finally, we demonstrate via numerical results that the proposed framework significantly outperforms existing designs in the literature. [less ▲] Detailed reference viewed: 70 (17 UL)Waveform Design for Joint Radar-Communications with Low Complexity Analog Components; ; et al Poster (2022, March) In this paper, we aim to design an efficient and low hardware complexity based dual-function multiple-input multiple-output (MIMO) joint radar-communication (JRC) system. It is implemented via a low ... [more ▼] In this paper, we aim to design an efficient and low hardware complexity based dual-function multiple-input multiple-output (MIMO) joint radar-communication (JRC) system. It is implemented via a low complexity analog architecture, constituted by a phase shifting network and variable gain amplifier. The proposed system exploits the multiple antenna transmitter for the simultaneous communication with multiple downlink users and radar target detection. The transmit waveform of the proposed JRC system is designed to minimize the downlink multi-user interference such that the desired radar beampattern is achieved and the architecture specific constraints are satisfied. The resulting optimization problem is non-convex and in general difficult to solve. We propose an efficient algorithmic solution based on the primal-dual framework. The numerical results show the effectiveness of the proposed approach. [less ▲] Detailed reference viewed: 12 (0 UL)UAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory OptimizationTran Dinh, Hieu ; Nguyen, van Dinh ; Chatzinotas, Symeon et alin IEEE Transactions on Wireless Communications (2022), 21(3), 1621-1637 Unmanned aerial vehicle (UAV) communication hasemerged as a prominent technology for emergency communi-cations (e.g., natural disaster) in the Internet of Things (IoT)networks to enhance the ability of ... [more ▼] Unmanned aerial vehicle (UAV) communication hasemerged as a prominent technology for emergency communi-cations (e.g., natural disaster) in the Internet of Things (IoT)networks to enhance the ability of disaster prediction, damageassessment, and rescue operations promptly. A UAV can bedeployed as a flying base station (BS) to collect data from time-constrained IoT devices and then transfer it to a ground gateway(GW). In general, the latency constraint at IoT devices and UAV’slimited storage capacity highly hinder practical applicationsof UAV-assisted IoT networks. In this paper, full-duplex (FD)radio is adopted at the UAV to overcome these challenges. Inaddition, half-duplex (HD) scheme for UAV-based relaying isalso considered to provide a comparative study between twomodes (viz., FD and HD). Herein, a device is considered tobe successfully served iff its data is collected by the UAV andconveyed to GW timely during flight time. In this context,we aim to maximize the number of served IoT devices byjointly optimizing bandwidth, power allocation, and the UAVtrajectory while satisfying each device’s requirement and theUAV’s limited storage capacity. The formulated optimizationproblem is troublesome to solve due to its non-convexity andcombinatorial nature. Towards appealing applications, we firstrelax binary variables into continuous ones and transform theoriginal problem into a more computationally tractable form.By leveraging inner approximation framework, we derive newlyapproximated functions for non-convex parts and then develop asimple yet efficient iterative algorithm for its solutions. Next,we attempt to maximize the total throughput subject to thenumber of served IoT devices. Finally, numerical results showthat the proposed algorithms significantly outperform benchmarkapproaches in terms of the number of served IoT devices andsystem throughput. [less ▲] Detailed reference viewed: 98 (25 UL)Intelligent Reflecting Surface-assisted MU-MISOSystems with Imperfect Hardware: ChannelEstimation and Beamforming Design; ; et al in IEEE Transactions on Wireless Communications (2022), 21(3), 2077-2092 Intelligent reflecting surface (IRS), consisting of low-cost passive elements, is a promising technology for improvingthe spectral and energy efficiency of the fifth-generation (5G)and beyond networks. It ... [more ▼] Intelligent reflecting surface (IRS), consisting of low-cost passive elements, is a promising technology for improvingthe spectral and energy efficiency of the fifth-generation (5G)and beyond networks. It is also noteworthy that an IRS canshape the reflected signal propagation. Most works in IRS-assisted systems have ignored the impact of the inevitable residualhardware impairments (HWIs) at both the transceiver hardwareand the IRS while any relevant works have addressed only simplescenarios, e.g., with single-antenna network nodes and/or withouttaking the randomness of phase noise at the IRS into account.In this work, we aim at filling up this gap by considering ageneral IRS-assisted multi-user (MU) multiple-input single-output(MISO) system with imperfect channel state information (CSI)and correlated Rayleigh fading. In parallel, we present a generalcomputationally efficient methodology for IRS reflect beamforming(RB) optimization. Specifically, we introduce an advantageouschannel estimation (CE) method for such systems accounting forthe HWIs. Moreover, we derive the uplink achievable spectralefficiency (SE) with maximal-ratio combining (MRC) receiver,displaying three significant advantages being: 1) its closed-formexpression, 2) its dependence only on large-scale statistics, and3) its low training overhead. Notably, by exploiting the first twobenefits, we achieve to perform optimization with respect to thethat can take place only at every several coherence intervals,and thus, reduces significantly the computational cost comparedto other methods which require frequent phase optimization.Among the insightful observations, we highlight that uncorrelatedRayleigh fading does not allow optimization of the SE, whichmakes the application of an IRS ineffective. Also, in the case thatthe phase drifts, describing the distortion of the phases in theRBM, are uniformly distributed, the presence of an IRS providesno advantage. The analytical results outperform previous worksand are verified by Monte-Carlo (MC) simulations. [less ▲] Detailed reference viewed: 18 (0 UL)Stochastic Geometry-Based Analysis of Cache-Enabled Hybrid Satellite-Aerial-Terrestrial Networks With Non-Orthogonal Multiple Access; ; et al in IEEE Transactions on Wireless Communications (2022), 21(2), 1272-1287 Due to the emergence of non-terrestrial platformswith extensive coverage, flexible deployment, and reconfigurablecharacteristics, the hybrid satellite-aerial-terrestrial networks(HSATNs) can accommodate a ... [more ▼] Due to the emergence of non-terrestrial platformswith extensive coverage, flexible deployment, and reconfigurablecharacteristics, the hybrid satellite-aerial-terrestrial networks(HSATNs) can accommodate a great variety of wireless accessservices in different applications. To effectively reduce the trans-mission latency and facilitate the frequent update of files withimproved spectrum efficiency, we investigate the performanceof cache-enabled HSATN, where the user retrieves the requiredcontent files from the cache-enabled aerial relay or the satellitewith the non-orthogonal multiple access (NOMA) scheme. If therequired content files of the user are cached in the aerial relay,the cache-enabled relay would serve directly. Otherwise, the userwould retrieve the content file from the satellite system, where thesatellite system seeks opportunities for proactive content pushingto the relay during the user content delivery phase. Specifically,taking into account the uncertainty of the number and locationof aerial relays, along with the channel fading of terrestrialusers, the outage probability and hit probability of the considerednetwork are, respectively, derived based on stochastic geometry.Numerical results unveil the effectiveness of the cache-enabledHSATN with the NOMA scheme and proclaim the influence ofkey factors on the system performance. The realistic, tractable,and expandable framework, as well as associated methodology,provide both useful guidance and a solid foundation for evolvednetworks with advanced configurations in the performance ofcache-enabled HSATN. [less ▲] Detailed reference viewed: 12 (0 UL)Deep Convolutional Self-Attention Network forEnergy-Efficient Power Control in NOMA Networks; ; Chatzinotas, Symeon et alin IEEE Transactions on Vehicular Technology (2022), 71(5), 5540-5545 In this letter, we propose an end-to-end multi-modalbased convolutional self-attention network to perform powercontrol in non-orthogonal multiple access (NOMA) networks. Weformulate an energy efficiency ... [more ▼] In this letter, we propose an end-to-end multi-modalbased convolutional self-attention network to perform powercontrol in non-orthogonal multiple access (NOMA) networks. Weformulate an energy efficiency (EE) maximization problem wedesign an iterative solution to handle the optimization problem.This solution can provides an offline benchmark but might notbe suitable for online power control therefore, we employ ourproposed deep learning model. The proposed deep learning modelconsists of two main pipelines, one for the deep feature mappingwhere we stack our self-attention block on top of a ResNet toextract high quality features and focus on specific regions in thedata to extract the patterns of the influential factors (interference,quality of service (QoS) and the corresponding power allocation).The second pipeline is to extract the shallow modality features.Those features are combined and passed to a dense layer toperform the final power prediction. The proposed deep learningframework achieves near optimal performance and outperformstraditional solutions and other strong deep learning models suchas PowerNet and the conventional convolutional neural network(CNN). [less ▲] Detailed reference viewed: 10 (1 UL)Energy Efficient Sparse Precoding Design for Satellite Communication SystemAbdu, Tedros Salih ; Kisseleff, Steven ; Lagunas, Eva et alScientific Conference (2022) Through precoding, the spectral efficiency of the system can be improved; thus, more users can benefit from 5G and beyond broadband services. However, complete precoding (using all precoding coefficients ... [more ▼] Through precoding, the spectral efficiency of the system can be improved; thus, more users can benefit from 5G and beyond broadband services. However, complete precoding (using all precoding coefficients) may not be possible in practice due to the high signal processing complexity involved in calculating a large number of precoding coefficients and combining them with symbols for transmission. In this paper, we propose an energy-efficient sparse precoding design, where only a few precoding coefficients are used with lower power consumption depending on the demand. In this context, we formulate an optimization problem that minimizes the number of in-use precoding coefficients and the system power consumption while matching the per beam demand. This problem is nonconvex. Hence, we apply Lagrangian relaxation and successive convex approximation to convexify it. The proposed solution outperforms the benchmark scheme in power consumption and demand satisfaction with the additional advantage of sparse precoding design. [less ▲] Detailed reference viewed: 87 (20 UL) Physical Layer Security Analysis of SWIPT-Enabled Cooperative Wireless IoT Networks in the Presence of Friendly Jammer and Eavesdropper; Tran Dinh, Hieu ; et alin IEEE Internet of Things Journal (2022), 9(21), —Physical layer security (PLS) and simultane ous wireless information and power transfer (SWIPT) in cooperative relaying have gained great interest as technolo gies for security and energy enhancement in ... [more ▼] —Physical layer security (PLS) and simultane ous wireless information and power transfer (SWIPT) in cooperative relaying have gained great interest as technolo gies for security and energy enhancement in Internet-of Things (IoT) networks. In this work, we investigate PLS for a SWIPT- and AF-enabled cooperative wireless IoT system, consisting of one source, multiple energy harvesting (EH) relays, and one destination, in the presence of an eaves dropper that tries to overhear the confidential information. Furthermore, an EH-friendly jammer is deployed to trans mit jamming signals aimed at the eavesdropper to improve the security system. In this context, a low complexity, sub optimal, but efficient relay selection method is proposed. More specifically, the relay is selected to convey informa tion such that it has the best channel to the source. Based on the proposed system model, the performance analysis of intercept probability (IP), asymptotic IP, and non-zero secrecy probability (NZSP) is analyzed by considering the time switching (TS)-based relaying strategy. Particularly, Tan N. Nguyen is with the Wireless Communications Re search Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam. (e mail:nguyennhattan@tdtu.edu.vn). Dinh-Hieu Tran, Symeon Chatzinotas, and Bjorn Ottersten are with ¨ the Interdisciplinary Centre for Security, Reliability and Trust (SnT), the University of Luxembourg, Luxembourg. (e-mail: {hieu.tran-dinh, symeon.chatzinotas, bjorn.ottersten} @uni.lu). Miroslav Voznak is with VSB - Technical University of Ostrava, 17. listopadu 15/2172, 708 33 Ostrava - Poruba, Czech Republic. (e-mail:miroslav.voznak@vsb.cz). H. V. Poor is with the Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544 USA. (email: poor@princeton.edu). Byung-Seo Kim is with the Department of Software and Com munications Engineering, Hongik University, Sejong 30016, South Korea (e-mail: jsnbs@hongik.ac.kr). Corresponding author: Van-Duc Phan is at Faculty of Automobile Technology, Van Lang University, Ho Chi Minh City, Vietnam. (email: duc.pv@vlu.edu.vn). This research was supported by the Ministry of Education, Youth and Sports of the Czech Republic under the grant SP2021/25 and e-INFRA CZ (ID:90140). the exact closed-form expression of IP is achieved applying modified Bessel function expansion. Finally, Monte-Carlo simulations are employed to corroborate the correctness and the efficiency of our mathematical analysis. [less ▲] Detailed reference viewed: 30 (0 UL)Active Terminal Identification, Channel Estimation, and Signal Detection for Grant-Free NOMA-OTFS in LEO Satellite Internet-of-Things; ; et al in IEEE Transactions on Wireless Communications ( Early Access ) (2022) This paper investigates the massive connectivity of low Earth orbit (LEO) satellite-based Internet-of-Things (IoT) for seamless global coverage. We propose to integrate the grant-free non-orthogonal ... [more ▼] This paper investigates the massive connectivity of low Earth orbit (LEO) satellite-based Internet-of-Things (IoT) for seamless global coverage. We propose to integrate the grant-free non-orthogonal multiple access (GF-NOMA) paradigm with the emerging orthogonal time frequency space (OTFS) modulation to accommodate the massive IoT access, and mitigate the long round-trip latency and severe Doppler effect of terrestrial–satellite links (TSLs). On this basis, we put forward a two-stage successive active terminal identification (ATI) and channel estimation (CE) scheme as well as a low-complexity multi-user signal detection (SD) method. Specifically, at the first stage, the proposed training sequence aided OTFS (TS-OTFS) data frame structure facilitates the joint ATI and coarse CE, whereby both the traffic sparsity of terrestrial IoT terminals and the sparse channel impulse response are leveraged for enhanced performance. Moreover, based on the single Doppler shift property for each TSL and sparsity of delay-Doppler domain channel, we develop a parametric approach to further refine the CE performance. Finally, a least square based parallel time domain SD method is developed to detect the OTFS signals with relatively low complexity. Simulation results demonstrate the superiority of the proposed methods over the state-of-the-art solutions in terms of ATI, CE, and SD performance confronted with the long round-trip latency and severe Doppler effect. [less ▲] Detailed reference viewed: 17 (0 UL)Time vs. Unit Cell Splitting for Autonomous Reconfigurable Intelligent SurfacesNtontin, Konstantinos ; ; Abdullah, Zaid et alScientific Conference (2022) Detailed reference viewed: 15 (2 UL)Network Traffic Modeling and Prediction Using Graph Gaussian Processes; Chatzinotas, Symeon in IEEE Access (2022) Traffic modeling and prediction is a vital task for designing efficient resource allocation strategies in telecommunication networks. This is challenging because network traffic data exhibits complex ... [more ▼] Traffic modeling and prediction is a vital task for designing efficient resource allocation strategies in telecommunication networks. This is challenging because network traffic data exhibits complex nonlinear spatiotemporal interactions. Moreover, the data can have missing values when traffic statistic collection is unavailable in certain nodes. In this paper, we introduce a graph Gaussian Process (GP) model for this challenging problem. The GP is a Bayesian non-parametric model and highly flexible in capturing complex patterns in the data. Additionally, it provides uncertainty information which can be exploited for robust resource allocation problems. The developed graph GP model is almost free of hyper-parameter tuning, can accurately capture short-term and long-term temporal patterns and can infer missing values by learning spatiotemporal interactions among the nodes in the network. Subsequently, we approximate the intractable posterior distribution using Variational Bayes (VB) algorithm which can be efficiently implemented. Finally, we evaluate the accuracy of the proposed model for predicting the data traffic using two real-world network datasets. Our simulation results shows that the proposed model can achieve better prediction accuracy with respect to the state-of-the-art approaches [less ▲] Detailed reference viewed: 11 (0 UL)Traffic-Aware Satellite Switch-off Technique for LEO ConstellationsGupta, Vaibhav Kumar ; Al-Hraishawi, Hayder ; Lagunas, Eva et alScientific Conference (2022) Detailed reference viewed: 88 (19 UL)User Scheduling and Power Allocation for Precoded Multi-Beam High Throughput Satellite Systems With Individual Quality of Service Constraints; Lagunas, Eva ; et alin IEEE Transactions on Vehicular Technology (2022) Detailed reference viewed: 21 (1 UL)What Will the Future ofUAV Cellular Communications Be?A Flight from 5G to 6G; ; et al in IEEE Communications Surveys & Tutorials (2022), 24(3), 1304-1335 What will the future of UAV cellular communicationsbe?In this tutorial article, we address such a compelling yetdifficult question by embarking on a journey from 5G to 6Gand expounding a large number of ... [more ▼] What will the future of UAV cellular communicationsbe?In this tutorial article, we address such a compelling yetdifficult question by embarking on a journey from 5G to 6Gand expounding a large number of case studies supported byoriginal results. We start by overviewing the status quo on UAVcommunications from an industrial standpoint, providing freshupdates from the 3GPP and detailing new 5G NR features insupport of aerial devices. We then dissect the potential andthe limitations of such features. In particular, we demonstratehow sub-6 GHz massive MIMO can successfully tackle cellselection and interference challenges, we showcase encouragingmmWave coverage evaluations in both urban and suburban/ruralsettings, and we examine the peculiarities of direct device-to-device communications in the sky. Moving on, we sneak a peekat next-generation UAV communications, listing some of the usecases envisioned for the 2030s. We identify the most promising6G enablers for UAV communication, those expected to takethe performance and reliability to the next level. For each ofthese disruptive new paradigms (non-terrestrial networks, cell-free architectures, artificial intelligence, reconfigurable intelligentsurfaces, and THz communications), we gauge the prospectivebenefits for UAVs and discuss the main technological hurdles thatstand in the way. All along, we distil our numerous findings intoessential takeaways, and we identify key open problems worthyof further study. [less ▲] Detailed reference viewed: 18 (1 UL)The Next Generation of Beam Hopping Satellite Systems: Dynamic Beam Illumination with Selective PrecodingChen, Lin ; Ha, Vu Nguyen ; Lagunas, Eva et alin IEEE Transactions on Wireless Communications (2022) Detailed reference viewed: 99 (43 UL) |
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