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See detailFedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud System
Nguyen, van Dinh UL; Chatzinotas, Symeon UL; Ottersten, Björn UL et al

in IEEE Transactions on Wireless Communications (in press)

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of ... [more ▼]

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of enabling FL over a wireless fogcloud system (e.g., non-i.i.d. data, users’ heterogeneity), we first propose an efficient FL algorithm based on Federated Averaging (called FedFog) to perform the local aggregation of gradient parameters at fog servers and global training update at the cloud. Next, we employ FedFog in wireless fog-cloud systems by investigating a novel network-aware FL optimization problem that strikes the balance between the global loss and completion time. An iterative algorithm is then developed to obtain a precise measurement of the system performance, which helps design an efficient stopping criteria to output an appropriate number of global rounds. To mitigate the straggler effect, we propose a flexible user aggregation strategy that trains fast users first to obtain a certain level of accuracy before allowing slow users to join the global training updates. Extensive numerical results using several real-world FL tasks are provided to verify the theoretical convergence of FedFog. We also show that the proposed co-design of FL and communication is essential to substantially improve resource utilization while achieving comparable accuracy of the learning model. [less ▲]

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See detailShort-Packet Communications in Multi-Hop Networks with WET: Performance Analysis and Deep Learning-Aided Optimization
Nguyen, Toan Van; Nguyen, van Dinh UL; Costa, Daniel Benevides da et al

in IEEE Transactions on Wireless Communications (in press)

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See detailSpectral Efficiency Analysis of HybridRelay-Reflecting Intelligent Surface-AssistedCell-Free Massive MIMO Systems
Nguyen, Nhan Thanh; Nguyen, Van-Dinh; Nguyen, Hieu Van et al

in IEEE Transactions on Wireless Communications (2022)

A cell-free (CF) massive multiple-input-multiple-output (mMIMO) system can provide uniformspectral efficiency (SE) with simple signal processing. On the other hand, a recently introduced technol-ogy ... [more ▼]

A cell-free (CF) massive multiple-input-multiple-output (mMIMO) system can provide uniformspectral efficiency (SE) with simple signal processing. On the other hand, a recently introduced technol-ogy called hybrid relay-reflecting intelligent surface (HR-RIS) can customize the physical propagationenvironment by simultaneously reflecting and amplifying radio waves in preferred directions. Thus, itis natural that incorporating HR-RIS into CF mMIMO can be a symbiotic convergence of these twotechnologies for future wireless communications. This motivates us to consider an HR-RIS-aided CFmMIMO system to utilize their combined benefits. We first model the uplink/downlink channels and de-rive the minimum-mean-square-error estimate of the effective channels. We then present a comprehensiveanalysis of SE performance of the considered system. Specifically, we derive closed-form expressionsfor the uplink and downlink SE. The results reveal important observations on the performance gainsachieved by HR-RISs compared to conventional systems. The presented analytical results are also validfor conventional CF mMIMO systems and those aided by passive reconfigurable intelligent surfaces. Suchresults play an important role in designing new transmission strategies and optimizing HR-RIS-aided CFmMIMO systems. Finally, we provide extensive numerical results to verify the analytical derivations andthe effectiveness of the proposed system design under various settings. [less ▲]

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See detailAdapting to Dynamic LEO-B5G Systems: Meta-Critic Learning Based Efficient Resource Scheduling
Yuan, Yaxiong; Lei, Lei; Vu, Thang Xuan UL et al

in IEEE Transactions on Wireless Communications (2022), 21(11), 9582-9595

Low earth orbit (LEO) satellite-assisted communications have been considered as one of the key elements in beyond 5G systems to provide wide coverage and cost-efficient data services. Such dynamic space ... [more ▼]

Low earth orbit (LEO) satellite-assisted communications have been considered as one of the key elements in beyond 5G systems to provide wide coverage and cost-efficient data services. Such dynamic space-terrestrial topologies impose an exponential increase in the degrees of freedom in network management. In this paper, we address two practical issues for an over-loaded LEO-terrestrial system. The first challenge is how to efficiently schedule resources to serve a massive number of connected users, such that more data and users can be delivered/served. The second challenge is how to make the algorithmic solution more resilient in adapting to dynamic wireless environments. We first propose an iterative suboptimal algorithm to provide an offline benchmark. To adapt to unforeseen variations, we propose an enhanced meta-critic learning algorithm (EMCL), where a hybrid neural network for parameterization and the Wolpertinger policy for action mapping are designed in EMCL. The results demonstrate EMCL’s effectiveness and fast-response capabilities in over-loaded systems and in adapting to dynamic environments compare to previous actor-critic and meta-learning methods. [less ▲]

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See detailRIS-Assisted Robust Hybrid Beamforming AgainstSimultaneous Jamming and Eavesdropping Attacks
Sun, Yifu; An, Kang; Zhu, Yonggang et al

in IEEE Transactions on Wireless Communications (2022), 21(11), 9212-9231

Wireless communications are increasingly vulnera-ble to simultaneous jamming and eavesdropping attacks due tothe inherent broadcast nature of wireless channels. With thisfocus, due to the potential of ... [more ▼]

Wireless communications are increasingly vulnera-ble to simultaneous jamming and eavesdropping attacks due tothe inherent broadcast nature of wireless channels. With thisfocus, due to the potential of reconfigurable intelligent surface(RIS) in substantially saving power consumption and boostinginformation security, this paper is the first work to investigate theeffect of the RIS-assisted wireless transmitter in improving boththe spectrum efficiency and the security of multi-user cellularnetwork. Specifically, with the imperfect angular channel stateinformation (CSI), we aim to address the worst-case sum ratemaximization problem by jointly designing the receive decoder atthe users, both the digital precoder and the artificial noise (AN)at the base station (BS), and the analog precoder at the RIS, whilemeeting the minimum achievable rate constraint, the maximumwiretap rate requirement, and the maximum power constraint.To address the non-convexity of the formulated problem, we firstpropose an alternative optimization (AO) method to obtain anefficient solution. In particular, a heuristic scheme is proposedto convert the imperfect angular CSI into a robust one andfacilitate the developing a closed-form solution to the receivedecoder. Then, after reformulating the original problem into atractable one by exploiting the majorization-minimization (MM)method, the digital precoder and AN can be addressed by thequadratically constrained quadratic programming (QCQP), andthe RIS-aided analog precoder is solved by the proposed pricemechanism-based Riemannian manifold optimization (RMO).To further reduce the computational complexity of the pro-posed AO method and gain more insights, we develop a low-complexity monotonic optimization algorithm combined with thedual method (MO-dual) to identify the closed-form solution.Numerical simulations using realistic RIS and communicationmodels demonstrate the superiority and validity of our proposedschemes over the existing benchmark schemes. [less ▲]

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See detailSpectral Efficiency Analysis of Hybrid Relay-Reflecting Intelligent Surface-Assisted Cell-Free Massive MIMO Systems
Nguyen, Nhan Thanh; Nguyen, Van-Dinh; Nguyen, Hieu Van et al

in IEEE Transactions on Wireless Communications (2022)

A cell-free (CF) massive multiple-input-multiple-output (mMIMO) system can provide uniform spectral efficiency (SE) with simple signal processing. On the other hand, a recently introduced technology ... [more ▼]

A cell-free (CF) massive multiple-input-multiple-output (mMIMO) system can provide uniform spectral efficiency (SE) with simple signal processing. On the other hand, a recently introduced technology called hybrid relay-reflecting intelligent surface (HR-RIS) can customize the physical propagation environment by simultaneously reflecting and amplifying radio waves in preferred directions. Thus, it is natural that incorporating HR-RIS into CF mMIMO can be a symbiotic convergence of these two technologies for future wireless communications. This motivates us to consider an HR-RIS-aided CF mMIMO system to utilize their combined benefits. We first model the uplink/downlink channels and derive the minimum-mean-square-error estimate of the effective channels. We then present a comprehensive analysis of SE performance of the considered system. Specifically, we derive closed-form expressions for the uplink and downlink SE. The results reveal important observations on the performance gains achieved by HR-RISs compared to conventional systems. The presented analytical results are also valid for conventional CF mMIMO systems and those aided by passive reconfigurable intelligent surfaces. Such results play an important role in designing new transmission strategies and optimizing HR-RIS-aided CF mMIMO systems. Finally, we provide extensive numerical results to verify the analytical derivations and the effectiveness of the proposed system design under various settings. [less ▲]

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See detailFrequency-Packed Faster-Than-Nyquist Signaling via Symbol-Level Precoding for Multiuser MISO Redundant Transmissions
Alves Martins, Wallace UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Wireless Communications (2022), 21(10), 8660-8674

This work addresses the issue of interference generated by co-channel users in downlink multi-antenna multicarrier systems with frequency-packed faster-than-Nyquist (FTN) signaling. The resulting ... [more ▼]

This work addresses the issue of interference generated by co-channel users in downlink multi-antenna multicarrier systems with frequency-packed faster-than-Nyquist (FTN) signaling. The resulting interference stems from an aggressive strategy for enhancing the throughput via frequency reuse across different users and the squeezing of signals in the time-frequency plane beyond the Nyquist limit. The spectral efficiency is proved to be increasing with the frequency packing and FTN acceleration factors. The lower bound for the FTN sampling period that guarantees information losslesness is derived as a function of the transmitting-filter roll-off factor, the frequency-packing factor, and the number of subcarriers. Space-time-frequency symbol-level precoders (SLPs) that trade off constructive and destructive interblock interference (IBI) at the single-antenna user terminals are proposed. Redundant elements are added as guard interval to cope with vestigial destructive IBI effects. The proposals can handle channels with delay spread longer than the multicarrier-symbol duration. The receiver architecture is simple, for it does not require digital multicarrier demodulation. Simulations indicate that the proposed SLP outperforms zero-forcing precoding and achieves a target balance between spectral and energy efficiencies by controlling the amount of added redundancy from zero (full IBI) to half (destructive IBI-free) the group delay of the equivalent channel. [less ▲]

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See detailDefeating Super-Reactive Jammers With Deception Strategy: Modeling, Signal Detection, and Performance Analysis
Van Huynh, Nguyen; Nguyen, Diep N.; Thai Hoang, Dinh et al

in IEEE Transactions on Wireless Communications (2022), 21(9), 7374-7390

This paper develops a novel framework to defeat a super-reactive jammer, one of the most difficult jamming attacks to deal with in practice. Specifically, the jammer has an unlimited power budget and is ... [more ▼]

This paper develops a novel framework to defeat a super-reactive jammer, one of the most difficult jamming attacks to deal with in practice. Specifically, the jammer has an unlimited power budget and is equipped with the self-interference suppression capability to simultaneously attack and listen to the 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 and then leverage jamming signals to transmit data based on the ambient backscatter communication technology. To detect the backscattered signals, the maximum likelihood detector can be adopted. However, this method is notorious for its high computational complexity and requires the model of the current propagation environment as well as channel state information. Hence, we propose a deep learning-based detector that can dynamically adapt to any channels and noise distributions. With a Long Short-Term Memory network, our detector can learn the received signals’ dependencies to achieve a performance close to that of the optimal maximum likelihood detector. Through simulation and theoretical results, we demonstrate that with our approaches, the more power the jammer uses to attack the channel, the better bit error rate performance the transmitter can achieve. [less ▲]

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See detailJoint Optimization of Beam-Hopping Design and NOMA-Assisted Transmission for Flexible Satellite Systems
Wang, Anyue UL; Lei, Lei; Lagunas, Eva UL et al

in IEEE Transactions on Wireless Communications (2022)

Next-generation satellite systems require more flexibility in resource management such that available radio resources can be dynamically allocated to meet time-varying and non-uniform traffic demands ... [more ▼]

Next-generation satellite systems require more flexibility in resource management such that available radio resources can be dynamically allocated to meet time-varying and non-uniform traffic demands. Considering potential benefits of beam hopping (BH) and non-orthogonal multiple access (NOMA), we exploit the time-domain flexibility in multi-beam satellite systems by optimizing BH design, and enhance the power-domain flexibility via NOMA. In this paper, we investigate the synergy and mutual influence of beam hopping and NOMA. We jointly optimize power allocation, beam scheduling, and terminal-timeslot assignment to minimize the gap between requested traffic demand and offered capacity. In the solution development, we formally prove the NP-hardness of the optimization problem. Next, we develop a bounding scheme to tightly gauge the global optimum and propose a suboptimal algorithm to enable efficient resource assignment. Numerical results demonstrate the benefits of combining NOMA and BH, and validate the superiority of the proposed BH-NOMA schemes over benchmarks. [less ▲]

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See detailJoint resource allocation for full-duplex ambient backscatter communication: A difference convex algorithm
Kavehmadavani, Fatemeh UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Wireless Communications (2022)

Nowadays, Ambient Backscatter Communication (AmBC) systems have emerged as a green communication technology to enable massive self-sustainable wireless networks by leveraging Radio Frequency (RF) Energy ... [more ▼]

Nowadays, Ambient Backscatter Communication (AmBC) systems have emerged as a green communication technology to enable massive self-sustainable wireless networks by leveraging Radio Frequency (RF) Energy Harvesting (EH) capability. A Full-duplex Ambient Backscatter Communication (FAmBC) network with a Full-duplex Access Point (AP), a dedicated Legacy User (LU), and several Backscatter Devices (BDs) is considered in this study. The AP with two antennas transfers downlink Orthogonal Frequency Division Multiplexing (OFDM) information and energy to the dedicated LU and several BDs, respectively, while receiving uplink backscattered information from BDs at the same time. One of the key aims in AmBC networks is to ensure fairness among BDs. To address this, we propose the Multi-objective Lexicographical Optimization Problem (MLOP), which aims to maximize the minimum BD’s … [less ▲]

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See detailDefeating Super-Reactive Jammers WithDeception Strategy: Modeling, SignalDetection, and Performance Analysis
Van Huynh, Nguyen; Nguyen, Diep N.; Hoang, Dinh Thai 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 ▲]

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See detailUAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization
Tran Dinh, Hieu UL; Nguyen, van Dinh UL; Chatzinotas, Symeon UL et al

in 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 ▲]

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See detailDynamic Bandwidth Allocation and Precoding Design for Highly-Loaded Multiuser MISO in Beyond 5G Networks
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

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 ▲]

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See detailIntelligent Reflecting Surface-assisted MU-MISOSystems with Imperfect Hardware: ChannelEstimation and Beamforming Design
Papazafeiropoulos, Anastasios; Pan, Cunhua; Kourtessis, Pandelis 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 ▲]

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See detailStochastic Geometry-Based Analysis of Cache-Enabled Hybrid Satellite-Aerial-Terrestrial Networks With Non-Orthogonal Multiple Access
Zhang, Xiaokai; Zhang, Bangning; An, Kang 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 ▲]

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See detailHybrid Analog/Digital Precoding for Downlink Massive MIMO LEO Satellite Communications
You, Li; Qiang, Xiaoyu; Li, Ke-Xin et al

in IEEE Transactions on Wireless Communications (2022), 21(8), 5962-5976

Massive multiple-input multiple-output (MIMO) is promising for low earth orbit (LEO) satellite communications due to the potential in enhancing the spectral efficiency. However, the conventional fully ... [more ▼]

Massive multiple-input multiple-output (MIMO) is promising for low earth orbit (LEO) satellite communications due to the potential in enhancing the spectral efficiency. However, the conventional fully digital precoding architectures might lead to high implementation complexity and energy consumption. In this paper, hybrid analog/digital precoding solutions are developed for the downlink operation in LEO massive MIMO satellite communications, by exploiting the slow-varying statistical channel state information (CSI) at the transmitter. First, we formulate the hybrid precoder design as an energy efficiency (EE) maximization problem by considering both the continuous and discrete phase shift networks for implementing the analog precoder. The cases of both the fully and the partially connected architectures are considered. Since the EE optimization problem is nonconvex, it is in general difficult to solve. To make the EE maximization problem tractable, we apply a closed-form tight upper bound to approximate the ergodic rate. Then, we develop an efficient algorithm to obtain the fully digital precoders. Based on which, we further develop two different efficient algorithmic solutions to compute the hybrid precoders for the fully and the partially connected architectures, respectively. Simulation results show that the proposed approaches achieve significant EE performance gains over the existing baselines, especially when the discrete phase shift network is employed for analog precoding. [less ▲]

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See detailJoint Multislot Scheduling and Precoding for Unicast and Multicast Scenarios in Multiuser MISO Systems
Bandi, Ashok UL; Mysore Rama Rao, Bhavani Shankar UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2022), 21(7), 5004-5018

This paper studies the joint multislot design of user scheduling and precoding to minimize the time needed to serve all the users for unicast and multicast transmission in single-cell multiuser MISO ... [more ▼]

This paper studies the joint multislot design of user scheduling and precoding to minimize the time needed to serve all the users for unicast and multicast transmission in single-cell multiuser MISO downlink systems. In the literature, the joint design of scheduling and precoding is typically undertaken based on feedback from previous slots. In a system with time-varying channels and QoS requirements, joint multislot designs can achieve better performance since they have the flexibility to schedule users over multiple slots and also can split users across slots efficiently. Further, a joint multislot design can provide a feasible solution even when the sequential design fails. In this paper, scheduling is represented by a binary matrix where the rows represent users, columns represent slots and entries represent scheduling of users in the slots. Noticing that the users may not be permuted across slots for time-varying channels, service time needed for scheduling is rendered as the highest column index corresponding to non-zero columns. With the help of binary scheduling matrix, service time minimization is formulated as a structured mixed-Boolean fractional programming. Further, by exploiting the hidden convex-concave structure in the problem, a convex-concave procedure-based iterative algorithm is proposed. Finally, we vindicate the necessity and illustrate the superiority in performance of joint multislot design over the sequential solution through Monte-Carlo simulations. [less ▲]

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See detailThe Next Generation of Beam Hopping Satellite Systems: Dynamic Beam Illumination with Selective Precoding
Chen, Lin UL; Ha, Vu Nguyen UL; Lagunas, Eva UL et al

in IEEE Transactions on Wireless Communications (2022)

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See detailReconfigurable Intelligent Surface-Assisted Cell-Free Massive MIMO Systems Over Spatially-Correlated Channels
Van Chien, Trinh; Ngo, Hien Quoc; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2022), 21(7), 5106-5128

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free ... [more ▼]

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an aggregated channel estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability. [less ▲]

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See detailFlexible Resource Optimization for GEO Multibeam Satellite Communication System
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

in IEEE Transactions on Wireless Communications (2021)

Conventional GEO satellite communication systems rely on a multibeam foot-print with a uniform resource allocation to provide connectivity to users. However, applying uniform resource allocation is ... [more ▼]

Conventional GEO satellite communication systems rely on a multibeam foot-print with a uniform resource allocation to provide connectivity to users. However, applying uniform resource allocation is inefficient in presence of non-uniform demand distribution. To overcome this limitation, the next generation of broadband GEO satellite systems will enable flexibility in terms of power and bandwidth assignment, enabling on-demand resource allocation. In this paper, we propose a novel satellite resource assignment design whose goal is to satisfy the beam traffic demand by making use of the minimum transmit power and utilized bandwidth. The motivation behind the proposed design is to maximize the satellite spectrum utilization by pushing the spectrum reuse to affordable limits in terms of tolerable interference. The proposed problem formulation results in a non-convex optimization structure, for which we propose an efficient tractable solution. We validate the proposed method with extensive numerical results, which demonstrate the efficiency of the proposed approach with respect to benchmark schemes. [less ▲]

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