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See detailErgodic Capapcity of NOMA-Based Satellite Networks with Randomly Deployed Users
Yan, Xiaojuan; Xiao, Hailin; An, Kang et al

in IEEE Systems Journal (2020), 14(3), 3343-3350

In this letter, we investigate the ergodic capacity of an uplink satellite network using a power-domain nonorthogonal multiple access (NOMA for simplicity) to serve users simultaneously in the ... [more ▼]

In this letter, we investigate the ergodic capacity of an uplink satellite network using a power-domain nonorthogonal multiple access (NOMA for simplicity) to serve users simultaneously in the consideration of random deployment of satellite users. Taking into account the deployed information of served users, we derive expression for the achievable ergodic capacity of the considered networks, where an entire link budget involving propagation loss, channel statistical prosperities, and location information is considered. Moreover, expression for ergodic capacity with OMA scheme is also derived to facilitate the performance comparison. Numerical simulation results are provided to attest the validity of theoretical results and show the vital effect of key parameters, such as the deployed information and link quality on the considered networks. [less ▲]

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See detailActive Content Popularity Learning and Caching Optimization with Hit Ratio Guarantees
Bommaraveni, Srikanth UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in Active Content Popularity Learning and Caching Optimization with Hit Ratio Guarantees (2020), 8

Edge caching is an effective solution to reduce delivery latency and network congestion by bringing contents close to end-users. A deep understanding of content popularity and the principles underlying ... [more ▼]

Edge caching is an effective solution to reduce delivery latency and network congestion by bringing contents close to end-users. A deep understanding of content popularity and the principles underlying the content request sequence are required to effectively utilize the cache. Most existing works design caching policies based on global content requests with very limited consideration of individual content requests which reflect personal preferences. To enable the optimal caching strategy, in this paper, we propose an Active learning (AL) approach to learn the content popularities and design an accurate content request prediction model. We model the content requests from user terminals as a demand matrix and then employ AL-based query-by-committee (QBC) matrix completion to predict future missing requests. The main principle of QBC is to query the most informative missing entries of the demand matrix. Based on the prediction provided by the QBC, we propose an adaptive optimization caching framework to learn popularities as fast as possible while guaranteeing an operational cache hit ratio requirement. The proposed framework is model-free, thus does not require any statistical knowledge about the underlying traffic demands. We consider both the fixed and time-varying nature of content popularities. The effectiveness of the proposed learning caching policies over the existing methods is demonstrated in terms of root mean square error, cache hit ratio, and cache size on a simulated dataset. [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; Gautam, Sumit UL et al

E-print/Working paper (2020)

Unmanned aerial vehicle (UAV) communication has emerged as a prominent technology for emergency communications (e.g., natural disaster) in Internet of Things (IoT) networks to enhance the ability of ... [more ▼]

Unmanned aerial vehicle (UAV) communication has emerged as a prominent technology for emergency communications (e.g., natural disaster) in Internet of Things (IoT) networks to enhance the ability of disaster prediction, damage assessment, and rescue operations promptly. In this paper, a UAV is deployed as a flying base station (BS) to collect data from time-constrained IoT devices and then transfer the data to a ground gateway (GW). In general, the latency constraint at IoT users and the limited storage capacity of UAV highly hinder practical applications of UAV-assisted IoT networks. In this paper, full-duplex (FD) technique is adopted at the UAV to overcome these challenges. In addition, half-duplex (HD) scheme for UAV-based relaying is also considered to provide a comparative study between two modes (viz., FD and HD). Herein, a device is successfully served iff its data is collected by UAV and conveyed to GW within the flight time. In this context, we aim at maximizing the number of served IoT devices by jointly optimizing bandwidth and power allocation, as well as the UAV trajectory, while satisfying the requested timeout (RT) requirement of each device and the UAV’s limited storage capacity. The formulated optimization problem is troublesome to solve due to its non-convexity and combinatorial nature. Toward appealing applications, we first relax binary variables into continuous values and transform the original problem into a more computationally tractable form. By leveraging inner approximation framework, we derive newly approximated functions for non-convex parts and then develop a simple yet efficient iterative algorithm for its solutions. Next, we attempt to maximize the total throughput subject to the number of served IoT devices. Finally, numerical results show that the proposed algorithms significantly outperform benchmark approaches in terms of the number of served IoT devices and the amount of collected data. [less ▲]

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See detailEnergy-efficient deployment in wireless edge caching
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Wireless Edge Caching: Modeling, Analysis, and Optimization (2020)

In this chapter, we investigate the performance of edge-caching wireless networks by taking into account the caching capability when designing the signal transmission. We consider hierarchical caching ... [more ▼]

In this chapter, we investigate the performance of edge-caching wireless networks by taking into account the caching capability when designing the signal transmission. We consider hierarchical caching systems in which the contents can be prefetched at both user terminals or the base station and investigate the energy performance under two notable uncoded and coded caching strategies. The backhaul and access throughputs are derived for both caching policies for arbitrary values of base station and user cache sizes from which closed-form expressions for the corresponding system energy efficiency (EE) are obtained. Furthermore, we propose two optimization problems to maximize the system EE and minimize the content delivery time subject to some given quality of service requirements. [less ▲]

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See detailOn the Spectral and Energy Efficiencies of Full-Duplex Cell-Free Massive MIMO
Nguyen, Hieu V.; Nguyen, van Dinh UL; Dobre, Octavia A. et al

in IEEE Journal on Selected Areas in Communications (2020), 38(8), 1698-1718

In-band full-duplex (FD) operation is practically more suited for short-range communications such as WiFi and small-cell networks, due to its current practical limitations on the self-interference ... [more ▼]

In-band full-duplex (FD) operation is practically more suited for short-range communications such as WiFi and small-cell networks, due to its current practical limitations on the self-interference cancellation. In addition, cell-free massivemultiple-input multiple-output (CF-mMIMO) is a new and scalable version of MIMO networks, which is designed to bring service antennas closer to end user equipments (UEs). To achieve higher spectral and energy efficiencies (SE-EE) of a wireless network, it is of practical interest to incorporate FD capability into CF-mMIMO systems to utilize their combined benefits. We formulate a novel and comprehensive optimization problem for the maximization of SE and EE in which power control, access point-UE (AP-UE) association and AP selection are jointly optimized under a realistic power consumption model, resulting in a difficult class of mixed-integer nonconvex programming. To tackle the binary nature of the formulated problem, we propose an efficient approach by exploiting a strong coupling between binary and continuous variables, leading to a more tractable problem. In this regard, two low-complexity transmission designs based on zero-forcing (ZF) are proposed. Combining tools from inner approximation framework and Dinkelbach method, we develop simple iterative algorithms with polynomial computational complexity in each iteration and strong theoretical performance guaranteed. Furthermore, towards a robust design for FD CFmMIMO, a novel heap-based pilot assignment algorithm is proposed to mitigate effects of pilot contamination. Numerical results show that our proposed designs with realistic parameters significantly outperform the well-known approaches (i.e., smallcell and collocated mMIMO) in terms of the SE and EE. Notably, the proposed ZF designs require much less execution time than the simple maximum ratio transmission/combining. [less ▲]

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See detailA Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues
Nguyen, Cong T.; Saputra, Yuris M.; Nguyen, Huynh Van et al

in IEEE Access (2020)

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social ... [more ▼]

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs. [less ▲]

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See detailA Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies
Nguyen, Cong T.; Saputra, Yuris M.; Nguyen, Huynh Van et al

in IEEE Access (2020), 8

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching ... [more ▼]

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice [less ▲]

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See detailJoint User Scheduling, and Precoding for Multicast Spectral Efficiency in Multigroup Multicast Systems
Bandi, Ashok UL; Mysore Rama Rao, Bhavani Shankar UL; Chatzinotas, Symeon UL et al

in International conference on signal processing and communications (SPCOM) (2020, July)

This paper studies the joint design of user scheduling and precoding for the maximization of spectral efficiency (SE) for a multigroup multicast scenario in multiuser MISO downlink channels. Noticing that ... [more ▼]

This paper studies the joint design of user scheduling and precoding for the maximization of spectral efficiency (SE) for a multigroup multicast scenario in multiuser MISO downlink channels. Noticing that the existing definition of SE fails to account for group sizes, a new metric called multicast spectral efficiency (MC-SE) is proposed. In this context, the joint design is considered for the maximization of MC-SE. Firstly, with the help of binary scheduling variables, the joint design problem is formulated as a mixed-integer non-linear programming problem such that it facilitates the joint update of scheduling and precoding variables. Further, useful reformulations are proposed to reveal the hidden difference-of-convex/concave structure of the problem. Thereafter, we propose a convex-concave procedure based iterative algorithm with convergence guarantees to a stationary point. Finally, we compare different aspects namely MC-SE, SE and number of scheduled users through Monte-Carlo simulations. [less ▲]

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See detailBeam Illumination Pattern Design in Satellite Networks: Learning and Optimization for Efficient Beam Hopping
Lei, Lei UL; Lagunas, Eva UL; Yuan, Yaxiong UL et al

in IEEE Access (2020)

Beam hopping (BH) is considered to provide a high level of flexibility to manage irregular and time-varying traffic requests in future multi-beam satellite systems. In BH optimization, adopting ... [more ▼]

Beam hopping (BH) is considered to provide a high level of flexibility to manage irregular and time-varying traffic requests in future multi-beam satellite systems. In BH optimization, adopting conventional iterative heuristics may have their own limitations in providing timely solutions, and directly using data-driven technique to approximate optimization variables may lead to constraint violation and degraded performance. In this paper, we explore a combined learning-and-optimization (L&O) approach to provide an efficient, feasible, and near-optimal solution. The investigations are from the following aspects: 1) Integration ofBH optimization and learning techniques; 2) Features to be learned in BH design; 3) How to address the feasibility issue incurred by machine learning. We provide numerical results and analysis to show that the learning component in L&O significantly accelerates the procedure of identifying promising BH patterns, resulting in reduced computing time from seconds/minutes to milliseconds level. The identified learning feature enables high accuracy in predictions. In addition, the optimization component in L&O guarantees the solution’s feasibility and improves the overall performance with around 5% gap to the optimum. [less ▲]

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See detailCoarse Trajectory Design for Energy Minimization in UAV-enabled Wireless Communications with Latency Constraints
Tran Dinh, Hieu UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Vehicular Technology (2020)

In this paper, we design the UAV trajectory to minimize the total energy consumption while satisfying the requested timeout (RT) requirement and energy budget, which is accomplished via jointly optimizing ... [more ▼]

In this paper, we design the UAV trajectory to minimize the total energy consumption while satisfying the requested timeout (RT) requirement and energy budget, which is accomplished via jointly optimizing the path and UAV’s velocities along subsequent hops. The corresponding optimization problem is difficult to solve due to its non-convexity and combinatorial nature. To overcome this difficulty, we solve the original problem via two consecutive steps. Firstly, we propose two algorithms, namely heuristic search, and dynamic programming (DP) to obtain a feasible set of paths without violating the GU’s RT requirements based on the traveling salesman problem with time window (TSPTW). Then, they are compared with exhaustive search and traveling salesman problem (TSP) used as reference methods. While the exhaustive algorithm achieves the best performance at a high computation cost, the heuristic algorithm exhibits poorer performance with low complexity. As a result, the DP is proposed as a practical trade-off between the exhaustive and heuristic algorithms. Specifically, the DP algorithm results in near-optimal performance at a much lower complexity. Secondly, for given feasible paths, we propose an energy minimization problem via a joint optimization of the UAV’s velocities along subsequent hops. Finally, numerical results are presented to demonstrate the effectiveness of our proposed algorithms. The results show that the DP-based algorithm approaches the exhaustive search’s performance with a significantly reduced complexity. It is also shown that the proposed solutions outperform the state-of-theart benchmarks in terms of both energy consumption and outage performance. [less ▲]

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See detailA Novel Heap-based Pilot Assignment for Full Duplex Cell-Free Massive MIMO with Zero-Forcing
Nguyen, Van Hieu; Nguyen, van Dinh UL; Dobre, Octavia A. et al

in IEEE International Conference on Communications (2020, June 07)

This paper investigates the combined benefits of full-duplex (FD) and cell-free massive multiple-input multipleoutput (CF-mMIMO), where a large number of distributed access points (APs) having FD ... [more ▼]

This paper investigates the combined benefits of full-duplex (FD) and cell-free massive multiple-input multipleoutput (CF-mMIMO), where a large number of distributed access points (APs) having FD capability simultaneously serve numerous uplink and downlink user equipments (UEs) on the same time-frequency resources. To enable the incorporation of FD technology in CF-mMIMO systems, we propose a novel heapbased pilot assignment algorithm, which not only can mitigate the effects of pilot contamination but also reduce the involved computational complexity. Then, we formulate a robust design problem for spectral efficiency (SE) maximization in which the power control and AP-UE association are jointly optimized, resulting in a difficult mixed-integer nonconvex programming. To solve this problem, we derive a more tractable problem before developing a very simple iterative algorithm based on inner approximation method with polynomial computational complexity. Numerical results show that our proposed methods with realistic parameters significantly outperform the existing approaches in terms of the quality of channel estimate and SE. [less ▲]

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See detailUnified Framework for Secrecy Characteristics with Mixture of Gaussian (MoG) Distribution
Kong, Long UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Wireless Communications Letters (2020)

The mixture of Gaussian (MoG) distribution was proposed to model the wireless channels by implementing the completely unsupervised expectation-maximization (EM) learning algorithm. With the high ... [more ▼]

The mixture of Gaussian (MoG) distribution was proposed to model the wireless channels by implementing the completely unsupervised expectation-maximization (EM) learning algorithm. With the high convenience for density estimation applications, the focus of this letter is supposed to investigate the secrecy metrics, including secrecy outage probability (SOP), the lower bound of SOP, the probability of non-zero secrecy capacity (PNZ), and the average secrecy capacity (ASC) from the information-theoretic perspective. The above-mentioned metrics are derived with simple and unified closed-form expressions. The effectiveness of our obtained analytical expressions are successfully examined and compared with Monte-Carlo simulations. One can conclude that this letter provides a simple but effective closed-form secrecy analysis solution exploiting the MoG distribution. [less ▲]

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See detailPerceptive Packet Scheduling for Carrier Aggregation in Satellite Communication Systems
Al-Hraishawi, Hayder UL; Maturo, Nicola UL; Lagunas, Eva UL et al

in IEEE International Conference on Communications, June 2020. (2020, June)

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See detailSuccessive Convex Approximation for Transmit Power Minimization in SWIPT-Multicast Systems
Gautam, Sumit UL; Lagunas, Eva UL; Kisseleff, Steven UL et al

Scientific Conference (2020, June)

We propose a novel technique for total transmit power minimization and optimal precoder design in wireless multi-group (MG) multicasting (MC) systems. The considered framework consists of three different ... [more ▼]

We propose a novel technique for total transmit power minimization and optimal precoder design in wireless multi-group (MG) multicasting (MC) systems. The considered framework consists of three different systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures, energy harvesting (EH) only users with non-linear EH module, and users with joint ID and EH capabilities having separate units for the two operations, respectively. Each user is categorized under unique group(s), which can be of MC type specifically meant for ID users, and/or an energy group consisting of EH explicit users. The joint ID and EH users are a part of the (last) EH group as well as any one of the MC groups distinctly. In this regard, we formulate an optimization problem to minimize the total transmit power with optimal precoder designs for the three aforementioned scenarios, under constraints on minimum signal-to-interference-plus-noise ratio and harvested energy by the users with respective demands. The problem may be adapted to the well-known semi-definite program, which can be typically solved via relaxation of rank-1 constraint. However, the relaxation of this constraint may in some cases lead to performance degradation, which increases with the rank of the solution obtained from the relaxed problem. Hence, we develop a novel technique motivated by the feasible-point pursuit and successive convex approximation method in order to address the rank-related issue. The benefits of the proposed method are illustrated under various operating conditions and parameter values, with comparison between the three above-mentioned scenarios. [less ▲]

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See detailBoosting SWIPT via Symbol-Level Precoding
Gautam, Sumit UL; Krivochiza, Jevgenij UL; Haqiqatnejad, Alireza UL et al

Scientific Conference (2020, May 29)

In this paper, we investigate a simultaneous wireless information and power transmission (SWIPT) system, wherein a single multi-antenna transmitter serves multiple single-antenna users which employ the ... [more ▼]

In this paper, we investigate a simultaneous wireless information and power transmission (SWIPT) system, wherein a single multi-antenna transmitter serves multiple single-antenna users which employ the power-splitting (PS) receiver architecture. We formulate a Symbol-Level Precoding (SLP) based transmit power minimization problem dependent on the minimum signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) thresholds. We solve the corresponding non-negative convex quadratic optimization problem per time frame of transmitted symbols and study the benefits of proposed design under Zero-Forcing (ZF) Precoding, Direct Demand SLP (DD-SLP), and Squared-Root Demand SLP (RD-SLP) techniques. A static PS-ratio is fixed according to the SINR and EH demands to enable the segregation of intended received signals for information decoding (ID) and EH, respectively. Numerical results show the property conservation of SINR-enhancement via SLP at the ID unit while increasing the harvested energy at each of the end-users. [less ▲]

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See detailDeep Channel Learning For Large Intelligent Surfaces Aided mm-Wave Massive MIMO Systems
Elbir, Ahmet M.; Papazafeiropoulos, Anastasios; Kourtessis, Pandelis et al

in IEEE Wireless Communications Letters (2020), 9(Sept. 2020), 1447-1451

This letter presents the first work introducing a deep learning (DL) framework for channel estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple-output) systems. A ... [more ▼]

This letter presents the first work introducing a deep learning (DL) framework for channel estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple-output) systems. A twin convolutional neural network (CNN) architecture is designed and it is fed with the received pilot signals to estimate both direct and cascaded channels. In a multi-user scenario, each user has access to the CNN to estimate its own channel. The performance of the proposed DL approach is evaluated and compared with state-of-the-art DL-based techniques and its superior performance is demonstrated. [less ▲]

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See detail'Faster-than-Nyquist Signaling via Spatiotemporal Symbol-Level Precoding for Multi-User MISO Redundant Transmissions
Alves Martins, Wallace UL; Spano, Danilo UL; Chatzinotas, Symeon UL et al

in International Conference on Acoustics, Speech, and Signal Processing (ICASSP-2020), Barcelona 4-8 May 2020 (2020, May)

This paper tackles the problem of both multi-user and intersymbol interference stemming from co-channel users transmitting at a faster-than-Nyquist (FTN) rate in multi-antenna downlink transmissions. We ... [more ▼]

This paper tackles the problem of both multi-user and intersymbol interference stemming from co-channel users transmitting at a faster-than-Nyquist (FTN) rate in multi-antenna downlink transmissions. We propose a framework for redundant block-based symbol-level precoders enabling the trade-off between constructive and destructive multi-user and interblock interference (IBI) effects at the single-antenna user terminals. Redundant elements are added as guard interval to handle IBI destructive effects. It is shown that, within this framework, accelerating the transmissions via FTN signaling improves the error-free spectral efficiency, up to a certain acceleration factor beyond which the transmitted information cannot be perfectly recovered by linear filtering followed by sampling. Simulation results corroborate that the proposed spatiotemporal symbol-level precoding can change the amount of added redundancy from zero (full IBI) to half (IBI-free) the equivalent channel order, so as to achieve a target balance between spectral and energy efficiencies. [less ▲]

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See detailJoint Optimization for PS-based SWIPT Multiuser Systems with Non-linear Energy Harvesting
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Gautam, Sumit UL et al

in IEEE Wireless Communications and Networking Conference (WCNC), Seoul, 25-38 May 2020 (2020, May)

In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) multiuser systems, in which a base station serves a set of users with both information and ... [more ▼]

In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) multiuser systems, in which a base station serves a set of users with both information and energy simultaneously via a power splitting (PS) mechanism. To capture realistic scenarios, a nonlinear energy harvesting (EH) model is considered. In particular, we jointly design the PS factors and the beamforming vectors in order to maximize the total harvested energy, subjected to rate requirements and a total transmit power budget. To deal with the inherent non-convexity of the formulated problem, an iterative optimization algorithm is proposed based on the inner approximation method and semidefinite relaxation (SDR), whose convergence is theoretically guaranteed. Numerical results show that the proposed scheme significantly outperforms the baseline max-min based SWIPT multicast and fixed-power PS designs. [less ▲]

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See detailDeep Learning for Beam Hopping in Multibeam Satellite Systems
Lei, Lei UL; Lagunas, Eva UL; Yuan, Yaxiong UL et al

in IEEE 91st Vehicular Technology Conference (VTC2020-Spring) (2020, May)

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See detailTowards Power-Efficient Aerial Communicationsvia Dynamic Multi-UAV Cooperation
Xiang, Lin; Lei, Lei UL; Chatzinotas, Symeon UL et al

in IEEE Wireless Communications and Networking Conference (WCNC) 2020 (2020, May)

Detailed reference viewed: 50 (0 UL)