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See detailEnergy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization
Yuan, Yaxiong UL; Lei, Lei UL; Vu, Thang Xuan UL et al

in IEEE Transactions on Vehicular Technology (2021)

In unmanned aerial vehicle (UAV) applications, the UAV's limited energy supply and storage have triggered the development of intelligent energy-conserving scheduling solutions. In this paper, we ... [more ▼]

In unmanned aerial vehicle (UAV) applications, the UAV's limited energy supply and storage have triggered the development of intelligent energy-conserving scheduling solutions. In this paper, we investigate energy minimization for UAV-aided communication networks by jointly optimizing data-transmission scheduling and UAV hovering time. The formulated problem is combinatorial and non-convex with bilinear constraints. To tackle the problem, firstly, we provide an optimal relax-and-approximate solution and develop a near-optimal algorithm. Both the proposed solutions are served as offline performance benchmarks but might not be suitable for online operation. To this end, we develop a solution from a deep reinforcement learning (DRL) aspect. The conventional RL/DRL, e.g., deep Q-learning, however, is limited in dealing with two main issues in constrained combinatorial optimization, i.e., exponentially increasing action space and infeasible actions. The novelty of solution development lies in handling these two issues. To address the former, we propose an actor-critic-based deep stochastic online scheduling (AC-DSOS) algorithm and develop a set of approaches to confine the action space. For the latter, we design a tailored reward function to guarantee the solution feasibility. Numerical results show that, by consuming equal magnitude of time, AC-DSOS is able to provide feasible solutions and saves 29.94% energy compared with a conventional deep actor-critic method. Compared to the developed near-optimal algorithm, AC-DSOS consumes around 10% higher energy but reduces the computational time from minute-level to millisecond-level. [less ▲]

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See detailTrend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Mehrizi Rahmat Abadi, Sajad UL; X. Vu, Thang; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), (4369),

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See detailOutage Probability Analysis of IRS-Assisted Systems Under Spatially Correlated Channels
Van Chien, Trinh; Papazafeiropoulos, Anastasios K.; Thanh Tu, Lam et al

in IEEE Wireless Communications Letters (2021), 10(8), 1815-1819

This letter investigates the impact of spatial channel correlation on the outage probability of intelligent reflecting surface (IRS)-assisted single-input single-output (SISO) communication systems. In ... [more ▼]

This letter investigates the impact of spatial channel correlation on the outage probability of intelligent reflecting surface (IRS)-assisted single-input single-output (SISO) communication systems. In particular, we derive a novel closed-form expression of the outage probability for arbitrary phase shifts and correlation matrices of the indirect channels. To shed light on the impact of the spatial correlation, we further attain the closed-form expressions for two common scenarios met in the literature when the large-scale fading coefficients are expressed by the loss over a propagation distance. Numerical results validate the tightness and effectiveness of the closed-form expressions. Furthermore, the spatial correlation offers significant decreases in the outage probability as the direct channel is blocked. [less ▲]

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See detail5G-SpaceLab
Querol, Jorge UL; Abdalla, Abdelrahman UL; Bokal, Zhanna UL et al

Poster (2021, April 19)

The new phase of space exploration involves a growing number of human and robotic missions with varying communication and service requirements. Continuous, maximum coverage of areas where activities are ... [more ▼]

The new phase of space exploration involves a growing number of human and robotic missions with varying communication and service requirements. Continuous, maximum coverage of areas where activities are concentrated and orbiting missions (single spacecraft or constellations) around the Earth, Moon or Mars will be particularly challenging. The standardization of the 5G Non-Terrestrial Networks (NTN) has already begun [1], and nothing prevents 5G from becoming a common communications standard supporting space resource missions [2]. The 5G Space Communications Lab (5G-SpaceLab) is an interdisciplinary experimental platform, funded by the Luxembourg Space Agency and is part of the Space Research Program of SnT. The lab allows users to design and emulate realistic space communications and control scenarios for the next-generation of space applications. The capabilities of the 5G-SpaceLab testbed combine the experience of different disciplines including space communications, space and satellite mission design, and space robotics. The most relevant include the demonstration of SDR 5G NTN terminals including NB-IoT, emulation of space communications channel scenarios (e.g. link budget, delay, Doppler…), small satellite platform and payload design and testing, satellite swarm flight formation, lunar rover and robotic arm control and AI-powered telerobotics. Earth-Moon communications is one of the scenarios demonstrated in the 5G-SpaceLab. Bidirectional communication for the teleoperation of lunar rovers for near real-time operations including data collection and sensors feedback will be tested. AI-based approaches for perception and control will be developed to overcome communication delays and to provide safer, trustworthy, and efficient remote control of the rovers. [1] 3GPP Release 17 Timeline. [Online]. Available: https://www.3gpp.org/release-17 [2] Nokia, Nokia selected by NASA to build first ever cellular network on the Moon. [Online]. Available: https://www.nokia.com/about-us/news/releases/2020/10/19/nokia-selected-by-nasa-to-build-first-ever-cellular-network-on-the-moon/ [less ▲]

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See detailActor‑critic learning‑based energy optimization for UAV access and backhaul networks
Yuan, Yaxiong UL; Lei, Lei UL; Vu, Thang Xuan UL et al

in EURASIP Journal on Wireless Communications and Networking (2021)

In unmanned aerial vehicle (UAV)-assisted networks, UAV acts as an aerial base station which acquires the requested data via backhaul link and then serves ground users (GUs) through an access network. In ... [more ▼]

In unmanned aerial vehicle (UAV)-assisted networks, UAV acts as an aerial base station which acquires the requested data via backhaul link and then serves ground users (GUs) through an access network. In this paper, we investigate an energy minimization problem with a limited power supply for both backhaul and access links. The difficul- ties for solving such a non-convex and combinatorial problem lie at the high compu- tational complexity/time. In solution development, we consider the approaches from both actor-critic deep reinforcement learning (AC-DRL) and optimization perspectives. First, two offline non-learning algorithms, i.e., an optimal and a heuristic algorithms, based on piecewise linear approximation and relaxation are developed as benchmarks. Second, toward real-time decision-making, we improve the conventional AC-DRL and propose two learning schemes: AC-based user group scheduling and backhaul power allocation (ACGP), and joint AC-based user group scheduling and optimization-based backhaul power allocation (ACGOP). Numerical results show that the computation time of both ACGP and ACGOP is reduced tenfold to hundredfold compared to the offline approaches, and ACGOP is better than ACGP in energy savings. The results also verify the superiority of proposed learning solutions in terms of guaranteeing the feasibility and minimizing the system energy compared to the conventional AC-DRL. [less ▲]

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See detailBLER-based Adaptive Q-learning for Efficient Random Access in NOMA-based mMTC Networks
Tran, Duc Dung UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL

in Proceedings of 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) (2021, April)

The ever-increasing number of machine-type communications (MTC) devices and the limited available radio resources are leading to a crucial issue of radio access network (RAN) congestion in upcoming 5G and ... [more ▼]

The ever-increasing number of machine-type communications (MTC) devices and the limited available radio resources are leading to a crucial issue of radio access network (RAN) congestion in upcoming 5G and beyond wireless networks. Thus, it is crucial to investigate novel techniques to minimize RAN congestion in massive MTC (mMTC) networks while taking the underlying short-packet communications (SPC) into account. In this paper, we propose an adaptive Q-learning (AQL) algorithm based on block error rate (BLER), an important metric in SPC, for a non-orthogonal multiple access (NOMA) based mMTC system. The proposed method aims to efficiently accommodate MTC devices to the available random access (RA) slots in order to significantly reduce the possible collisions, and subsequently to enhance the system throughput. Furthermore, in order to obtain more practical insights on the system design, the scenario of imperfect successive interference cancellation (ISIC) is considered as compared to the widely-used perfect SIC assumption. The performance of the proposed AQL method is compared with the recent Q-learning solutions in the literature in terms of system throughput over a range of parameters such as the number of devices, blocklength, and residual interference caused by ISIC, along with its convergence evaluation. Our simulation results illustrate the superiority of the proposed method over the existing techniques, in the scenarios where the number of devices is higher than the number of available RA time-slots. [less ▲]

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See detailModeling and Optimization of RF-Energy Harvesting-assisted Quantum Battery System
Gautam, Sumit UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

Poster (2021, April)

The quest for finding a small-sized energy supply to run the small-scale wireless gadgets, with almost an infinite lifetime, has intrigued humankind since past several decades. In this context, the ... [more ▼]

The quest for finding a small-sized energy supply to run the small-scale wireless gadgets, with almost an infinite lifetime, has intrigued humankind since past several decades. In this context, the concept of Quantum batteries has come into limelight more recently to serve the purpose. However, the main issue revolving around the closed-system design of Quantum batteries is to ensure a loss-less environment, which is extremely difficult to realize in practice. In this paper, we present the modeling and optimization aspects of a Radio-Frequency (RF) Energy Harvesting (EH) assisted Quantum battery, wherein several EH modules (in the form of micro- or nano- sized integrated circuits (ICs)) help each of the involved Quantum sources achieve the so-called quasi-stable state. Specifically, a micro-controller manages the overall harvested energy from the RF-EH ICs and a photon emitting device, such that the emitted photons are absorbed by the electrons in the Quantum sources. In order to precisely model and optimize the considered framework, we formulate a transmit power minimization problem for an RF-based wireless system to optimize the number of RF-EH ICs under the given EH constraints at the Quantum battery-enabled wireless device. We obtain an analytical solution to the above-mentioned problem using a rational approach, while additionally seeking another solution obtained via a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results by taking a range of system parameters into account. [less ▲]

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See detailOn the Exploration and Exploitation Trade-off in Cooperative Caching-enabled Networks
Bommaraveni, Srikanth; Gautam, Sumit; Vu, Thang Xuan UL et al

in IEEE WCNC 2021 proceeding (2021, April)

Edge-caching is considered as a promising solution to address network congestion and reduce delivery latency in the future by bringing the relevant contents close to users. In this context, the commonly ... [more ▼]

Edge-caching is considered as a promising solution to address network congestion and reduce delivery latency in the future by bringing the relevant contents close to users. In this context, the commonly used notion involves the storage of the most popular contents in the cache, while consequently increasing the cache hit ratio (CHR). In the majority of prior works, the content popularity is assumed to be perfectly known and often a priori. However, in reality, the content popularity has to be explored especially for uncertain contents, such as new entrants and fast varying items. In this paper, we develop a framework to analyze the joint exploration and exploitation trade-off by caching both popular and uncertain contents to enable more efficient content caching. Particularly, we formulate an optimization problem to maximize the trade-off between exploration and exploitation subject to the maximum storage capacity, guaranteed CHR, and back-haul energy budget constraints. Further, we solve the formulated mixed-integer combinatorial problem using branch-and-bound optimizer by relaxing the binary to box constraints. The superiority in performance of the proposed method over the state-of-the-art is demonstrated in terms of the CHR and back-haul energy on a realistic Movie-lens dataset. [less ▲]

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See detailOn the Secrecy Performance of NOMA-Based Integrated Satellite Multiple-Terrestrial Relay Networks With Hardware Impairments
Guo, Kefeng; An, Kang; Zhou, Feng et al

in IEEE Transactions on Vehicular Technology (2021), 70

Integrated satellite terrestrial networks and non-orthogonal multiple access (NOMA) have been confirmed to be promising and effective approaches to achieve substantial performance gains for future ... [more ▼]

Integrated satellite terrestrial networks and non-orthogonal multiple access (NOMA) have been confirmed to be promising and effective approaches to achieve substantial performance gains for future wireless paradigms. This paper studies the effect of hardware impairments (HIs) on the secrecy performance of NOMA-based integrated satellite multiple-terrestrial relay networks (ISMTRNs). Particularly, we consider two important wiretapping cases: Case I, colluding case: all eavesdroppers cooperatively overhear the information; and Case II, non-colluding case: one eavesdropper with the best wiretapping quality is chosen to overhear the main channel information. Specially, the closed-form expressions for the secrecy outage probability (SOP) of the considered NOMA-based ISMTRNs in the presence of the above two eavesdropping cases and partial relay selection scheme are obtained. To obtain further insights in high signal-to-noise ratios (SNRs) regime, the asymptotic analysis of SOP with two considered cases are also derived, which give efficient means to evaluate the benefit of NOMA scheme and the impacts of HIs on the SOP. Moreover, we obtain Monte Carlo (MC) simulations for the secrecy energy efficiency (SEE). [less ▲]

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See detailTowards the assessment of realistic hybrid precoding in millimeter wave MIMO systems with hardware impairments
Papazafeiropoulos, Anastasios K; Papageorgiou, Georgios K; Kolawole, Oluwatayo Y et al

in IET Communications (2021), 15(12), 1606-1619

Hybrid processing in millimeter wave (mmWave) communication has been proposed as a solution to reduce the cost and energy consumption by reducing the number of radio-frequency (RF) chains. However, the ... [more ▼]

Hybrid processing in millimeter wave (mmWave) communication has been proposed as a solution to reduce the cost and energy consumption by reducing the number of radio-frequency (RF) chains. However, the impact of the inevitable residual transceiver hardware impairments (RTHIs), including the residual additive transceiver hardware impairments (RATHIs) and the amplified thermal noise (ATN), has not been sufficiently studied in mmWave hybrid processing. In this work, the hybrid precoder and combiner are designed, which include both digital and analog processing by taking into account the RATHIs and the ATN. In particular, a thorough study is provided to shed light on the degradation of the spectral efficiency (SE) of the practical system. The outcomes show the steady degradation of the performance by the ATN across all SNR values, which becomes increasingly critical for higher values of its variance. Furthermore, it is shown that RATHIs result in degradation of the system only in the high SNR regime. Hence, their impact in mmWave system operating at low SNRs might be negligible. Moreover, an increase concerning the number of streams differentiates the impact between the transmit and receive RATHIs with the latter having a more severe effect. [less ▲]

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See detailJoint Beam-Hopping Scheduling and Power Allocation in NOMA-Assisted Satellite Systems
Wang, Anyue UL; Lei, Lei UL; Lagunas, Eva UL et al

Scientific Conference (2021, March 31)

In this paper, we investigate potential synergies of non-orthogonal multiple access (NOMA) and beam hopping (BH) for multi-beam satellite systems. The coexistence of BH and NOMA provides time-power-domain ... [more ▼]

In this paper, we investigate potential synergies of non-orthogonal multiple access (NOMA) and beam hopping (BH) for multi-beam satellite systems. The coexistence of BH and NOMA provides time-power-domain flexibilities in mitigating a practical mismatch effect between offered capacity and requested traffic per beam. We formulate the joint BH scheduling and NOMA-based power allocation problem as mixed-integer nonconvex programming. We reveal the xponential-conic structure for the original problem, and reformulate the problem to the format of mixed-integer conic programming (MICP), where the optimum can be obtained by exponential-complexity algorithms. A greedy scheme is proposed to solve the problem on a timeslot-by-timeslot basis with polynomial-time complexity. Numerical results show the effectiveness of the proposed efficient suboptimal algorithm in reducing the matching error by 62.57% in average over the OMA scheme and achieving a good trade-off between computational complexity and performance compared to the optimal solution. [less ▲]

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See detailReconfigurable Intelligent Surface Optimal Placement in Millimeter-Wave Networks
Ntontin, Konstantinos UL; Boulogeorgos, Alexandros-Apostolos A.; Selimis, Dimitrios et al

in IEEE Open Journal of the Communications Society (2021), 2

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the ... [more ▼]

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the relationship between the transmission beam footprint at the RIS plane and the RIS size. Subsequently, based on the model we derive the end-to-end expression of the received signal power and, furthermore, provide approximate closed-form expressions in the case that the RIS size is either much smaller or at least equal to the transmission beam footprint. Moreover, building upon the expressions, we derive the optimal RIS placement that maximizes the end-to-end signal-to-noise ratio. Finally, we substantiate the analytical findings by means of simulations, which reveal important trends regarding the optimal RIS placement according to the system parameters. [less ▲]

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See detailShort-Packet Communications for MIMO NOMA Systems over Nakagami-m Fading: BLER and Minimum Blocklength Analysis
Tran, Duc Dung UL; Sharma, Shree Krishna UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Vehicular Technology (2021)

Recently, ultra-reliable and low-latency communications (URLLC) using short-packets has been proposed to fulfill the stringent requirements regarding reliability and latency of emerging applications in 5G ... [more ▼]

Recently, ultra-reliable and low-latency communications (URLLC) using short-packets has been proposed to fulfill the stringent requirements regarding reliability and latency of emerging applications in 5G and beyond networks. In addition, multiple-input multiple-output non-orthogonal multiple access (MIMO NOMA) is a potential candidate to improve the spectral efficiency, reliability, latency, and connectivity of wireless systems. In this paper, we investigate short-packet communications (SPC) in a multiuser downlink MIMO NOMA system over Nakagami-m fading, and propose two antenna-user selection methods considering two clusters of users having different priority levels. In contrast to the widely-used long data-packet assumption, the SPC analysis requires the redesign of the communication protocols and novel performance metrics. Given this context, we analyze the SPC performance of MIMO NOMA systems using the average block error rate (BLER) and minimum blocklength, instead of the conventional metrics such as ergodic capacity and outage capacity. More specifically, to characterize the system performance regarding SPC, asymptotic (in the high signal-to-noise ratio regime) and approximate closed-form expressions of the average BLER at the users are derived. Based on the asymptotic behavior of the average BLER, an analysis of the diversity order, minimum blocklength, and optimal power allocation is carried out. The achieved results show that MIMO NOMA can serve multiple users simultaneously using a smaller blocklength compared with MIMO OMA, thus demonstrating the benefits of MIMO NOMA for SPC in minimizing the transmission latency. Furthermore, our results indicate that the proposed methods not only improve the BLER performance, but also guarantee full diversity gains for the respective users. [less ▲]

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See detailEfficient Federated Learning Algorithm for Resource Allocation in Wireless IoT Networks
Nguyen, van Dinh UL; Sharma, Shree Krishna UL; Vu, Thang Xuan UL et al

in IEEE Internet of Things Journal (2021), 8(5), 3394-3409

Federated learning (FL) allows multiple edge computing nodes to jointly build a shared learning model without having to transfer their raw data to a centralized server, thus reducing communication ... [more ▼]

Federated learning (FL) allows multiple edge computing nodes to jointly build a shared learning model without having to transfer their raw data to a centralized server, thus reducing communication overhead. However, FL still faces a number of challenges such as non-iid distributed data and heterogeneity of user equipments (UEs). Enabling a large number of UEs to join the training process in every round raises a potential issue of the heavy global communication burden. To address these issues, we generalize the current state-of-the-art Federated Averaging (FedAvg) by adding a weight-based proximal term to the local loss function. The proposed FL algorithm runs stochastic gradient descent in parallel on a sampled subset of the total UEs with replacement during each global round. We provide a convergence upper bound characterizing the trade-off between convergence rate and global rounds, showing that a small number of active UEs per round still guarantees convergence. Next, we employ the proposed FL algorithm in wireless Internet-of-Things (IoT) networks to minimize either total energy consumption or completion time of FL, where a simple yet efficient path-following algorithm is developed for its solutions. Finally, numerical results on unbalanced datasets are provided to demonstrate the performance improvement and robustness on the convergence rate of the proposed FL algorithm over FedAvg. They also reveal that the proposed algorithm requires much less training time and energy consumption than the FL algorithm with full user participation. These observations advocate the proposed FL algorithm for a paradigm shift in bandwidth- constrained learning wireless IoT networks. [less ▲]

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See detailJoint Symbol Level Precoding and Combining for MIMO-OFDM Transceiver Architectures Based on One-Bit DACs and ADCs
Domouchtsidis, Stavros UL; Tsinos, Christos UL; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2021), 20(7), 4601-4613

Herein, a precoding scheme is developed for orthogonal frequency division multiplexing (OFDM) transmission in multiple-input multiple-output (MIMO) systems that use one-bit digital-to-analog converters ... [more ▼]

Herein, a precoding scheme is developed for orthogonal frequency division multiplexing (OFDM) transmission in multiple-input multiple-output (MIMO) systems that use one-bit digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) at the transmitter and receiver, respectively, as a means to reduce the power consumption. Two different one-bit architectures are presented. In the first, a single user MIMO system is considered where the DACs and ADCs of the transmitter and the receiver are assumed to be one-bit and in the second, a network of analog phase shifters is added at the receiver as an additional analog-only processing step with the view to mitigate some of the effects of coarse quantization. The precoding design problem is formulated and then split into two NP-hard optimization problems, which are solved by an algorithmic solution based on the Cyclic Coordinate Descent (CCD) framework. The design of the analog post-coding matrix for the second architecture is decoupled from the precoding design and is solved by an algorithm based on the alternating direction method of multipliers (ADMM). Numerical results show that the proposed precoding scheme successfully mitigates the effects of coarse quantization and the proposed systems achieve a performance close to that of systems equipped with full resolution DACs/ADCs. [less ▲]

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See detailDesign Optimization for Low-Complexity FPGA Implementation of Symbol-Level Multiuser Precoding
Haqiqatnejad, Alireza UL; Krivochiza, Jevgenij UL; Merlano Duncan, Juan Carlos UL et al

in IEEE Access (2021), 9

This paper proposes and validates a low-complexity FPGA design for symbol-level precoding (SLP) in multiuser multiple-input single-output (MISO) downlink communication systems. In the optimal case, the ... [more ▼]

This paper proposes and validates a low-complexity FPGA design for symbol-level precoding (SLP) in multiuser multiple-input single-output (MISO) downlink communication systems. In the optimal case, the symbol-level precoded transmit signal is obtained as the solution to an optimization problem tailored for a given set of users’ data symbols. This symbol-by-symbol design, however, imposes excessive computational complexity on the system. To alleviate this issue, we aim to reduce the per-symbol complexity of the SLP scheme by developing an approximate yet computationally-efficient closed-form solution. The proposed solution allows us to achieve a high symbol throughput in real-time implementations. To develop the FPGA design, we express the proposed solution in an algorithmic way and translate it to hardware description language (HDL). We then optimize the processing to accelerate the performance and generate the corresponding intellectual property (IP) core. We provide the synthesis report for the generated IP core, including performance and resource utilization estimates and interface descriptions. To validate our design, we simulate an uncoded transmission over a downlink multiuser channel using the LabVIEW software, where the SLP IP core is implemented as a clock-driven logic (CDL) unit. Our simulation results show that a throughput of 100 Mega symbols per second per user can be achieved via the proposed SLP design. We further use the MATLAB software to produce numerical results for the conventional zero-forcing (ZF) and the optimal SLP techniques as benchmarks for comparison. Thereby, it is shown that the proposed FPGA implementation of SLP offers an improvement of up to 50 percent in power efficiency compared to the ZF precoding. Remarkably, it enjoys the same per-symbol complexity order as that of the ZF technique. We also evaluate the loss of the real-time SLP design, introduced by the algebraic approximations and arithmetic inaccuracies, with respect to the optimal scheme. [less ▲]

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See detailBackscatter-Assisted Data Offloading inOFDMA-based Wireless Powered Mobile EdgeComputing for IoT Networks
Nguyen, Xuan Phu; Tran Dinh, Hieu UL; Onireti, ‪Oluwakayode et al

in IEEE Internet of Things Journal (2021)

Mobile edge computing (MEC) has emerged as a prominent technology to overcome sudden demands on computation-intensive applications of the Internet of Things (IoT) with finite processing capabilities ... [more ▼]

Mobile edge computing (MEC) has emerged as a prominent technology to overcome sudden demands on computation-intensive applications of the Internet of Things (IoT) with finite processing capabilities. Nevertheless, the limited energy resources also seriously hinders IoT devices from offloading tasks that consume high power in active RF communications. Despite the development of energy harvesting (EH) techniques, the harvested energy from surrounding environments could be inadequate for power-hungry tasks. Fortunately, Backscatter communications (Backcom) is an intriguing technology to narrow the gap between the power needed for communication and harvested power. Motivated by these considerations, this paper investigates a backscatter-assisted data offloading in OFDMA-based wireless-powered (WP) MEC for IoT systems. Specifically, we aim at maximizing the sum computation rate by jointly optimizing the transmit power at the gateway (GW), backscatter coefficient, time-splitting (TS) ratio, and binary decision-making matrices. This problem is challenging to solve due to its non-convexity. To find solutions, we first simplify the problem by determining the optimal values of transmit power of the GW and backscatter coefficient. Then, the original problem is decomposed into two sub-problems, namely, TS ratio optimization with given offloading decision matrices and offloading decision optimization with given TS ratio. Especially, a closedform expression for the TS ratio is obtained which greatly enhances the CPU execution time. Based on the solutions of the two sub-problems, an efficient algorithm, termed the fast-efficient algorithm (FEA), is proposed by leveraging the block coordinate descent method. Then, it is compared with exhaustive search (ES), bisection-based algorithm (BA), edge computing (EC), and local computing (LC) used as reference methods. As a result, the FEA is the best solution which results in a near-globally-optimal solution at a much lower complexity as compared to benchmark schemes. For instance, the CPU execution time of FEA is about 0.029 second in a 50-user network, which is tailored for ultralow latency applications of IoT networks. [less ▲]

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See detailTowards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems
Papazafeiropoulos, A.; Ngo, H.Q.; Kourtessis, Pandelis et al

in IEEE Transactions on Green Communications and Networking (2021), 5(2), 816-831

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink ... [more ▼]

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink (DL) for optimal energy efficiency (EE). To address this fundamental topic, we assume that each access point (AP) is deployed with multiple antennas and serves multiple users on the same time-frequency resource while the APs are Poisson point process (PPP) distributed, which approaches realistically their opportunistic spatial randomness. Relied on tools from stochastic geometry, we derive a lower bound on the DL average achievable spectral efficiency (SE). Next, we consider a realistic power consumption model for CF mMIMO systems. These steps enable the formulation of a tractable optimization problem concerning the DL EE, which results in the analytical determination of the optimal pilot reuse factor, the AP density, and the number of AP antennas and users that maximize the EE. Hence, we provide useful design guidelines for CF mMIMO systems relating to fundamental system variables towards optimal EE. Among the results, we observe that an optimal pilot reuse factor and AP density exist, while larger values result in an increase of the interference, and subsequently, lower EE. Overall, it is shown that the CF mMIMO technology is a promising candidate for next-generation networks achieving simultaneously high SE and EE. [less ▲]

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See detailTowards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems
Papazafeiropoulos, Anastasios; Ngo, Hien Quoc; Kourtessis, Pandelis et al

in IEEE Transactions on Green Communications and Networking (2021), 5(2), 816-831

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink ... [more ▼]

Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink (DL) for optimal energy efficiency (EE). To address this fundamental topic, we assume that each access point (AP) is deployed with multiple antennas and serves multiple users on the same time-frequency resource while the APs are Poisson point process (PPP) distributed, which approaches realistically their opportunistic spatial randomness. Relied on tools from stochastic geometry, we derive a lower bound on the DL average achievable spectral efficiency (SE). Next, we consider a realistic power consumption model for CF mMIMO systems. These steps enable the formulation of a tractable optimization problem concerning the DL EE, which results in the analytical determination of the optimal pilot reuse factor, the AP density, and the number of AP antennas and users that maximize the EE. Hence, we provide useful design guidelines for CF mMIMO systems relating to fundamental system variables towards optimal EE. Among the results, we observe that an optimal pilot reuse factor and AP density exist, while larger values result in an increase of the interference, and subsequently, lower EE. Overall, it is shown that the CF mMIMO technology is a promising candidate for next-generation networks achieving simultaneously high SE and EE. [less ▲]

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