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See detailExperimental evaluation of RF waveform designs for Wireless Power Transfer using Software Defined Radio
Gautam, Sumit UL; Kumar, Sumit UL; Chatzinotas, Symeon UL et al

in IEEE Access (2021), 9

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest ... [more ▼]

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest in the field of wireless power transfer (WPT) using the RF range of the electromagnetic (EM) spectrum. In this paper, we experimentally investigate the aspect of real-time energy harvesting (EH) via different types of waveform designs such as orthogonal frequency division multiplexing (OFDM), square, triangular, sinusoidal, and sawtooth. We make use of a Software Defined Radio (SDR) and a Powercast P21XXCSR-EVB EH module to carry out the experiments on a practical device to assess performance. Specifically, we are interested in obtaining some insights based on the comparison between the aforementioned waveform designs from the perspectives of the separation distance between the USRP and P21XXCSR-EVB EH module, and power emission via USRP. In this vein, we perform additional subsequent experiments after reporting the practical effectiveness of the OFDM waveform, which also follows our intuitive analysis. Correspondingly, we study the effect on WPT with variable USRP transmit power, the separation distance between the USRP and EH antennas, number of OFDM sub-carriers, and multipath setting. As an application of OFDM, the effectiveness of fifth generation-new radio (5G-NR) and long-term evolution (LTE) waveforms are also tested for the WPT mechanism. The demonstration of the EH is provided in terms of the above-mentioned investigation metrics while seeking the best waveform to support WPT. [less ▲]

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See detailExperimental evaluation of RF waveform designs for Wireless Power Transfer using Software Defined Radio
Gautam, Sumit UL; Kumar, Sumit UL; Chatzinotas, Symeon UL et al

in IEEE Access (2021), 9

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest ... [more ▼]

The possibility to harvest energy from ambient radio-frequency (RF) sources has intrigued humankind for the past several decades. In this context, there has been a tremendously growing research interest in the field of wireless power transfer (WPT) using the RF range of the electromagnetic (EM) spectrum. In this paper, we experimentally investigate the aspect of real-time energy harvesting (EH) via different types of waveform designs such as orthogonal frequency division multiplexing (OFDM), square, triangular, sinusoidal, and sawtooth. We make use of a Software Defined Radio (SDR) and a Powercast P21XXCSR-EVB EH module to carry out the experiments on a practical device to assess performance. Specifically, we are interested in obtaining some insights based on the comparison between the aforementioned waveform designs from the perspectives of the separation distance between the USRP and P21XXCSR-EVB EH module, and power emission via USRP. In this vein, we perform additional subsequent experiments after reporting the practical effectiveness of the OFDM waveform, which also follows our intuitive analysis. Correspondingly, we study the effect on WPT with variable USRP transmit power, the separation distance between the USRP and EH antennas, number of OFDM sub-carriers, and multipath setting. As an application of OFDM, the effectiveness of fifth generation-new radio (5G-NR) and long-term evolution (LTE) waveforms are also tested for the WPT mechanism. The demonstration of the EH is provided in terms of the above-mentioned investigation metrics while seeking the best waveform to support WPT. [less ▲]

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See detailWideband OFDM-based Communications in Bus Topology as a Key Enabler for Industry 4.0 Networks
Gonzalez Rios, Jorge Luis UL; Torres Gómez, Jorge; Sharma, Rajesh Kumar et al

in IEEE Access (2021), 9

The Industry 4.0 paradigm conceives a cyber-physical supporting framework for the manufacturing processes in smart factories. In this context, solutions concerning the wired communications at the field ... [more ▼]

The Industry 4.0 paradigm conceives a cyber-physical supporting framework for the manufacturing processes in smart factories. In this context, solutions concerning the wired communications at the field-level have been reported which utilize either fieldbuses, which exhibit a huge distance range but a reduced data rate in a bus topology, or Ethernet-based technologies, which provide an increased data rate but reduced distance in a ring topology. To overcome this shortage, we propose the use of orthogonal frequency division multiplexing (OFDM) to significantly increase the achievable data rates over large distances in industrial bus systems. Also, we establish a novel methodology to compute the signal-to-noise ratio between arbitrary pairs of nodes, which in turn allows to compute the communication capacity. Our wideband system was validated by connecting up to 32 nodes in the distance range 100 m–1 km. Compared to fieldbuses, the results of the proposal exhibit an amazing improvement in data rate of about fifty times for 100m distance and more than ten times for 0.5 km. Moreover, with respect to Ethernet-based solutions, the results show a relevant improvement in the data rate of around five times for 100 m distance, but Ethernet-based systems cannot go beyond this distance, to which our proposal is not limited. [less ▲]

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See detailBlockPerf: A Hybrid Blockchain Emulator/Simulator Framework
Polge, Julien UL; Ghatpande, Sankalp UL; Kubler, Sylvain et al

in IEEE Access (2021), 9

Blockchain is increasingly used for registering, authenticating and validating digital assets (financial assets, real estate, etc.) and transactions, governing interactions, recording data and managing ... [more ▼]

Blockchain is increasingly used for registering, authenticating and validating digital assets (financial assets, real estate, etc.) and transactions, governing interactions, recording data and managing identification among multiple parties in a trusted, decentralized, and secure manner. Today, a large variety of blockchain technologies is expanding in order to fulfill technical and non-technical needs and requirements. Within this context, determining and most importantly evaluating the characteristics/performance of a given blockchain platform is crucial for system designers before deploying it. A number of blockchain simulators have been proposed in the literature over the past few years, as reviewed in this paper, but are often limited in several respects (lack of extensibility, do not allow for evaluating all aspects of a blockchain...). This paper extends and improves a state-of-the-art simulator (BlockSim) into a new simulator called ‘‘BlockPerf’’ to overcome those limitations. Both simulators are compared based on a real-life (benchmarking) Bitcoin scenario, whose results show that BlockPerf provides more realistic results than BlockSim, improving by around ≈50% (in average) the outcomes. [less ▲]

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See detailFrom Hume to Wuhan: An Epistemological Journey on the Problem of Induction in COVID-19 Machine Learning Models and its Impact Upon Medical Research
Vega Moreno, Carlos Gonzalo UL

in IEEE Access (2021), 9

Advances in computer science have transformed the way artificial intelligence is employed in academia, with Machine Learning (ML) methods easily available to researchers from diverse areas thanks to ... [more ▼]

Advances in computer science have transformed the way artificial intelligence is employed in academia, with Machine Learning (ML) methods easily available to researchers from diverse areas thanks to intuitive frameworks that yield extraordinary results. Notwithstanding, current trends in the mainstream ML community tend to emphasise <italic>wins</italic> over knowledge, putting the scientific method aside, and focusing on maximising metrics of interest. Methodological flaws lead to poor justification of method choice, which in turn leads to disregard the limitations of the methods employed, ultimately putting at risk the translation of solutions into real-world clinical settings. This work exemplifies the impact of the problem of induction in medical research, studying the methodological issues of recent solutions for computer-aided diagnosis of COVID-19 from chest X-Ray images. [less ▲]

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See detailEnd-to-end Precoding Validation over a Live GEO Satellite Forward Link
Krivochiza, Jevgenij UL; Merlano Duncan, Juan Carlos UL; Querol, Jorge UL et al

in IEEE Access (2021)

In this paper we demonstrate end-to-end precoded multi-user multiple-input singleoutput (MU-MISO) communications over a live GEO satellite link. Precoded communications enable full frequency reuse (FFR ... [more ▼]

In this paper we demonstrate end-to-end precoded multi-user multiple-input singleoutput (MU-MISO) communications over a live GEO satellite link. Precoded communications enable full frequency reuse (FFR) schemes in satellite communications (SATCOM) to achieve broader service availability and higher spectrum efficiency than with the conventional four-color (4CR) and twocolor (2CR) reuse approaches. In this scope, we develop an over-the-air test-bed for end-to-end precoding validations.We use an actual multi-beam satellite to transmit and receive precoded signals using the DVB-S2X standard based gateway and user terminals. The developed system is capable of end-to-end real-time communications over the satellite link including channel measurements and precompensation. It is shown, that by successfully canceling inter-user interference in the actual satellite FFR link precoding brings gains in terms of enhanced SINR and increased system goodput. [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 detailExperimental Evaluation of a Team of Multiple Unmanned Aerial Vehicles for Cooperative Construction
Real, Fran; Castaño, Angel; Torres-Gonzalez, Arturo et al

in IEEE Access (2021)

This article presents a team of multiple Unmanned Aerial Vehicles (UAVs) to perform cooperative missions for autonomous construction. In particular, the UAVs have to build a wall made of bricks that need ... [more ▼]

This article presents a team of multiple Unmanned Aerial Vehicles (UAVs) to perform cooperative missions for autonomous construction. In particular, the UAVs have to build a wall made of bricks that need to be picked and transported from different locations. First, we propose a novel architecture for multi-robot systems operating in outdoor and unstructured environments, where robustness and reliability play a key role. Then, we describe the design of our aerial platforms and grasping mechanisms to pick, transport and place bricks. The system was particularly developed for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC), where Challenge 2 consisted of building a wall cooperatively with multiple UAVs. However, our approach is more general and extensible to other multi-UAV applications involving physical interaction, like package delivery. We present not only our results in the final stage of MBZIRC, but also our simulations and field experiments throughout the previous months to the competition, where we tuned our system and assessed its performance. [less ▲]

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See detailHigh-Level Modular Autopilot Solution for Fast Prototyping of Unmanned Aerial Systems
Rodriguez de Cos, Carlos; Fernandez, Manuel Jesus; Sanchez Cuevas, Pedro Jesus UL et al

in IEEE Access (2020)

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R ... [more ▼]

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R with a backup autopilot, the computational power of an Intel R NUC mini-computer is employed to implement complex functionalities directly in Simulink R , thus including in-flight debugging, tuning and monitoring. Altogether, the presented tool provides a flexible and user-friendly high-level environment with enhanced computational capabilities, which drastically reduces the prototyping timespans of complex algorithms -between 50% and 75%, according to our long and proven experience in aerial robotics-, while preventing incidents thanks to its redundant design with a human-in-the-loop pilot on the reliable PX4. Three typical outdoor cases are carried out for validation in real-life scenarios, all mounted in a DJI © F550 platform. Full integration results and telemetry for more than 50 hours of outdoor flight tests are provided. [less ▲]

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See detailMulti-Channel Joint Forecasting-Scheduling for the Internet of Things
Rodoplu, Volkan; Nakip, Mert; Qorbanian, Roozbeh UL et al

in IEEE Access (2020), 8

We develop a methodology for Multi-Channel Joint Forecasting-Scheduling (MC-JFS) targeted at solving the Medium Access Control (MAC) layer Massive Access Problem of Machine-to-Machine (M2M) communication ... [more ▼]

We develop a methodology for Multi-Channel Joint Forecasting-Scheduling (MC-JFS) targeted at solving the Medium Access Control (MAC) layer Massive Access Problem of Machine-to-Machine (M2M) communication in the presence of multiple channels, as found in Orthogonal Frequency Division Multiple Access (OFDMA) systems. In contrast with the existing schemes that merely react to current traffic demand, Joint Forecasting-Scheduling (JFS) forecasts the traffic generation pattern of each Internet of Things (IoT) device in the coverage area of an IoT Gateway and schedules the uplink transmissions of the IoT devices over multiple channels in advance, thus obviating contention, collision and handshaking, which are found in reactive protocols. In this paper, we present the general form of a deterministic scheduling optimization program for MC-JFS that maximizes the total number of bits that are delivered over multiple channels by the delay deadlines of the IoT applications. In order to enable real-time operation of the MC-JFS system, first, we design a heuristic, called Multi-Channel Look Ahead Priority based on Average Load (MC-LAPAL), that solves the general form of the scheduling problem. Second, for the special case of identical channels, we develop a reduction technique by virtue of which an optimal solution of the scheduling problem is computed in real time. We compare the network performance of our MC-JFS scheme against Multi-Channel Reservation-based Access Barring (MC-RAB) and Multi-Channel Enhanced Reservation-based Access Barring (MC-ERAB), both of which serve as benchmark reactive protocols. Our results show that MC-JFS outperforms both MC-RAB and MC-ERAB with respect to uplink cross-layer throughput and transmit energy consumption, and that MC-LAPAL provides high performance as an MC-JFS heuristic. Furthermore, we show that the computation time of MC-LAPAL scales approximately linearly with the number of IoT devices. This work serves as a foundation for building scalable JFS schemes at IoT Gateways in the near future. [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 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 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 detailA survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art
Pham, Quoc Viet; Fang, Fang; Ha, Vu Nguyen UL et al

in IEEE Access (2020)

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic ... [more ▼]

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research. [less ▲]

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See detailA RAN Resource Slicing Mechanism for Multiplexing of eMBB and URLLC Services in OFDMA based 5G Wireless Networks
Korrai, Praveenkumar UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in IEEE Access (2020)

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two main expected services in the next generation of wireless networks. Accommodation of these two ... [more ▼]

Enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communications (URLLC) are the two main expected services in the next generation of wireless networks. Accommodation of these two services on the same wireless infrastructure leads to a challenging resource allocation problem due to their heterogeneous specifications. To address this problem, slicing has emerged as an architecture that enables a logical network with specific radio access functionality to each of the supported services on the same network infrastructure. The allocation of radio resources to each slice according to their requirements is a fundamental part of the network slicing that is usually executed at the radio access network (RAN). In this work, we formulate the RAN resource allocation problem as a sum-rate maximization problem subject to the orthogonality constraint (i.e., service isolation), latency-related constraint and minimum rate constraint while maintaining the reliability constraint with the incorporation of adaptive modulation and coding (AMC). However, the formulated problem is not mathematically tractable due to the presence of a step-wise function associated with the AMC and a binary assignment variable. Therefore, to solve the proposed optimization problem, first, we relax the mathematical intractability of AMC by using an approximation of the non-linear AMC achievable throughput, and next, the binary constraint is relaxed to a box constraint by using the penalized reformulation of the problem. The result of the above two-step procedure provides a close-to-optimal solution to the original optimization problem. Furthermore, to ease the complexity of the optimization-based scheduling algorithm, a low-complexity heuristic scheduling scheme is proposed for the efficient multiplexing of URLLC and eMBB services. Finally, the effectiveness of the proposed optimization and heuristic schemes is illustrated through extensive numerical simulations. [less ▲]

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