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A technique to implement true-sample-and-hold circuits that hold the output for almost the entire clock cycle without resetting to zero is introduced, alleviating the slew rate requirement on the op-amp. It is based on a Miller op-amp with an auxiliary output stage that increases power dissipation by only 1.3%. The circuit is offset-compensated and has close to rail-to-rail swing. Experimental results of a test chip prototype in 130nm CMOS technology with 0.3mW power dissipation are provided, which validate the proposed technique.

This article presents a method for selecting the best battery sizing based on an optimal market participation strategy in a hybrid renewable power plant. The proposed formulation considers different scenarios to ensure the reserve provision compliance and includes two terms. The first one maximizes the day-ahead and automatic frequency restoration reserve (aFRR) market revenues. The second minimizes the battery degradation, accounting for both cycling and calendar ageing effects. The Iberian Electricity Market is selected as the study case, and two different market scenarios are compared: the current market scenario and the upcoming one, in which the upward and downward aFRR band offers are independent. The operation of a set of batteries is simulated until their end of life, and results reveal that energy/power ratios higher than 3 h for the current market scenario, and than 4 h for the upcoming one, are less cost effective. Regarding the best battery energy storage systems sizing, the selection varies considering incomes or profitability criteria. Moreover, keeping the current prices, in the upcoming market scenario hybrid renewable power plants are encouraged to participate more in the downward than in the upward aFRR market. [ABSTRACT FROM AUTHOR]

The realization of photonic microwave oscillators using optomechanical cavities has recently become a reality. By pumping the cavity with a blue-detuned laser, the so-called phonon lasing regime - in which a mechanical resonance is amplified beyond losses - can be reached and the input signal gets modulated by highly-coherent tones at integer multiples of the mechanical resonance. Implementing optomechanical cavities on released films with high index of refraction can lead to optical modes at telecom wavelengths and mechanical resonances in the GHz scale, resulting in highly-stable signals in the microwave domain upon photodetection. Owing to the extreme compactness of such cavities, application in satellite communications (SATCOM) seems highly appropriate, but no experiments have been reported so far. In this paper, an optomechanical microwave oscillator (OMO) built on a micron-scale silicon optomechanical crystal cavity is characterized and tested in a real SATCOM testbed. Using a blue-detuned laser, the OMO is driven into a phonon lasing state where multiple harmonics are generated, reaching tones up to 20 GHz. Under this regime, its practical applicability, remarkably addressing its performance as a photonic local oscillator, has been validated. The results, in addition with the advantages of extreme compactness and silicon-technology compatibility, make OMOs very promising candidates to build ultra-low weight photonics-based microwave oscillators for SATCOM applications. [ABSTRACT FROM AUTHOR]

This paper provides a summary of media distribution in the 3GPP 5G System. We provide a status overview on the basics of 5G and in particular the Release 16 technologies on 5G Media Streaming and 5G Broadcast. Particular focus in this document are the recent Release-17 activities including extensions to 5G Media Streaming and 5G Broadcast. On the former, for example the integration of edge computing into media streaming is a major focus. On the latter, 5G Broadcast is extended to support co-existence of the technology with other broadcast technologies in the UHF band. A new set of functionalities is developed under the 5G Multicast–Broadcast Services (5MBS) umbrella work item. This includes new user service and system architecture functions to support broadcast and multicast throughout the 5G system. Particular focus in this paper are the radio layer and physical layer extensions to support point-to-multipoint delivery on top of New Radio (NR). We also touch briefly on the relevance of the 5G media distribution for third party ecosystems and industry with special focus on collaboration of media verticals and the 5G ecosystem. [ABSTRACT FROM AUTHOR]

Quartz crystal microbalances (QCMs) are devices that have been proven to function as sensors for detecting specific chemical species; this usually requires that the QCM is modified with a material that is capable to interact with the desired compound. Zeolites are an example of materials used as sensitive layer. This due to their capacity for selective adsorption and large surface area; moreover, they can grow directly on the QCM surface. After, the interaction between sensitive layer and analyte, there is a mass change on the QCM surface, which induces a frequency shift in the frequency generated by the QCM. However, the application of QCMs requires that some factors are considered, such as QCM functioning, wiring and surface functionalization. Even when there are commercial devices for QCM operation, a literature revision shows that some concepts are not understood, or some misconceptions are observed. In this work, the basics of QCM are discussed, from principles of operation to an application where a QCM was functionalized to work as sensor for water vapor. [ABSTRACT FROM AUTHOR]

Advanced control algorithms are of great interest in control engineering, they make it possible to guarantee the correct operation of complex systems and improve their performance under adverse operating conditions, thanks to negative output feedback. In this work, two adaptive control algorithms are shown: controllers based on Gain Scheduling and Direct Self-Tuning Regulators, using them to control the velocity of an electromagnetic accelerator and comparing their results with those obtained by a classic PID regulator when the system is operated under adverse operating conditions (setpoint changes, load changes and noise resistance). lt shows how this type of regulators can exceed the performance of classical control algorithms, making them a very attractive alternative for digital systems based on microcontrollers, whose high processing capacity allows them to be easily implemented in a wide variety of processes, including nonlinear dynamical systems. [ABSTRACT FROM AUTHOR]

As a newly emerging technology, deep learning (DL) is a very promising field in big data applications. Remote sensing often involves huge data volumes obtained daily by numerous in-orbit satellites. This makes it a perfect target area for data-driven applications. Nowadays, technological advances in terms of software and hardware have a noticeable impact on Earth observation applications, more specifically in remote sensing techniques and procedures, allowing for the acquisition of data sets with greater quality at higher acquisition ratios. This results in the collection of huge amounts of remotely sensed data, characterized by their large spatial resolution (in terms of the number of pixels per scene), and very high spectral dimensionality, with hundreds or even thousands of spectral bands. As a result, remote sensing instruments on spaceborne and airborne platforms are now generating data cubes with extremely high dimensionality, imposing several restrictions in terms of both processing runtimes and storage capacity. In this article, we provide a comprehensive review of the state of the art in DL for remote sensing data interpretation, analyzing the strengths and weaknesses of the most widely used techniques in the literature, as well as an exhaustive description of their parallel and distributed implementations (with a particular focus on those conducted using cloud computing systems). We also provide quantitative results, offering an assessment of a DL technique in a specific case study (source code available: https://github.com/mhaut/cloud-dnn-HSI). This article concludes with some remarks and hints about future challenges in the application of DL techniques to distributed remote sensing data interpretation problems. We emphasize the role of the cloud in providing a powerful architecture that is now able to manage vast amounts of remotely sensed data due to its implementation simplicity, low cost, and high efficiency compared to other parallel and distributed architectures, such as grid computing or dedicated clusters. [ABSTRACT FROM AUTHOR]

Waveguides are structures that can be used as sensors. After adding a cladding of a proper material, waveguides can be used for detecting specific chemical species. In particular, high band gap oxide semiconductors can be used as cladding for optical waveguides. In these materials, the synthesis processes are expensive or contaminant generators, for this reason novel approaches are required. This work addresses a simple synthesis method for the preparation of zinc oxide nanoparticles using Citrus reticulata extract. XRD presented only the wurtzite structure for the zinc oxide nanoparticles, while TEM showed size and shape homogeneity. The ZnO band gap was lower than commercial ZnO. Using a computer simulation and frequency dependent electrical characteristics, a waveguide model was tested. The resulting characteristics presented great parameters for using in optoelectronic sensors. Resulting ZnO NPs have negligible amounts of green matter afterwards, making this a non-toxic method. As a result, herein presented synthesis is a promising method for developing new optoelectronic sensors. These devices can be used for automatic detection of chemical species by automated systems. [ABSTRACT FROM AUTHOR]

Optoelectronic oscillators (OEO) based sensors generate low-phase-noise signals, whose frequency is in the order of GHz. These sensors are highly sensitive to parameters like strain, transverse load or temperature. Particularly, an OEO transforms a wavelength change into a frequency shift in the order of MHz. This creates a particular challenge for measuring instruments used in OEO, where novel mathematical methods for advanced processing of their signals is required. The principle of rational approximations is a frequency measurement technique based on number theory, with the fundamental property of measurement time dependent on the frequency value of input signals. This means that if the frequency of input signals increases, less time for measuring is required. This is quite useful for time-frequency measurement systems, where if more accuracy is needed, more time is required for measuring. This paper shows how the principle of rational approximations can be used in OEO based sensors, this allows to estimate the frequency shifts in a bandwidth from 6 to 600 MHz, with a maximum uncertainty of 2.5 MHz. Such an accuracy is achieved in a time as short as 0.2 μs. [ABSTRACT FROM AUTHOR]

A low voltage linear transconductor is introduced. The circuit is a pseudo differential architecture that operates with ±0.2V supplies and uses 900nA total biasing current. It employs a floating battery technique to achieve low voltage operation. The transconductor has a 1MHz bandwidth. It exhibits a SNR = 72dB, SFDR = 42dB and THD = 0.83% for a 100mVpp 10kHz sinusoidal input signal. Moreover, stability is not affected by the capacitance of the signal source. The circuit has been validated with a prototype chip fabricated in a 130nm CMOS technology. [ABSTRACT FROM AUTHOR]

Power quality in electrical systems is a basic requirement that should be guaranteed. Nonetheless, the increase of power-electronics-based applications and other nonlinear loads have induced harmonic distortion degrading the power quality; therefore, effective methods to measure and suppress such distortion need to be developed. The main contributions of this article are the following: the development of a novel fast-converging optimal estimator to determine online the harmonic components of a time-varying signal, which can be used for analysis and control purposes; the usage of the estimator to generate reference signals for an optimal control system in order to suppress the harmonics components; and the experimental validation of the proposed methodology as a feasible solution for industrial applications. The proposal considers practical assumptions such as the signal to be analyzed is corrupted with noise and contains time-varying harmonics (i.e., no steady-state condition is assumed). As an application of the harmonic estimator, the following two experimental tests are carried out: first, the optimal determination of the harmonic components of the current waveform in a nonlinear load, and second, the usage of harmonics information to mitigate them through of an active power filter, which is controlled by using an optimal trajectory tracking control scheme. [ABSTRACT FROM AUTHOR]

Despite the fact that underwater optical wireless communication (UOWC) systems are able to provide high-data rate links with high security, the performance of these systems presents several limitations related to the maximum achievable distance due to attenuation, and scattering effects. Hence, quantifying the signal attenuation, and the time-dispersion produced by such effects represents a crucial work in channel modeling. Motivated by this, we present, for the first time, a novel, and unified impulse response modeling of underwater optical scattering channels based on the superposition of one impulsive component, and one dispersive component with two degrees of freedom. We provide analytical results for channel path loss, and channel impulse response (CIR) which are validated through Monte-Carlo simulations based on photon-tracing for clear ocean, coastal, and harbor waters. In order to provide a physical insight, the developed CIR is used to compute the root-mean-square (RMS) delay spread as a function of distance, and type of water, as well as to analyze in greater detail the impact of inter-symbol interference (ISI) on the data rate. These outcomes can be used for high-speed systems design, and optimization. [ABSTRACT FROM AUTHOR]

We present the latest developments in the physical layer evolution for the transmission of Multimedia Broadcast Multicast Service (MBMS) over fifth generation (5G) cellular networks. We first provide an overview of how the MBMS physical layer has evolved during the initial releases of the Third Generation Partnership Project (3GPP) specifications and provide motivations and insights for key developments that have helped mature MBMS into a competitive broadcasting solution. We provide an overview of dedicated MBMS carriers for Multimedia Broadcast multicast service Single Frequency Network (MBSFN) transmission as well as Orthogonal Frequency Division Multiplexing (OFDM) numerologies with longer cyclic prefixes to support MBSFN transmission over large geographical areas with large distances between cooperating cell sites. Next, we describe the most recent enhancements to the MBMS physical layer, addressing advanced use cases in the recently completed release of the 3GPP specifications (Release 16). First, we describe the physical layer design for enabling MBSFN-based MBMS services for rooftop receivers with inter-site distances between cooperating cell sites as large as 125 km. In this realm, we demonstrate the need for an OFDM numerology with a 300-microsecond cyclic prefix to communicate effectively over channels with very large delay spreads. Next, we explain how support for high mobility up to 250 kmph was added to the standards by using an OFDM numerology that gracefully trades off inter-symbol interference due to large delay spreads and inter-carrier interference due to large doppler spreads to achieve better performance than existing numerologies at high speeds. Finally, we describe the enhancements that were made to the Cell Acquisition Subframe (CAS)—specifically, the introduction of larger aggregation levels for the Physical Downlink Control Channel (PDCCH) and the support of Physical Broadcast Channel (PBCH) repetitions—that significantly increase the coverage for the control and system information associated with MBMS that are carried by these subframes. [ABSTRACT FROM AUTHOR]

Constrained model predictive control (MPC) usually requires the computation of a quadratic programming problem (QP) at each sampling instant. This is computationally expensive and becomes a limitation to embed and use MPC in plants with fast sampling rates. Several special solvers for MPC problems have been proposed in the last years, but most of them focus on state-space formulations, which are very popular in academia. This paper proposes a solution based on alternated direction method of multipliers, tailored for embedded systems and applied to generalized predictive control (GPC), which is a very popular formulation in industry. Implementations issues of parallel computation are discussed in order to accelerate the time required for the operations. The implementation in an FPGA proved to be quite fast, with the observed worst case execution time of 11,54 µs for the presented example. These results contribute to embed GPC applications in processes that are typically controlled by classical controllers because of their fast dynamics. [ABSTRACT FROM AUTHOR]

Situational awareness in wireless networks refers to the availability of position information on transmitters and receivers as well as information on their propagation environments to aid wireless communications. In millimeter wave massive multiple-input multiple-output communication systems, situational awareness can significantly improve the quality and robustness of communications. In this paper, we establish a model that describes the statistical dependencies between channel state information and the position, orientation, and clock offset of a user equipment along with the locations of features in the propagation environment. Based on this model, we introduce COMPAS (COncurrent Mapping, Positioning, And Synchronization); an inference engine that can provide accurate and reliable situational awareness in millimeter wave massive multiple-input multiple-output communication systems. Numerical results show that COMPAS is able to infer the positions of an unknown and time-varying number of features in the propagation environment and, at the same time, estimate the position, orientation, and clock offset of a user equipment. [ABSTRACT FROM AUTHOR]

In this article we present options for the evolution from G.fast-based access networks to multi-gigabit access networks with a focus on solutions based on G.mgfast. The corresponding evolutions of the network architecture as well as a framework for the cost modeling are shown. The starting point for future architecture evolutions is the ongoing wireline access rollout in Switzerland. Based on this, different evolution steps are possible. These architectures are described and compared to each other based on the cost modeling framework, which shows that for certain building sizes different options are cost optimal. [ABSTRACT FROM AUTHOR]

Sampled simulation is a mature technique for reducing simulation time of single-threaded programs. Nevertheless, current sampling techniques do not take advantage of other execution models, like task-based execution, to provide both more accurate and faster simulation. Recent multi-threaded sampling techniques assume that the workload assigned to each thread does not change across multiple executions of a program. This assumption does not hold for dynamically scheduled task-based programming models. Task-based programming models allow the programmer to specify program segments as tasks which are instantiated many times and scheduled dynamically to available threads. Due to variation in scheduling decisions, two consecutive executions on the same machine typically result in different instruction streams processed by each thread. In this paper, we propose TaskPoint, a sampled simulation technique for dynamically scheduled task-based programs. We leverage task instances as sampling units and simulate only a fraction of all task instances in detail. Between detailed simulation intervals, we employ a novel fast-forwarding mechanism for dynamically scheduled programs. We evaluate different automatic techniques for clustering task instances and show that DBSCAN clustering combined with analytical performance modeling provides the best trade-off of simulation speed and accuracy. TaskPoint is the first technique combining sampled simulation and analytical modeling and provides a new way to trade off simulation speed and accuracy. Compared to detailed simulation, TaskPoint accelerates architectural simulation with 8 simulated threads by an average factor of 220x at an average error of 0.5 percent and a maximum error of 7.9 percent. [ABSTRACT FROM AUTHOR]

In the past, NLOS propagation was proven to be a source of distortion for radio-based positioning systems due to the lack of temporal and spatial resolution of previous cellular systems. Hence, every NLOS component was perceived as a perturbation for localization. Even though 5G is not yet standardized, a strong proposal, which has the potential to overcome the problem of limited temporal and spatial resolution, is the massive MIMO millimeter wave technology. We reconsider the role of NLOS components for position and orientation estimation in 5G millimeter wave MIMO systems. Our analysis is based on the concept of Fisher information. We show that for sufficiently high temporal and spatial resolution, NLOS components always provide position and orientation information that consequently increase position and orientation estimation accuracy. In addition, we show that the information gain of NLOS components depends on the actual location of the reflector or scatter. Our numerical examples suggest that the NLOS components are most informative about the position and orientation of a mobile terminal when the corresponding reflectors or scatterers are illuminated with narrow beams. [ABSTRACT FROM AUTHOR]

The control of multi-input and multioutput (MIMO) systems with multiple time delays is difficult to be done using classical control techniques, especially if the process is not open-loop stable. Model predictive control (MPC) is the natural choice in industry for this case, but its tuning and implementation are not trivial and, in general, cannot be done in the low level of the process control system. This paper aims to show a method to design MIMO filtered Smith predictors for $n \times n$ processes with multiple time delays based on the decentralized direct decoupling structure. This method allows an easy tuning of the primary controller by simplifying the problem to multiple single loops if the realizability conditions presented in the paper are met. The proposed method can also be used in MPC to remove the interactions between process variables. The effectiveness of the method is illustrated through two case studies. [ABSTRACT FROM AUTHOR]

According to the American Cancer Society the number of patients with bone tumors is growing up. The extremities of the long bones are the most affected by this disease. The common treatments are surgery (amputation), radio and chemotherapy. However, their high cost and side-effects show the necessity of new treatments. These should not only eradicate the tumor but also offer a major control over the treated area. In this sense, the microwave ablation plays an important role. A micro-coaxial slot antenna to generated thermal ablation in bone tumors is proposed. The antenna was modeled, constructed and evaluated in pig tissue. A parametric study to evaluate the effect of the blood perfusion in the thermal distributions was done. Values of bone blood perfusion among 30-1171 ml/min/kg were included in this study. Subsequently, temperature profiles and thermal distributions generated in pig bones were obtained and compared with those obtained in the model. This evaluation shows a high level of concordance; in the best cases, a difference between simulation and measurement of 0.13°C-3.83°C and 0.08°C-0.41°C was found. This study corroborates the efficiency of the models to predict the antenna behavior and the efficiency of the proposed antenna to generated thermal ablation in bone tissue. [ABSTRACT FROM AUTHOR]

The effect of an orthostatic stress on cardiovascular and respiratory complexity was investigated to detect impaired autonomic regulation in patients with vasovagal syncope (VVS). A total of 16 female patients and 12 age-matched healthy female subjects were enrolled in a passive 70° head-up tilt test. Also, 12 age-matched healthy male subjects were enrolled to study gender differences. Analysis was performed dynamically using various short-term (5 min) windows shifted by 1 min as well as by 20 min of orthostatic phase (OP) to evaluate local and global complexity. Complexity was determined over multiple time scales by the established method of refined composite multiscale entropy (RCMSE) and by a new proposed method of multiscale entropy based on symbolic dynamics (MSE-SD). Concerning heart rate variability (HRV) during OP, both methods revealed the highest complexity for female controls followed by lower complexity in male controls (p < 0.01) and by the lowest complexity in female patients (p < 0.01). For blood pressure variability (BPV), no gender differences in controls were shown by any method. However, MSE-SD demonstrated highly significantly increased BPV complexity in patients during OP (p < 0.01 on 4 time-scales after 7 min, p < 0.001 on 5 time-scales after 11 min) while RCMSE did not reveal considerable differences (p < 0.05 on 2 time scales after 7 min). Respiratory complexity was further increased in patients primary shown by MSE-SD. Findings indicated impaired autonomic regulation in VVS patients characterized by predominantly increased BPV complexity accompanied with decreased HRV complexity. In addition, results suggested extending the concept of complexity loss with disease. [ABSTRACT FROM AUTHOR]

Heterogeneous systems composed of CPUs and accelerators sharing communication channels of different performance are getting mainstream in HPC but, at the same time, they show a complexity that makes it difficult to optimize the deployment of a data parallel application. Recent analytical tools such as Functional Performance Models, combined with advanced partitioning algorithms, manage to achieve a balanced configuration by distributing the workload unevenly, according to the performance of the different processing units. Unfortunately, such uneven distribution of the computation load leads to communication unbalances that, very often, render worthless the previous workload balancing efforts. Finding the optimal communication scheme without expensive testing on the executing platform requires an analytical approach to the estimation of the communication cost of different configurations of the application. With this goal in mind, we propose and discuss an extension of the $\tau$ -Lop communication performance model to cover heterogeneous architectures. In order to provide a quantitative assessment of this extended model, we conduct experiments with two representative computational kernels, the SUMMA algorithm and the 2D wave equation solver. The $\tau$ -Lop predictions are compared against the HLogGP model and the observed costs for a variety of configurations, hardware resources and problem sizes. [ABSTRACT FROM PUBLISHER]

In this paper, a practical event-based framework for multivariable processes is introduced. The developed control algorithm is based on a Generalized Predictive Control (GPC) algorithm suitable for multiple-input multiple-output systems. The most important advantage of the proposed control scheme is the adaptability of control actions to process disturbances and process interactions. The application of the developed control system allows us to reduce the amount of messages exchanged between control system agents, what is beneficial for communication burden. Moreover, event-based approach allows us prioritizing the selected control variables, paying more attention to important variables (often related to security or costs), while neglecting the noncritical ones. This is possible through adjusting the sensor deadband value, making feasible a tradeoff between control effort and control performance. Using this approach, it is possible to keep less relevant variables within the established limits, focusing the control system attention on those critical to process operation. The analyzed event-based control technique for multivariable systems is tested through a simulation study and real experiments. The obtained results show several benefits regarding event-based control application, keeping all properties of event-based approach as well as model predictive control ones. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for estimating the energy losses due to theft and fraud in electrical distribution systems, which are known as non-technical losses caused by third parties in relation to the activities of the electrical utility. The rates of these losses are obtained by measuring certain variables in electrified randomly selected. Mathematical models for theft and fraud are obtained by means of a multiple linear regression models to develop strategies with a high degree of certainty to control and mitigate these energy losses. A real distribution system is analyzed, the system includes 10 distribution zones, 1,476,564 clients in low voltages and 53,703 electrified sectors. [ABSTRACT FROM PUBLISHER]

As performance and energy efficiency have become the main challenges for next-generation high-performance computing, asymmetric multi-core architectures can provide solutions to tackle these issues. Parallel programming models need to be able to suit the needs of such systems and keep on increasing the application’s portability and efficiency. This paper proposes two task scheduling approaches that target asymmetric systems. These dynamic scheduling policies reduce total execution time either by detecting the longest or the critical path of the dynamic task dependency graph of the application, or by finding the earliest executor of a task. They use dynamic scheduling and information discoverable during execution, fact that makes them implementable and functional without the need of off-line profiling. In our evaluation we compare these scheduling approaches with two existing state-of the art heterogeneous schedulers and we track their improvement over a FIFO baseline scheduler. We show that the heterogeneous schedulers improve the baseline by up to 1.45$\times$ in a real 8-core asymmetric system and up to 2.1$\times$ in a simulated 32-core asymmetric chip. [ABSTRACT FROM AUTHOR]

This paper presents a maximum power point tracking (MPPT) method that compensates fast, though smooth, irradiance (or temperature) changes. The proposed method belongs to the family of perturb and observe (P&O) methods as the photovoltaic (PV) voltage is intentionally perturbed to induce changes on the PV power. In consequence, the slope of the $pv$-characteristic curve can be detected, which reveals the MPP position. The perturbation is usually an increment with varying direction, which is used to update the next PV voltage reference. However, changes on irradiance (or temperature) may also cause changes on the PV power, which mix with the algorithm's intentional increment effect on the PV power. This combination of effects confuses the slope detection, which may entail a wrong decision on the next increment direction, and a considerable deviation from the MPP. The scheme presented here proposes the use of more samplings and an associated combination of increments directions before taking a decision. This additional information is used to separate the effect of irradiance (or temperature) changes from the algorithm's intentional perturbation effect. Thus, the proposed multisampling MPPT can provide effective MPP tracking despite of irradiance (or temperature) changes. The proposed scheme is experimentally tested and compared to the conventional P&O under irradiance changes. [ABSTRACT FROM PUBLISHER]

We consider the problem of estimating the frame error rate (FER) of a given memoryless binary symmetric channel by observing the success or failure of transmitted packets. Whereas FER estimation is relatively straightforward if all observations correspond to packets with equal length, the problem becomes considerably more complex when this is not the case. We develop FER estimators when transmissions of different lengths are observed, together with the Cramer–Rao lower bound (CRLB). Although the main focus is on maximum likelihood (ML) estimation, we also obtain low-complexity schemes performing close to optimal in some scenarios. In a second stage, we consider the case in which FER estimation is performed at a node different from the receiver, and incorporate the impairment of unreliable observations by considering noisy ACK/NAK feedback links. The impact of unreliable feedback is analyzed by means of the corresponding CRLB. In this setting, the ML estimator is obtained by applying the expectation–maximization algorithm to jointly estimate the error probabilities of the data and feedback links. Simulation results illustrate the benefits of the proposed estimators. [ABSTRACT FROM PUBLISHER]

This article describes the ARM Scalable Vector Extension (SVE). Several goals guided the design of the architecture. First was the need to extend the vector processing capability associated with the ARM AArch64 execution state to better address the computational requirements in domains such as high-performance computing, data analytics, computer vision, and machine learning. Second was the desire to introduce an extension that can scale across multiple implementations, both now and into the future, allowing CPU designers to choose the vector length most suitable for their power, performance, and area targets. Finally, the architecture should avoid imposing a software development cost as the vector length changes and where possible reduce it by improving the reach of compiler auto-vectorization technologies. SVE achieves these goals. It allows implementations to choose a vector register length between 128 and 2,048 bits. It supports a vector-length agnostic programming model that lets code run and scale automatically across all vector lengths without recompilation. Finally, it introduces several innovative features that begin to overcome some of the traditional barriers to autovectorization. [ABSTRACT FROM PUBLISHER]