Samsung (United States)

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.

The ever growing traffic explosion in mobile communications has recently drawn increased attention to the large amount of underutilized spectrum in the millimeter-wave frequency bands as a potentially viable solution for achieving tens to hundreds of times more capacity compared to current 4G cellular networks. Historically, mmWave bands were ruled out for cellular usage mainly due to concerns regarding short-range and non-line-of-sight coverage issues. In this article, we present recent results from channel measurement campaigns and the development of advanced algorithms and a prototype, which clearly demonstrate that the mmWave band may indeed be a worthy candidate for next generation (5G) cellular systems. The results of channel measurements carried out in both the United States and Korea are summarized along with the actual free space propagation measurements in an anechoic chamber. Then a novel hybrid beamforming scheme and its link- and system-level simulation results are presented. Finally, recent results from our mmWave prototyping efforts along with indoor and outdoor test results are described to assert the feasibility of mmWave bands for cellular usage.

The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as 3D deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools, such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.

Almost all mobile communication systems today use spectrum in the range of 300 MHz-3 GHz. In this article, we reason why the wireless community should start looking at the 3-300 GHz spectrum for mobile broadband applications. We discuss propagation and device technology challenges associated with this band as well as its unique advantages for mobile communication. We introduce a millimeter-wave mobile broadband (MMB) system as a candidate next generation mobile communication system. We demonstrate the feasibility for MMB to achieve gigabit-per-second data rates at a distance up to 1 km in an urban mobile environment. A few key concepts in MMB network architecture such as the MMB base station grid, MMB interBS backhaul link, and a hybrid MMB + 4G system are described. We also discuss beamforming techniques and the frame structure of the MMB air interface.

Recent studies show that the state-of-the-art deep neural networks (DNNs) are vulnerable to adversarial examples, resulting from small-magnitude perturbations added to the input. Given that that emerging physical systems are using DNNs in safety-critical situations, adversarial examples could mislead these systems and cause dangerous situations. Therefore, understanding adversarial examples in the physical world is an important step towards developing resilient learning algorithms. We propose a general attack algorithm, Robust Physical Perturbations (RP2), to generate robust visual adversarial perturbations under different physical conditions. Using the real-world case of road sign classification, we show that adversarial examples generated using RP2 achieve high targeted misclassification rates against standard-architecture road sign classifiers in the physical world under various environmental conditions, including viewpoints. Due to the current lack of a standardized testing method, we propose a two-stage evaluation methodology for robust physical adversarial examples consisting of lab and field tests. Using this methodology, we evaluate the efficacy of physical adversarial manipulations on real objects. With a perturbation in the form of only black and white stickers, we attack a real stop sign, causing targeted misclassification in 100% of the images obtained in lab settings, and in 84.8% of the captured video frames obtained on a moving vehicle (field test) for the target classifier.

Development of high conductivity solid-state electrolytes for lithium ion batteries has proceeded rapidly in recent years, but incorporating these new materials into high-performing batteries has proven difficult. Interfacial resistance is now the limiting factor in many systems, but the exact mechanisms of this resistance have not been fully explained - in part because experimental evaluation of the interface can be very difficult. In this work, we develop a computational methodology to examine the thermodynamics of formation of resistive interfacial phases. The predicted interfacial phase formation is well correlated with experimental interfacial observations and battery performance. We calculate that thiophosphate electrolytes have especially high reactivity with high voltage cathodes and a narrow electrochemical stability window. We also find that a number of known electrolytes are not inherently stable but react in situ with the electrode to form passivating but ionically conducting barrier layers. As a reference for experimentalists, we tabulate the stability and expected decomposition products for a wide range of electrolyte, coating, and electrode materials including a number of high-performing combinations that have not yet been attempted experimentally.

The efficiency droop in GaInN∕GaN multiple-quantum well (MQW) light-emitting diodes is investigated. Measurements show that the efficiency droop, occurring under high injection conditions, is unrelated to junction temperature. Furthermore, the photoluminescence output as a function of excitation power shows no droop, indicating that the droop is not related to MQW efficiency but rather to the recombination of carriers outside the MQW region. Simulations show that polarization fields in the MQW and electron blocking layer enable the escape of electrons from the MQW region and thus are the physical origin of the droop. It is shown that through the use of proper quaternary AlGaInN compositions, polarization effects are reduced, thereby minimizing droop and improving efficiency.

The next chapter of the robotics revolution is well underway with the deployment of robots for a broad range of commercial use cases. Even in a myriad of applications and environments, there exists a common vocabulary of components that robots share-the need for a modular, scalable, and reliable architecture; sensing; planning; mobility; and autonomy. The Robot Operating System (ROS) was an integral part of the last chapter, demonstrably expediting robotics research with freely available components and a modular framework. However, ROS 1 was not designed with many necessary production-grade features and algorithms. ROS 2 and its related projects have been redesigned from the ground up to meet the challenges set forth by modern robotic systems in new and exploratory domains at all scales. In this Review, we highlight the philosophical and architectural changes of ROS 2 powering this new chapter in the robotics revolution. We also show through case studies the influence ROS 2 and its adoption has had on accelerating real robot systems to reliable deployment in an assortment of challenging environments.

Modern image inpainting systems, despite the significant progress, often struggle with large missing areas, complex geometric structures, and high-resolution images. We find that one of the main reasons for that is the lack of an effective receptive field in both the inpainting network and the loss function. To alleviate this issue, we propose a new method called large mask inpainting (LaMa). LaMa is based on i) a new inpainting network architecture that uses fast Fourier convolutions (FFCs), which have the image-wide receptive field; ii) a high receptive field perceptual loss; iii) large training masks, which unlocks the potential of the first two components. Our inpainting network improves the state-of-the-art across a range of datasets and achieves excellent performance even in challenging scenarios, e.g. completion of periodic structures. Our model generalizes surprisingly well to resolutions that are higher than those seen at train time, and achieves this at lower parameter&time costs than the competitive baselines. The code is available at https://github.com/saic-mdal/lama.

In this paper, for the first time we demonstrate that horizontally stacked gate-all-around (GAA) Nanosheet structure is a good candidate for the replacement of FinFET at the 5nm technology node and beyond. It offers increased W <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eff</inf> per active footprint and better performance compared to FinFET, and with a less complex patterning strategy, leveraging EUV lithography. Good electrostatics are reported at L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</inf> =12nm and aggressive 44/48nm CPP (Contacted Poly Pitch) ground rules. We demonstrate work function metal (WFM) replacement and multiple threshold voltages, compatible with aggressive sheet to sheet spacing for wide stacked sheets. Stiction of sheets in long-channel devices is eliminated. Dielectric isolation is shown on standard bulk substrate for sub-sheet leakage control. Wrap-around contact (WAC) is evaluated for extrinsic resistance reduction.

Surface plasmon resonance (SPR) plays a dominant role in real-time interaction sensing of biomolecular binding events. This book focuses on a total system description including optics, fluidics and sensor surfaces. It covers all commercial SPR systems in the market. It is the first of its kind and fills a gap in the technical literature as no other handbook on SPR is currently available. The final chapter discussed new trends and a vision is given for future developments and needs of the SPR market. This excellent handbook provides comprehensive information with easy to use, stand-alone chapters and will be of great use to anyone one working with or affiliated to the technology.

Due to the increased popularity of augmented and virtual reality experiences, the interest in capturing the real world in multiple dimensions and in presenting it to users in an immersible fashion has never been higher. Distributing such representations enables users to freely navigate in multisensory 3D media experiences. Unfortunately, such representations require a large amount of data, not feasible for transmission on today's networks. Efficient compression technologies well adopted in the content chain are in high demand and are key components to democratize augmented and virtual reality applications. Moving Picture Experts Group, as one of the main standardization groups dealing with multimedia, identified the trend and started recently the process of building an open standard for compactly representing 3D point clouds, which are the 3D equivalent of the very well-known 2D pixels. This paper introduces the main developments and technical aspects of this ongoing standardization effort.

Heart rate monitoring using wrist-type photoplethysmographic signals during subjects' intensive exercise is a difficult problem, since the signals are contaminated by extremely strong motion artifacts caused by subjects' hand movements. So far few works have studied this problem. In this study, a general framework, termed TROIKA, is proposed, which consists of signal decomposiTion for denoising, sparse signal RecOnstructIon for high-resolution spectrum estimation, and spectral peaK trAcking with verification. The TROIKA framework has high estimation accuracy and is robust to strong motion artifacts. Many variants can be straightforwardly derived from this framework. Experimental results on datasets recorded from 12 subjects during fast running at the peak speed of 15 km/h showed that the average absolute error of heart rate estimation was 2.34 beat per minute, and the Pearson correlation between the estimates and the ground truth of heart rate was 0.992. This framework is of great values to wearable devices such as smartwatches which use PPG signals to monitor heart rate for fitness.

Recently, several indoor localization solutions based on WiFi, Bluetooth, and UWB have been proposed. Due to the limitation and complexity of the indoor environment, the solution to achieve a low-cost and accurate positioning system remains open. This article presents a WiFibased positioning technique that can improve the localization performance from the bottleneck in ToA/AoA. Unlike the traditional approaches, our proposed mechanism relaxes the need for wide signal bandwidth and large numbers of antennas by utilizing the transmission of multiple predefined messages while maintaining high-accuracy performance. The overall system structure is demonstrated by showing localization performance with respect to different numbers of messages used in 20/40 MHz bandwidth WiFi APs. Simulation results show that our WiFi-based positioning approach can achieve 1 m accuracy without any hardware change in commercial WiFi products, which is much better than the conventional solutions from both academia and industry concerning the trade-off of cost and system complexity.

We present an investigation of the phase stability, electrochemical stability and Li+ conductivity of the Li10±1MP2X12 (M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors using first principles calculations. The Li10GeP2S12 (LGPS) superionic conductor has the highest Li+ conductivity reported to date, with excellent electrochemical performance demonstrated in a Li-ion rechargeable battery. Our results show that isovalent cation substitutions of Ge4+ have a small effect on the relevant intrinsic properties, with Li10SiP2S12 and Li10SnP2S12 having similar phase stability, electrochemical stability and Li+ conductivity as LGPS. Aliovalent cation substitutions (M = Al or P) with compensating changes in the Li+ concentration also have a small effect on the Li+ conductivity in this structure. Anion substitutions, however, have a much larger effect on these properties. The oxygen-substituted Li10MP2O12 compounds are predicted not to be stable (with equilibrium decomposition energies >90 meV per atom) and have much lower Li+ conductivities than their sulfide counterparts. The selenium-substituted Li10MP2Se12 compounds, on the other hand, show a marginal improvement in conductivity, but at the expense of reduced electrochemical stability. We also studied the effect of lattice parameter changes on the Li+ conductivity and found the same asymmetry in behavior between increases and decreases in the lattice parameters, i.e., decreases in the lattice parameters lower the Li+ conductivity significantly, while increases in the lattice parameters increase the Li+ conductivity only marginally. Based on these results, we conclude that the size of the S2− is near optimal for Li+ conduction in this structural framework.

Deep neural networks are typically trained by optimizing a loss function with an SGD variant, in conjunction with a decaying learning rate, until convergence. We show that simple averaging of multiple points along the trajectory of SGD, with a cyclical or constant learning rate, leads to better generalization than conventional training. We also show that this Stochastic Weight Averaging (SWA) procedure finds much flatter solutions than SGD, and approximates the recent Fast Geometric Ensembling (FGE) approach with a single model. Using SWA we achieve notable improvement in test accuracy over conventional SGD training on a range of state-of-the-art residual networks, PyramidNets, DenseNets, and Shake-Shake networks on CIFAR-10, CIFAR-100, and ImageNet. In short, SWA is extremely easy to implement, improves generalization, and has almost no computational overhead.

Emissive molecules comprising a donor and an acceptor bridged by 9,9-dimethylxanthene, were studied (XPT, XCT, and XtBuCT). The structures position the donor and acceptor with cofacial alignment at distances of 3.3-3.5 Å wherein efficient spatial charge transfer can occur. The quantum yields were enhanced by excluding molecular oxygen and thermally activated delayed fluorescence with lifetimes on the order of microseconds was observed. Although the molecules displayed low quantum yields in solution, higher quantum yields were observed in the solid state. Crystal structures revealed π-π intramolecular interactions between a donor and an acceptor, however, the dominant intermolecular interactions were C-H···π, which likely restrict the molecular dynamics to create aggregation-induced enhanced emission. Organic light emitting devices using XPT and XtBuCT as dopants displayed electroluminescence external quantum efficiencies as high as 10%.

For reliable operation, individual cells of an STT-MRAM memory array must meet specific requirements on their performance. In this work we review some of these requirements and discuss the fundamental physical principles of STT-MRAM operation, covering the range from device level to chip array performance, and methodology for its development.

In this paper, a review of the developments in MRAM technology over the past 20 years is presented. The various MRAM generations are described with a particular focus on spin-transfer torque MRAM (STT-MRAM) which is currently receiving the greatest attention. The working principles of these various MRAM generations, the status of their developments, and demonstrations of working circuits, including already commercialized MRAM products, are discussed.