Ericsson (United States)

Throughout this article, we concentrate on the transcoding of block-based video coding schemes that use hybrid discrete cosine transform (DCT) and motion compensation (MC). In such schemes, the frames of the video sequence are divided into macroblocks (MBs), where each MB typically consists of a luminance block (e.g., of size 16 × 16, or alternatively, four 8 × 8 blocks) along with corresponding chrominance blocks (e.g., 8 × 8 Cb and 8 × 8 Cr). This article emphasizes the processing that is done on the luminance components of the video. In general, the chrominance components can be handled similarly and will not be discussed in this article. We first provide an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed. Then, we describe the advances regarding spatial and temporal resolution reduction techniques and architectures. Additionally, an overview of error resilient transcoding is also provided, as well as a discussion of scalable coding techniques and how they relate to video transcoding. Finally, the article ends with concluding remarks, including pointers to other works on video transcoding that have not been covered in this article, as well as some future directions.

Transmitter diversity wireless communication systems over Rayleigh fading channels using pilot symbol assisted modulation (PSAM) are studied. Unlike conventional transmitter diversity systems with PSAM that estimate the superimposed fading process, we are able to estimate each individual fading process corresponding to the multiple transmitters by using appropriately designed pilot symbol sequences. With such sequences, special coded modulation schemes can then be designed to access the diversity provided by the multiple transmitters without having to use an interleaver or expand the signal bandwidth. The code matrix notion is introduced for the coded modulation scheme, and its design criteria are also established. In addition to the reduction in receiver complexity, simulation results are compared to, and shown to be superior to, that of an intentional frequency offset system over a wide range of system parameters.

With the popular Jakes fading model, it is difficult to create multiple uncorrelated fading waveforms. In the Letter, modifications to the model are proposed which solve this problem.

Research work focusing on the enhancement of large-signal current-voltage (I-V) capabilities has resulted in significant performance improvement for AlGaN/GaN HEMT's. 100-150 /spl mu/m wide devices grown on SiC substrates demonstrated a record power density of 9.8 W/mm at 8 GHz, which is about ten times higher than GaAs-based FETs; similar devices grown on sapphire substrates showed 6.5 W/mm, which was thermally limited, 2-mm-wide devices flip-chip mounted on to AlN substrates produced 9.2-9.8 W output power at 8 GHz with 44-47% PAE. A flip-chip amplifier IC using a 4-mm device generated 14 W at 8 GHz, representing the highest CW power obtained from GaN-based integrated circuits to date.

As a part of a special collection in this issue of Academic Medicine, which is focused on mastery learning in medical education, this Perspective describes how the expert-performance approach with deliberate practice is consistent with many characteristics of mastery learning. Importantly, this Perspective also explains how the expert-performance approach provides a very different perspective on the acquisition of skill. Whereas traditional education with mastery learning focuses on having students attain an adequate level of performance that is based on goals set by the existing curricula, the expert-performance approach takes an empirical approach and first identifies the final goal of training-namely, reproducibly superior objective performance (superior patient outcomes) for individuals in particular medical specialties. Analyzing this superior complex performance reveals three types of mental representations that permit expert performers to plan, execute, and monitor their own performance. By reviewing research on medical performance and education, the author describes evidence for these representations and their development within the expert-performance framework. He uses the research to generate suggestions for improved training of medical students and professionals. Two strategies-designing learning environments with libraries of cases and creating opportunities for individualized teacher-guided training-should enable motivated individuals to acquire a full set of refined mental representations. Providing the right resources to support the expert-performance approach will allow such individuals to become self-regulated learners-that is, members of the medical community who have the tools to improve their own and their team members' performances throughout their entire professional careers.

We describe the 1-meter Swedish solar telescope which replaces the former 50-cm solar telescope (SVST) in La Palma. The un-obscured optics consists of a singlet lens used as vacuum window and two secondary optical systems. The first of these enables narrow-band imaging and polarimetry with a minimum of optical surfaces. The second optical system uses a field mirror to re-image the pupil on a 25 cm corrector which provides a perfectly achromatic image, corrected also for atmospheric dispersion. The adaptive optics system is integrated with the design of the telescope but is sufficiently flexible to allow future upgrades. It consists of a low-order bimorph modal mirror with 37 electrodes, allowing near-diffraction-limited imaging a reasonable fraction of the observing time on La Palma. The new telescope became operational at the end of May 2002 and has already proven to be the most highly resolving solar telescope ever built. In this paper, we describe its mechanical and optical design, the polishing and testing of the optics and the instrumentation in use or planned for this telescope.

We present a performance comparison of a number of key micromobility protocols that have been discussed in the IETF Mobile IP Working Group over the past several years. IP micromobility protocols complement Mobile IP by offering fast and seamless handoff control in limited geographical areas, and IP paging in support of scalability and power conservation. We show that despite the apparent differences between IP micromobility protocols, the operational principles that govern them are largely similar. We use this observation to establish a generic micromobility model to better understand design and performance trade offs. A number of key design choices are identified within the context of the generic model related to handoff quality and route control messaging. We present simulation results for Cellular IP, Hawaii, and Hierarchical Mobile IP, and evaluate the handoff performance of these protocols. Simulation results presented in this article are based on the Columbia IP Micromobility Software (CIMS), which is freely available from the Web (comet.columbia. edu/micromobility) for experimentation.

This article defines sustainability and sustainable cyclic processes, and quantifies the degree of non-renewability of a major biofuel: ethanol produced from industrially grown corn. It demonstrates that more fossil energy is used to produce ethanol from corn than the ethanol's calorific value. Analysis of the carbon cycle shows that all leftovers from ethanol production must be returned back to the fields to limit the irreversible mining of soil humus. Thus, production of ethanol from whole plants is unsustainable. In 2004, ethanol production from corn will generate 8 million tons of incremental CO2, over and above the amount of CO2 generated by burning gasoline with 115% of the calorific value of this ethanol. It next calculates the cumulative exergy (available free energy) consumed in corn farming and ethanol production, and estimates the minimum amount of work necessary to restore the key non-renewable resources consumed by the industrial corn-ethanol cycle. This amount of work is compared with the maximum useful work obtained from the industrial corn-ethanol cycle. It appears that if the corn-ethanol exergy is used to power a car engine, the minimum restoration work is about 6 times the maximum useful work from the cycle. This ratio drops down to 2 if an ideal fuel cell is used to process the ethanol. The article estimates the U.S. taxpayer subsidies of the industrial corn-ethanol cycle at $3.8 billion in 2004. The parallel subsidies by the environment are estimated at $1.8 billion in 2004. The latter estimate will increase manifold when the restoration costs of aquifers, streams, and rivers, and the Gulf of Mexico are also included. Finally, the article estimates that (per year and unit area) the inefficient solar cells produce ∼ 100 times more electricity than corn ethanol. There is a need for more reliance on sunlight, the only source of renewable energy on the earth.

The Third Generation Partnership Project defined multimedia broadcast/multicast service in 2005 to optimize the distribution of video traffic. This standard covers the terminal, radio, core network, and user service aspects. This MBMS standard has evolved into enhanced MBMS (eMBMS) that builds on top of the 3GPP Long Term Evolution standard. eMBMS evolution brings improved performance thanks to higher and more flexible LTE bit rates, single frequency network operations, and carrier configuration flexibility. 3GPP Rel-11 also brings improvements in the areas of service layer with, for example, video codec for higher resolutions and frame rate, and forward error correction. eMBMS allows offloading of the LTE network and backhaul. It enables the possibility to deliver premium content to many users with secured quality of service in defined areas. Other important use cases are pushed content via user equipment caching and machine-to-machine services. This article describes the relevant use cases for eMBMS in terms of service. It then gives a tutorial on eMBMS, in particular highlighting the evolution over MBMS. The scope comprises the radio access, core network, and service layer.

The Internet of Things (IoT) will feature pervasive sensing and control capabilities via a massive deployment of machine-type communication (MTC) devices. The limited hardware, low-complexity, and severe energy constraints of MTC devices present unique communication and security challenges. As a result, robust physical-layer security methods that can supplement or even replace lightweight cryptographic protocols are appealing solutions. In this paper, we present an overview of low-complexity physical-layer security schemes that are suitable for the IoT. A local IoT deployment is modeled as a composition of multiple sensor and data subnetworks, with uplink communications from sensors to controllers, and downlink communications from controllers to actuators. The state of the art in physical-layer security for sensor networks is reviewed, followed by an overview of communication network security techniques. We then pinpoint the most energy-efficient and low-complexity security techniques that are best suited for IoT sensing applications. This is followed by a discussion of candidate low-complexity schemes for communication security, such as on-off switching and space-time block codes. The paper concludes by discussing open research issues and avenues for further work, especially the need for a theoretically well-founded and holistic approach for incorporating complexity constraints in physical-layer security designs.

A wide variety of unique systems and components inhabits the HF, VHF, and UHF bands. Many communication systems (ionospheric, meteor-burst, and troposcatter) provide beyond-line-of-sight coverage and operate independently of external infrastructure. Broadcasting and over-the-horizon radar also operate in these bands. Magnetic-resonance imaging uses HF/VHF signals to see the interior of a human body, and RF heating is used in a variety of medical and industrial applications. Receivers typically employ a mix of analog and digital-signal-processing techniques. Systems for these frequencies make use of RF-power MOSFETs, p-i-n diodes, and ferrite-loaded transmission-line transformers.

Digital twin (DT) technology has recently gathered pace in the engineering communities as it allows for the convergence of the real structure and its digital counterpart throughout their entire life-cycle. With the rapid development of supporting technologies, including machine learning (ML), 5G/6G, cloud computing, and Internet of Things, DT has been moving progressively from concept to practice. In this article, a DT framework based on cloud computing and deep learning (DL) for structural health monitoring is proposed to efficiently perform real-time monitoring and proactive maintenance. The framework consists of structural components, device measurements, and digital models formed by combining different submodels, including mathematical, finite element, and ML ones. The data interaction among physical structure, digital model, and human interventions are enhanced by using cloud computing infrastructure and a user-friendly web application. The feasibility of the proposed framework is demonstrated via case studies of damage detection of model bridge and real bridge structures using DL algorithms, with high accuracy of 92%.

We present three unconventional approaches to keying variable management. The first approach is based on using a public key cryptosystem (PKC) that is breakable in short, but on average less, time than it takes to set up an ultrawide bandwidth modem that is then used to transport a keying variable for a classical cryptosystem. The second concept proposes using the characteristics of an urban UHF radio channel, determined by mutual sounding, as the cryptovariable. The third concept encourages research into ill-conditioned problems as potentially fruitful ground for PKCs not based on finite field arithmetic.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Network operators are faced with the challenge of deploying and managing middleboxes (also called inline services) such as firewalls within their broadband access, datacenter or enterprise networks. Due to the lack of available protocols to route traffic through middleboxes, operators still rely on error-prone and complex low-level configurations to coerce traffic through the desired set of middleboxes. Built upon the recent software-defined networking (SDN) architecture and OpenFlow protocol, this paper proposes StEERING, short for SDN inlinE sERvices and forwardlNG. It is a scalable framework for dynamically routing traffic through any sequence of middleboxes. With simple centralized configuration, StEERING can explicitly steer different types of flows through the desired set of middleboxes, scaling at the level of per-subscriber and per-application policies. With its capability to support flexible routing, we further propose an algorithm to select the best locations for placing services, such that the performance is optimized. Overall, StEERING allows network operators to monetize their middlebox deployment in new ways by allowing subscribers flexibly to select available network services.

The fifth generation (5G) of cellular networks is starting to be defined to meet the wireless connectivity demands for 2020 and beyond. One area that is considered increasingly important is the capability to provide ultra-reliable and low-latency communication, to enable e.g., new mission-critical machine-type communication use cases. One such example with extremely demanding requirements is the industrial automation with a need for ultra-low latency with a high degree of determinism. In this paper, we discuss the feasibility, requirements and design challenges of an OFDM based 5G radio interface that is suitable for mission-critical MTC. The discussion is further accompanied with system-level performance evaluations that are carried out for a factory hall-wide automation scenario with two different floor layouts.

Currently, a global third-generation cellular system based on code-division multiple-access (CDMA) is being developed with a wider bandwidth than existing second-generation systems. The wider bandwidth provides increased multipath resolution in a time-dispersive channel, leading to higher frequency-selectivity. A generalized RAKE receiver for interference suppression and multipath mitigation is proposed. The receiver exploits the fact that time dispersion significantly distorts the interference spectrum from each base station in the downlink of a wideband CDMA system. Compared to the conventional RAKE receiver, this generalized RAKE receiver may have more fingers and different combining weights. The weights are derived from a maximum likelihood formulation, modeling the intracell interference as colored Gaussian noise. This low-complexity detector is especially useful for systems with orthogonal downlink spreading codes, as orthogonality between own cell signals cannot be maintained in a frequency-selective channel. The performance of the proposed receiver is quantified via analysis and simulation for different dispersive channels, including Rayleigh fading channels. Gains on the order of 1-3.5 dB are achieved, depending on the dispersiveness of the channel, with only a modest increase in the number of fingers. For a wideband CDMA (WCDMA) system and a realistic mobile radio channel, this translates to capacity gains of the order of 100%.

Transmissions in different cells of a time-division duplex system are typically synchronous in order to eliminate the base station-to-base station and terminal-to-terminal interference. The synchronous operation limits dynamic resource configuration for downlink and uplink transmissions. Today, as a large percentage of mobile traffic is generated in hotspots and indoor environments, heterogeneous networks comprising high-power/wide-area and low-power/local-area network nodes are becoming a reality. Such heterogeneous networks provide opportunities to exploit dynamic uplink-downlink configuration in TDD systems, adapting to the individual traffic needs of a specific cell area. This article presents a tutorial overview of dynamic uplink-downlink configuration and interference management in time-division Long Term Evolution, including motivations, target deployment scenarios, opportunities and challenges, system requirements, design aspects, and performance evaluations.

Link quality model is widely used in system evaluations to simplify the simulation complexity. It is also important in practical systems for improving the accuracy of the link adaptation and the efficiency of radio-resource-management. Conventional linear average SNR characterization of fading channel performance lacks generality, since the same linear SNR value may lead to drastic block error rate differences in various fading channels. A unified metric is proposed in this paper for link performance characterization and quality modeling. This paper proposes a mutual-information-based (Mi-based) link quality model, which contains separate modulation and coding models. The modulation model maps the received SNR to the mutual information symbol by symbol. The coding model maps the sum or average of the mutual information to decoding performance for each coding block. The existing methods based on the effective signal-to-noise-ratio (SNR) of a multi-state channel have limited accuracy in the mixed modulation cases. Compared with the existing models, the Mi-model is simpler and easier to apply to mixed-modulation cases and different H-ARQ schemes. The simulation results verify the accuracy in different multi-state channels and give the comparison with the exponential effective-SNR-mapping (EESM) model

Fifth generation wireless networks are currently being developed to handle a wide range of new use cases. One important emerging area is ultra-reliable communication with guaranteed low latencies well beyond what current wireless technologies can provide. In this paper, we explore the viability of using wireless communication for low-latency, high-reliability communication in an example scenario of factory automation, and outline important design choices for such a system. We show that it is possible to achieve very low error rates and latencies over a radio channel, also when considering fast fading signal and interference, channel estimation errors, and antenna correlation. The most important tool to ensure high reliability is diversity, and low latency is achieved by using short transmission intervals without retransmissions, which, however, introduces a natural restriction on coverage area.

Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) in order to execute various tasks ranging from coordinated trajectory planning to cooperative target recognition. However, due to the lack of continuous connections between the UAV swarm and ground base stations (BSs), using centralized ML will be challenging, particularly when dealing with a large volume of data. In this paper, a novel framework is proposed to implement distributed federated learning (FL) algorithms within a UAV swarm that consists of a leading UAV and several following UAVs. Each following UAV trains a local FL model based on its collected data and then sends this trained local model to the leading UAV who will aggregate the received models, generate a global FL model, and transmit it to followers over the intra-swarm network. To identify how wireless factors, like fading, transmission delay, and UAV antenna angle deviations resulting from wind and mechanical vibrations, impact the performance of FL, a rigorous convergence analysis for FL is performed. Then, a joint power allocation and scheduling design is proposed to optimize the convergence rate of FL while taking into account the energy consumption during convergence and the delay requirement imposed by the swarm's control system. Simulation results validate the effectiveness of the FL convergence analysis and show that the joint design strategy can reduce the number of communication rounds needed for convergence by as much as 35% compared with the baseline design.