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Tuesday, October 23, 2018

Flash Translation Layer allows NAND memory to be used for deterministic operation in embedded designs

By Nick Flaherty

HCC Embedded in Budapest has extended its existing flash translation layer (FTL) solution for NAND with the addition of deterministic execution control. 

Engineers integrating NAND flash into safety-based systems in automotive, aerospace, and industrial applications can use HCC’s SafeFTL to ensure stable and predictable operation of the NAND flash. The deterministic SafeFTL has been fully verified both in simulated environments and on real NAND flash arrays.

Traditionally, NOR flash has been the dominant memory in highly reliable systems, but more recently engineers are integrating NAND flash into safety systems where information must be predictably available. An FTL manages an array of NAND flash to create a logical interface that software can use. This includes wear leveling, bad block handling, and the many other subtleties of managing NAND flash. However, existing FTLs all stall at some point for a variable period of time, particularly when placed under heavy load.

Safety-critical systems demand a different approach that ensures stability and predictability above all else. For these systems, where accurate time division is critical to the delivery of safety, engineers can use HCC’s deterministic SafeFTL to integrate arrays of NAND flash without disturbing the predictability of the system. 

The deterministic FTL builds on HCC’s SafeFTL by enabling the host or safety system to know how long operations will take and respond by either scheduling tasks appropriately or executing them in multiple steps. The host system gets the length of time a flash operation will take from the FTL and can schedule an appropriate time slot, or can spread complex operations over multiple time slots, while leaving the NAND flash accessible to other tasks.

“HCC has spent much of its history developing a deep understanding of flash storage technology,” said HCC Embedded CEO Dave Hughes. “Our SafeFTL has provided fail-safety and reliability to embedded systems for the last 15 years. We do this by taking a system-level approach that ensures each layer in the system has correctly defined the behaviour it requires from adjacent layers. The addition of deterministic execution control to our SafeFTL product goes a step beyond to ensure the utmost reliability and predictability in safety-critical systems.”

Monday, October 22, 2018

Silicon Labs teams with Digi for LTE-M IoT module

By Nick Flaherty

Silicon Labs has teamed up with Digi for an LTE-M expansion kit around the XBee3 pre-certified cellular modem.
The LTE-M expansion kit works with Silicon Labs’ EFM32 Giant Gecko 11 starter kit to simplify the development of gateways and end devices that operate in deep-sleep mode and require extended battery life. The kit is aimed at agricultural, asset tracking, smart energy and smart city IoT applications.

“Together, Silicon Labs and Digi International are dedicated to connecting people, networks and ‘things’ with best-in-class IoT and M2M technologies,” said Matt Johnson, Senior Vice President and General Manager of IoT products at Silicon Labs. “We’ve collaborated with Digi to deliver flexible LTE-M cellular connectivity capabilities, enabling cloud-connected applications that are remote, on the go and ready to deploy.”

“The jointly developed LTE-M expansion kit works with Silicon Labs’ starter kits to accelerate development by quickly enabling cellular IoT connectivity and avoiding costly cellular device certifications,” said Mark Tekippe, Director of Product Management, Digi International. “Digi XBee3 cellular modems and Silicon Labs Gecko MCUs are an ideal pairing to deliver seamless cloud connectivity with ultra-low power capabilities. The pre-certified Digi XBee3 cellular modem is easy to configure and provides secure, flexible out-of-box connectivity over LTE-M and NB-IoT networks.”

“LTE-M is a great option for LPWAN applications that require a combination of long battery life, LTE reliability and low latency. LTE-M is compatible with existing LTE networks and in the future will coexist with 5G technologies,” added Mike Krell, Head of IoT Strategy, J. Brehm & Associates. “Vendors offering easy-to-use development tools to accelerate LTE-M solutions will be well-positioned for growth in the cellular IoT market.”

Developers can take advantage of the development tools including the Digi Remote Manager, Silicon Labs’ Energy Profiler and pre-programmed demos. The XBee3 is certified on AT&T and Verizon cellular networks. Using the XBee allows for easy migration to NB-IoT as well as the XBee API frames, MicroPython and XCTU software tools to simplify development and Digi TrustFence for integrated device security, identity and data privacy.

The LTE-M expansion kit and EFM32 Giant Gecko 11 starter kit (SLSTK3701A) are available now, and both are priced at $99. 

Related stories:

Power news this week

By Nick Flaherty

. Electric pickup charges battery in 13 minutes

. World’s largest organic solar cell film installation in Germany

. Meyer Burger cuts 100 more jobs in China focus

. 3D printing a lithium ion battery for wearables

. Work starts on hemp for supercapacitor

. Smartwatch uses photodiodes for both energy harvesting and gesture recognition

. Third generation SiC JFET adds 1200 V and 650 V options

. 11kW bi-directional SiC DC-DC converter targets energy storage systems

. Integrated magnetics cut power converter size in half

. Choosing blocking capacitors – it’s more than just values

. Mentor: Concepts of power integrity: Taking the noise out of via-to-via coupling

. Coilcraft: An introduction to inductor specifications

Qualcomm launches 60GHz 802.11ay chipset

By Nick Flaherty

Qualcomm Technologies has launched a family of 60GHz Wi-Fi chipsets, the QCA64x8 and QCA64x1, providing 10+ gigabit-per-second (Gbps) network speeds and wire-equivalent latency as well as sensing applications like proximity and presence detection, gesture recognition, room mapping with precise location and improved facial feature detection. 
Qualcomm Technologies is the first-to-market with a 60GHz Wi-Fi solution with optimizations based on the 802.11ay specification. Although the 60GHz has a limited range, the chips include always-on ambient Wi-Fi sensing capabilities, enabling devices to identify people, objects, movements and precise location without being affected by light conditions. Networking and mobile devices alike can take advantage of these new Wi-Fi sensing features to provide new and differentiated experiences to end users. 

“mmWave holds enormous potential to support a new class of user experiences, and Qualcomm Technologies is leading the charge with both its Qualcomm Snapdragon X50 5G NR modem family and unlicensed 60GHz Wi-Fi mmWave solution,” said Rahul Patel, senior vice president and general manager, connectivity and networking at Qualcomm Technologies. “Our 11ay solutions were developed with the flexibility to support a broad ecosystem of smartphone, router or fixed wireless access platforms and provides the industry with the critical building blocks needed to take connectivity performance to the next level.”

The QCA6438 and QCA6428 are aimed at infrastructure and fixed wireless access, and the QCA6421 and QCA6431 at mobile applications. Facebook’s Terragraph technology is using the QCA6438 and QCA6428 chipsets for a multimode wireless access point. 

“We are excited to work with Qualcomm Technologies to develop 60 GHz solutions based on Facebook’s Terragraph technology and Qualcomm Technologies’ chipsets,” said Anuj Madan, Product Manager at Facebook. “By enabling service providers to offer high-quality internet connectivity in dense urban and suburban areas, this collaboration supports our work to bring more people online to a faster internet.”
“As consumers all around the world are increasingly relying on mobile devices to power their gaming and entertainment activities, they expect seamless experiences powered by unrivalled speed and ultra-low-latency,” said Bryan Chang, General Manager of ASUS Mobile Business Unit. “Our latest line of Republic of Gamers (ROG) mobile devices are designed specifically to meet these high-performance mobile gaming needs while leveraging Qualcomm Technologies’ existing 60GHz Wi-Fi solutions. We are happy to see Qualcomm Technologies continue their innovation on 60GHz Wi-Fi technology.”

The QCA64x8 and QCA64x1 are available today and we will bring you details of the mobile chips when we have them.

Friday, October 19, 2018

Infineon backs FreeRTOS for IoT edge computing

By Nick Flaherty

We've highlighted the importance of FreeRTOS (now Amazon FreeRTOS) for real time processing and connecting devices in the Internet of Things to the cloud.

Infineon Technologies has combined its microcontroller and security tech for easy and secure use of new generation sensors featuring new AI functionalities running on Amazon Web Services (AWS).
“Infineon supports the development of secured cloud connection-enabled applications,” said Sandro Cerato, Chief Technology Officer of the Power Management & Multimarket Division at Infineon. “These can range from mere motion detection up to situational awareness, by leveraging AI and machine learning algorithms. We are combining leading-edge sensors, hardware-based security and Infineon microcontrollers, with the technology and services provided by AWS to support customers with the next level of smartness.”

To do this, Infineon’s XMC4000 family of 32-bit-microcontrollers now supports Amazon FreeRTOS, a microcontroller operating system that makes small, low-power edge devices easy to program, deploy, secure, connect, and manage. This will create multiple new options of edge-computing based applications for consumer and industrial markets are enabled.

Securely connecting manufacturers’ devices both locally and to the cloud is paramount for customers to take up the connected service offering. People living in smart homes and working in smart buildings can benefit from the seamless interaction of the new generation XENSIV sensors. Radar, pressure sensors and MEMS microphones are accompanied by OPTIGA hardware security solutions, allowing energy, light management, health care and building operation running on AWS to improve the quality of life and deliver substantial cost savings.

For example, Infineon’s XMC4800 family Connectivity kit WiFi runs on AWS. This development platform brings edge-computing services to the next level of interaction in customers’ applications, including WiFi connectivity and ETHERCAT. “Using the XMC4800 series, Infineon has the opportunity to be one of the first movers in the market offering AWS FreeRTOS combined with ETHERCAT functionality,” said Ralf Koedel, Director Product Marketing for Automotive & Industrial Microcontroller at Infineon.

XMC4800 devices are powered by Cortex ARM M4F microcontrollers. They also offer up to six standard CAN and ETHERCAT connectivity, for IoT gateway applications, plus many other peripherals with the benefit of the Arduino and Click Board compatible form factor. The combination with AWS Greengrass software allows developers to easily develop and take advantage of the cloud capability provided by AWS.

The Evaluation Board XMC4800 IoT Amazon FreeRTOS Connectivity kit WiFi is available.

Related stories:
  • Amazon and ST launch IoT Node-to-Cloud implementation for FreeRTOS

Thursday, October 18, 2018

LoRa gateway module boosts deployment

By Nick Flaherty

Murata has launched two highly integrated 14pin LoRa Pico Gateway metal-shielded modules to accelerate the deployment of long range IoT networks.
The LBAA0ZZ1QM (for the US) and LBAA0ZZ1TY (for the EU) support eight channels and are available for EU or US ISM bands. The module measures just 55.0 mm x 21.0 mm x 3.4 mm and Murata believes them to be the world’s smallest LoRaWAN gateway modules. 

The single substrate module uses a Semtech SX1308 transceiver concentrator capable of managing packets from many remotely dispersed end-points, two Semtech SX1257 highly integrated RF front end I/Q transceivers and an STMicroelectronics STM32F401 Arm Cortex M4 microcontroller. A Skyworks RF front-end multi-chip module provides antenna matching, receiver pre-amplifier and transmitter final stage function.

The microcontroller hosts packet forwarding, communication with the application host controller and the module’s power management functions. The packet forwarder handles the two-way communication of packets between an end-point and the network server while the host driver provisions a USB CDC virtual port to communication with the host gateway application processor. Alternatively, if desired, the module’s UART port can be used for communication with the gateway’s host. The microcontroller firmware also takes care of the power management, in particular when using a USB port, by limiting downlink power consumption to within the 500 mA maximum power budget.

The LoRa network provides a low cost long-range communication infrastructure to communication with thousands of end-points. Example deployments include utility meter reading, smart agriculture and industrial IoT applications. Ensuring reliable communication across metropolitan or rural areas is essential and gateways such as the Murata LBAA0ZZ1 play an essential part in maintaining network links.

The module has support from network operators such as Actility and the Things Network to speed up rollouts. 

“This module is a significant step, ready to accelerate the growth of LoRaWAN use cases requiring widespread deployment of picocells, such as smart building applications,” said Actility CEO Oliver Hersent. “We are working with Murata to ensure out of the box compatibility with our market-leading ThingPark IoT network management platform, so our customers can benefit from the most cost-effective picocell gateways. This will be particularly valuable for integrators of ThingPark Enterprise targetting in-building and in-factory solutions.”

Wienke Giezeman, founder and CEO of The Things Network, added "Murata understands the future of LoRaWAN very well by providing an easy way for any router, set top box and base station makers to offer LoRaWAN in their products in a very easy way. We are very happy to partner with them to bring the complete solution to the market."

“With its new LBAA0ZZ1 series LoRa Pico Gateway module, Murata is greatly simplifying the development of new LoRaWAN gateways, which is a crucial contribution to our ecosystem as LoRaWAN becomes widespread in the most diverse applications,” said Domenico Arpaia, CEO of OrbiWise. “We have long cooperated with the Murata Team: OrbiWAN, our Carrier-grade LoraWAN Network Server, which already supports all commercial LoRaWAN gateways, now also supports natively Murata’s new gateway module. We are confident that, with Murata’s competence and resources and our own help, their new gateway module will quickly become the solution of choice for many new gateways in the rapidly growing LoRa market.”

Wednesday, October 17, 2018

NXP launches machine learning tools for IoT edge processing

By Nick Flaherty

NXP has launched an edge intelligence environment called eIQ that provides a comprehensive machine learning (ML) toolkit with support for TensorFlow Lite, Caffe2, and other neural network frameworks, as well as non-neural ML algorithms.

This will enable turnkey integrated ML solutions for voice, vision and anomaly detection applications, including data acquisition, trained models, with user feature customisation to use with NXP's EdgeScale software that provides secure device on-boarding, provisioning, and container management of ML applications targeting i.MX and Layerscape applications processors.
The eIQ software environment includes the tools necessary to structure and optimise cloud-trained ML models to efficiently run in resource-constrained edge devices for a broad range of industrial, Internet-of-Things (IoT), and automotive applications. The turnkey, production-ready solutions are specifically targeted for voice, vision, and anomaly detection applications. By removing the heavy investment necessary to become ML experts, NXP enables tens of thousands of customers whose products need machine learning capability.

"Having long recognised that processing at the edge node is really the driver for customer adoption of machine learning, we created scalable ML solutions and eIQ tools, to make transferring artificial intelligence capabilities from the cloud-to-the-edge even more accessible and easy to use," said Geoff Lees, senior vice president and general manager of microcontrollers.

With support for NXP's full microcontroller (MCU) and applications processor product line, eIQ provides the building blocks that developers need to implement ML in edge devices. Keeping pace with ML's changing landscape, NXP eIQ is continuously expanding to include: data acquisition and curation tools; model conversion for a wide range of neural net (NN) frameworks and inference engines, such as, TensorFlow Lite, Caffe2, CNTK, and Arm® NN; support for emerging NN compilers like GLOW and XLA; classical ML algorithms (e.g. support vector machine and random forest); and tools to deploy the models for heterogeneous processing on NXP embedded processors.

NXP also recently introduced a software infrastructure called EdgeScale to unify how data is collected, curated, and processed at the edge, with focus on enabling ML applications. EdgeScale enables seamless integration to cloud-based artificial intelligence (AI) / ML services and deployment of cloud-trained models and inferencing engines on all NXP devices, from low-cost MCUs to high-performance i.MX and Layerscape applications processors.

Building on the eIQ environment, the company introduced turnkey solutions for edge-based learning and local execution of vision, voice, and anomaly detection models. These system-level solutions provide the hardware and software necessary for building fully functional applications, while allowing customers to add their own differentiation. The solutions are modular, making it easy for customers to expand functionality of their products with a simple plug-in. For example, a voice recognition module can be easily added to a product that has NXP's vision recognition solution. 

Demonstrations include facial recognition training on high-performance i.MX 8QM and deployment of extracted inference engines on mid-range i.MX 8QXP and i.MX 8M applications processors using secure docker containers, as well as CMSIS-NN performance benchmarking using CIFAR-10 on just-announced LPC5500 MCUs and anomaly detection with classical machine learning techniques using Cortex-M4F based Kinetis MCUs.
Localized voice and vision ML applications include voice-enabled solution for localised wake word and end-user programmable voice control experience also using i.MX RT1050 crossover processor and vision systems with theAu-Zone DeepView ML Kit using i.MX 8QM implemented in a microwave oven and traffic sign recognition using low-cost i.MX RT 1050 crossover processor.

Related stories:

Tuesday, October 16, 2018

SiFlower uses CEVA 802.11ac in Chinese Smart Home Access Point chip

By Nick Flaherty

Despite the move to rebranding WiFi generations, Chinese chip maker SiFlower Communication Technology is using the RivieraWaves RW-11AC Wi-Fi IP cost-effective access point system on chip (SoC).
SiFlower’s SF16A18 is a highly integrated single chip that combines the RW-11AC IP with a dual-core CPU and rich suite of interfaces (Ethernet, GMAC, USB, SD, IIS), creating an optimal platform for intelligent routers / access points, smart home gateways and smart speakers.

“Highly integrated and optimized Wi-Fi solutions are the key to opening the mass Smart Home market,” said Albert Lee, CEO of SiFlower. “We are proud of the solution we have created in the SF16A18, and CEVA’s RW-11AC Wi-Fi IP along with their engineering excellence and technical support have been instrumental in our success.”

“We are delighted to announce SiFlower as a licensee for our Wi-Fi IP,” said Aviv Malinovitch, vice president and general manager of the Connectivity Business Unit at CEVA. “The SF16A18 is a leading example of the next-generation of fully-integrated and differentiated Wi-Fi enabled SoCs that are available at a very cost-effective price point.”

CEVA’s RivieraWaves Wi-Fi IP family offers a comprehensive suite of platforms for embedding Wi-Fi 802.11a/b/g/n/ac/ax into SoCs/ASSPs. Optimized implementations are available targeting a broad range of connected devices, including smartphones, wearables, consumer electronics, smart home, industrial and automotive applications. CEVA also offers RISC-V based fully integrated platforms. 

Shanghai SiFlower Communication Technology was formally incorporated in 2014 and is headquartered in Zhangjiang Hi-Tech Park, Pudong, Shanghai, developing deciecs for the Internet of Things (IoT). 

Monday, October 15, 2018

Power news this week

From eeNews Europe by Nick Flaherty

. Dialog cashes in on Apple relationship

. CellCube spins out its vanadium mines

. Ceres to build £7m solid oxide fuel cell plant


. Printable thermoelectric energy capture for IoT systems

. Stability boost for high efficiency perovskite solar cells

. Silicon solar cell breakthrough tops efficiency limit

. Cabot teams with SAFT on low-cobalt cathodes for lithium-ion batteries


. Battery management system supports ASIL-C safety spec

. GaN thin film transistors for flexible substrates

. National Instruments: Key considerations for powertrain HIL test

. UnitedSiC: Practical considerations when comparing SiC and GaN in power applications

Samsung first to 5G commercial call

By Nick Flaherty

SK Telecom has this week made the first commercial 5G call, a key milestone for the industry, using equipment from Samsung Electronics.

The jointly-developed 3GPP 5G Non-standalone (NSA) new radio (NR) standard and commercial 5G NR equipment was part of the SKT's 5G testbed located in its Bundang office building.

The first 5G NSA-NR calls used a 100MHz bandwidth in the 3.5GHz band on the 5G NR radio, along with 4G LTE radio and NSA core.

In NSA-NR architecture, 5G is supported by the infrastructure of legacy 4G LTE where mobile devices are connected to both 4G and 5G for data traffic, while using the 4G network for non-data traffic such as exchanging signals for mobility controls. This approach has been considered as one of the promising 5G architectures for the initial 5G deployments

Saturday, October 13, 2018

NXP pushes security in move from M3 to M33 microcontroller cores

By Nick Flaherty

NXP Semiconductors is pushing the embedded security requirements of IoT edge devices and cloud to edge connections with two new multi-core microcontrollers based around the Arm Cortex M33 core.

NXP is emphasising its multi-layered, hardware-enabled protection scheme that protects embedded systems with secure boot for hardware-based immutable root-of-trust, certificate-based secure debug authentication and encrypted on-chip firmware storage with real-time, latency-free decryption.

These are used alongside Arm TrustZone for Armv8-M and Memory Protection Unit (MPU) to ensure physical and runtime protection with hardware-based, memory mapped isolation for privilege-based access to resources and data. 
“The promise of the connected world through the Internet-of-Things is extraordinary,” said Geoff Lees, senior vice president and general manager of microcontrollers at NXP. “Through NXP’s in-depth security and processing expertise, software ecosystem and breadth of portfolio, we are uniquely positioned to bring innovative and accessible advancements in IoT security to all developers.”

The key to this is a ROM-based secure boot process that uses device-unique keys to create an immutable hardware ‘root-of-trust’. The keys can now be locally generated on-demand by an SRAM-based Physically Unclonable Function (PUF) that uses natural variations intrinsic to the SRAM bitcells. This permits closed loop transactions between the end-user and the original equipment manufacturer (OEM), thus allowing the elimination of third-party key handling in potentially insecure environments. Optionally, keys can be injected through a traditional fuse-based methodology.

NXP is also working with Dover Microsystems to introduce Dover’s CoreGuard technology in future platforms. This is a hardware-based active defense security IP that instantly blocks instructions that violate pre-established security rules, enabling embedded processors to defend themselves against software vulnerabilities and network-based attacks.

The security environment improves the symmetric and asymmetric cryptography for edge-to-edge, and cloud-to-edge communication by generating device-unique secret keys through innovative usage of the SRAM PUF. The security for public key infrastructure (PKI) or asymmetric encryption is enhanced through the Device Identity Composition Engine (DICE) security standard as defined by the Trusted Computing Group (TCG). SRAM PUF ensures confidentiality of the Unique Device Secret (UDS) as required by DICE. The newly announced solutions support acceleration for asymmetric cryptography (RSA 1024 to 4096-bit lengths, ECC), plus up to 256-bit symmetric encryption and hashing (AES-256 and SHA2-256) with mbedTLS optimized library.

“Maintaining the explosive growth of connected devices requires increased user trust in those devices,” said John Ronco, vice president and general manager, Embedded & Automotive Line of Business, Arm. “NXP’s commitment to securing connected devices is evident in its new Cortex-M33 based products built on the proven secure foundation of TrustZone technology, while incorporating design principles from Arm’s Platform Security Architecture (PSA) and pushing the boundaries of Cortex-M performance efficiency.”

NXP strategically chose the Cortex-M33 core for its first full-feature implementation of the Armv8-M architecture to provide security platform benefits and substantial performance improvements compared to existing Cortex-M3/M0 MCUs (over 15 to 65 percent improvement, respectively). One of the key features of the Cortex-M33 is the dedicated co-processor interface that extends the processing capability of the CPU by allowing efficient integration of tightly-coupled co-processors while maintaining full ecosystem and toolchain compatibility. 

NXP has used this capability to implement a co-processor for accelerating key ML and DSP functions, such as, convolution, correlation, matrix operations, transfer functions, and filtering; enhancing performance by as much as 10x compared to executing on Cortex-M33. The co-processor further leverages the popular CMSIS-DSP library calls (API) to simplify customer code portability.

The LPC5500 devices provide single and dual core Cortex-M33 in a 40nm process with integrated DC-DC that delivers industry-leading performance at a fraction of power budget, up to 90 CoreMarks/mA. The high density of on-chip memory, up to 640KB flash and 320KB SRAM, enables efficient execution of complex edge applications. Further, NXP’s autonomous, programmable logic unit for offloading and execution of user-defined tasks delivers enhanced real-time parallelism. 

The i.MX RT600 crossover Platform is aimed at real time machine learning and artificial intelligence by adding a 600MHz Cadence Tensilica HiFi 4 DSP and shared on-chip SRAM of up to 4.5MB to a 300MHz M33 with a wide operating voltage. The ML performance is further enhanced in the DSP with 4x 32-bit MACs, vector FPU, 256-bit wide access bus, and DSP extensions for special Activation Functions (e.g., Sigmoid transfer function). 

Related stories:

Thursday, October 11, 2018

5G Toolbox for MATLAB

By Nick Flaherty

MathWorks has launched a toolbox for its Matlab tool that standards compliant waveforms and reference examples for modeling, simulation, and verification of the physical layer of 3GPP 5G New Radio (NR) communications systems. 

This will allow engineers using 5G Toolbox can quickly design critical algorithms and predict end-to-end link performance of systems that conform to the 5G Release 15 standard specification, starting the move to commercial system rollout in 2019. They can now use the toolbox for link-level simulation, golden reference verification, conformance testing, and test waveform generation – without starting from scratch.

The 5G Toolbox joins other toolboxes for LTE and WLAN standards, simulation of massive MIMO antenna arrays and RF front end technologies, over-the-air testing, and rapid prototyping of radio hardware.

“When adopting 5G, wireless engineers need to verify that their product designs can conform or co-exist with a new, complex standard that will continue to evolve. Very few companies have adequate resources or in-house expertise to understand and implement a 5G-compliant design,” said Ken Karnofsky, senior strategist for signal processing applications, MathWorks. “Having seen how LTE Toolbox has helped teams quickly deploy pre-5G designs in radio test beds, we anticipate 5G Toolbox will have a similar impact for the mainstream wireless market.”

5G Toolbox is the foundation of a design workflow that helps wireless teams rapidly develop, prototype, and test designs. Companies with siloed tools for RF, antenna, and baseband design; limited experience with MIMO technologies; or that lack automation from simulation to prototyping can now rely on MATLAB as a common environment for simulation, over-the-air-testing, and rapid prototyping.

MATLAB has also been used for 5G standards development by serving as a common research & development environment for multiple companies involved in the 3GPP working groups.

There's also a Q&A with Convida Wireless, a joint venture between Sony Corporation of America and InterDigital that focuses on research into the future of wireless connectivity technology at
Related stories:

Tuesday, October 09, 2018

Sprayable, transparent antennas for the IoT

By Nick Flaherty

Researchers at Drexel University’s College of Engineering have developed a technique for spraying invisibly thin antennas, made from a type of two-dimensional, metallic material called MXene, that perform as well as those being used in mobile devices, wireless routers and portable transducers.

“This is a very exciting finding because there is a lot of potential for this type of technology,” said Kapil Dandekar, PhD, a professor of Electrical and Computer Engineering in the College of Engineering, who directs the Drexel Wireless Systems Lab, and was a co-author of the research. “The ability to spray an antenna on a flexible substrate or make it optically transparent means that we could have a lot of new places to set up networks — there are new applications and new ways of collecting data that we can’t even imagine at the moment.”

Spray-applied MXene antennas could open the door for new applications in smart technology, wearables and IoT devices.

MXene titanium carbide can be dissolved in water to create an ink or paint and the high conductivity allows the printed structures to transmit and direct radio waves.

“We found that even transparent antennas with thicknesses of tens of nanometers were able to communicate efficiently,” said Asia Sarycheva, a doctoral candidate in the A.J. Drexel Nanomaterials Institute and Materials Science and Engineering Department. “By increasing the thickness up to 8 microns, the performance of MXene antenna achieved 98 percent of its predicted maximum value.”

“This technology could enable the truly seamless integration of antennas with everyday objects which will be critical for the emerging Internet of Things,” said Dandekar. “Researchers have done a lot of work with non-traditional materials trying to figure out where manufacturing technology meets system needs, but this technology could make it a lot easier to answer some of the difficult questions we’ve been working on for years.”

Initial testing of the sprayed antennas suggest that they can perform with the same range of quality as current antennas, which are made from familiar metals, like gold, silver, copper and aluminum, but are much thicker than MXene antennas. Making antennas smaller and lighter has long been a goal of materials scientists and electrical engineers, so this discovery is a major step in reducing their footprint as well as broadening their application.

“Current fabrication methods of metals cannot make antennas thin enough and applicable to any surface, in spite of decades of research and development to improve the performance of metal antennas,” said Yury Gogotsi, professor of Materials Science and Engineering in the College of Engineering, and Director of the A.J. Drexel Nanomaterials Institute, who initiated and led the project. “We were looking for two-dimensional nanomaterials, which have sheet thickness about hundred thousand times thinner than a human hair; just a few atoms across, and can self-assemble into conductive films upon deposition on any surface. Therefore, we selected MXene, which is a two-dimensional titanium carbide material, that is stronger than metals and is metallically conductive, as a candidate for ultra-thin antennas.”

Drexel researchers discovered the family of MXene materials in 2011 and have been gaining an understanding of their properties, and considering their possible applications, ever since. The layered two-dimensional material, which is made by wet chemical processing, has already shown potential in energy storage devices, electromagnetic shielding, water filtration, chemical sensing, structural reinforcement and gas separation.

“The MXene antenna not only outperformed the macro and micro world of metal antennas, we went beyond the performance of available nanomaterial antennas, while keeping the antenna thickness very low,” said Babak Anasori, a research assistant professor in A.J. Drexel Nanomaterials Institute. “The thinnest antenna was as thin as 62nm — about thousand times thinner than a sheep of paper — and it was almost transparent. Unlike other nanomaterials fabrication methods, that requires additives, called binders, and extra steps of heating to sinter the nanoparticles together, we made antennas in a single step by airbrush spraying our water-based MXene ink.”

The group initially tested the spray-on application of the antenna ink on a rough substrate — cellulose paper — and a smooth one — polyethylene terephthalate sheets — the next step for their work will be looking at the best ways to apply it to a wide variety of surfaces from glass to yarn and skin.

“Further research on using materials from the MXene family in wireless communication may enable fully transparent electronics and greatly improved wearable devices that will support the active lifestyles we are living,” said Anasori.

Rugged AI system for hostile environments

By Nick Flaherty

General Micro Systems (GMS) has launched a rugged, conduction-cooled, commercial off-the-shelf (COTS) deep learning/artificial intelligence (AI) mobile system that offers real-time data analysis and decision in hostile environments.

The X422 “Lighting” integrates two Nvidia V100 Tesla data centre accelerators into a fully sealed, conduction-cooled chassis. It is designed as a dual co-processor companion to GMS Intel Xeon rugged air-cooled or conduction-cooled servers

GMC claims this is an industry first for deep learning and artificial intelligence, as the X422 includes no fans or moving parts, promising wide temperature operation and massive data movement via an external PCI Express fabric in ground vehicles, tactical command posts, UAV/UAS, or other remote locations. It uses the company’s patented RuggedCool thermal technology to adapt the GPGPUs for harsh conditions, extending the temperature operation while increasing environmental MTBF.

“No one besides GMS has done this before because we own the technology that makes it possible. The X422 not only keeps the V100s or other 250 W GPGPU cards cool on the battlefield, but our unique x16 PCIe Gen 3 FlexVPX fabric streams real-time data between the X422 and host processor/server at an astounding 32 GB/s all day long,” said Ben Sharfi, chief architect and CEO, General Micro Systems. “From sensor to deep learning co-processor to host: X422 accelerates the fastest and most complete data analysis and decision making possible.”

The X422, which is approximately 12x12 inches square and under 3 inches high, includes dual x16 PCIe Gen 3 slots for the GMS-ruggedized PCIe deep learning cards. Each card has 5120 CUDA processing cores, giving X422 over 10,200 GPGPU cores and in excess of 225 TFLOPS for deep learning. In addition to using Nvidia GPGPU co-processors, the X422 can accommodate other co-processors, different deep learning cards, and high-performance computers (HPC) based upon FPGAs from Xilinx or Altera, or ASICs up to a total of 250 W per slot (500 W total).
Another industry first brings I/O to X422 via GMS’s FlexVPX bus extension fabric. X422 interfaces with servers and modules from GMS and from One Stop Systems, using industry-standard iPass+ HD connectors offering x16 lanes in and x16 lanes out of PCI Express Gen 3 (8 GT/s) fabric for a total of 256 GT/s (about 32 GB/s) system throughput. X422 deep learning co-processor systems can be daisy-chained up to a theoretical limit of 16 chassis working together.

Unique to X422 are the pair of X422’s two PCIe deep learning cards that can operate independently or work together as a high-performance computer (HPC) using the user-programmable onboard, non-blocking low-latency PCIe switch fabric. For PCIe cards with outputs—such as the Titan V’s DisplayPorts—these are routed to separate A and B front panel connectors.