Access the latest quantum technology

Quantum technology in Bristol and bath - find out more about how you can access the commercialisation of quantum technology for sensing and security

Tuesday, October 15, 2019

Pixel 4 smartphone adds Infineon 60GHz radar chip

By Nick Flaherty

Infineon is supplying a 60GHz radar system for gesture detection in the next generation Pixel 4 smartphone being developed by Google.

An integrated antenna system in the XENSIV BGT60TR13C package allows sensing of the presence and movement of people and objects with high precision or measures distances and speeds. This chip is the base for Google’s Soli technology and has now been integrated for the first time into a smartphone for gesture control.

"With our radar technology devices become 'context-aware’. This means that they can finally understand their environment and react much more purposefully," says Andreas Urschitz, Division President for Power Management and Multimarket at Infineon Technologies. "The precise motion detection by the 60 GHz radar chip turns the Google Pixel 4 smartphone into a gesture control system. This is a revolution in the human-machine-interaction. At Infineon, we are furthermore working on the fusion of multiple sensors to simplify interaction and increase the usefulness of the devices."

Infineon’s radar technology has its roots in the automotive sector. Radar sensors have been effectively measuring distances, speeds and movements while driving for decades. Infineon has further developed these functions for small devices. The 60 GHz chip is a complete radar system with antennas on a very small area (5 x 6.5 mm) coupled with low power consumption. The BGT60 family has a transmit current of 480mA at 3.3V, giving a power consumption in use of 1.5W, which is high for a smartphone but the previous devices were aimed at tethered applications such as smart speakers with a sensing distance from 20cm to 5m. However the overall power usage of the sensor will depend on the software controlling the duty cycle, or how often it is used, as it is only likely to be used in infrequent short bursts. This version will be optimised for shorter distances from 1cm to 1m, which will reduce the power consumption by potentially by a factor of 5. Further circuit optimisations will reduce that further, and we’ll publish the figures when we get them. 

The radar sensor can perceive movements in rooms or measure distances from objects in the millimetre range with utmost precision. With the appropriate software, the motion data is converted into functions, so that control via gestures is possible without touching the device.

 The fusion of multiple sensors in a single device creates new solutions that measure and improve air quality or intelligently control burglary protection, for example. In addition to voice-controlled assistants, 'intelligent' household appliances or wearables, buildings, so-called smart buildings in particular, are becoming more interactive. Sensors detect the number of people in the rooms or can adjust the need for light sources to improve safety and energy efficiency.

Monday, October 07, 2019

NXP ARM multicore processors get Lynx hypervisor

By Nick Flaherty

NXP's QorIQ Arm-based processors can now use the LynxSecure Separation Kernel Hypervisor for to keep applications separate in avionics designs.

Lynx has ported LynxSecure onto the NXP QorIQ Layerscape 1046A (LS1046A) multicore communication processor integrating quad 64-bit Arm Cortex-A72 cores. This joins the existing support for NXP S32V234 MPSoC.
“Multicore architectures are seeing increasing adoption in avionics systems due to performance requirements and the lack of availability of single core processors," said Geoff Waters, Senior Principal Engineer at NXP Semiconductors and Chairman of the NXP- led Multicore for Avionics Working Group. "The porting of LynxSecure separation kernel hypervisor technology is an important step forward. It offers an exceptional technology for managing the complexity associated with multicores, reducing the design and certification time for safety critical systems based on NXP Layerscape SoCs.”

David Beal, Director of Product Marketing at Lynx Software Technologies, added, “Increasingly, avionics, transportation and other safety-critical systems rely on redundant platforms. Now, system architects and engineers who have strict requirements around performance, safety and security can take full advantage of the features and capabilities offered by NXP LS1046A within a straight-forward, secure-by-design software systems architecture that is enabled by LYNX MOSA.ic. The combination results in high performance and immutable security while preserving modularity and providing a natural path for future software-migration as newer, processing platforms become available.”

The LynxSecure separation kernel forms the foundation of the LYNX MOSA.ic framework to address markets such as avionics, transportation, industrial and medical systems. By providing the highest levels of performance, security and safety protections, LYNX MOSA.ic enables complex, systems that are responsible for both critical and non-critical functions. This reduces system design, integration, test and certification efforts.

Thursday, September 19, 2019

First fanless 100W edge and micro servers in COM Express format

By Nick Flaherty

congatec has launched a range of 100W embedded edge and micro servers in the COM Express Type 7 Server-on-Module format for fanless operation.

The range initially targets the recently launched conga-B7E3 modules featuring 3 GHz dual-die processors of the AMD EPYC Embedded 3000 series that supports a maximum TDP thermal envelope of 100 Watt, up to 16 cores and 32 threads. 

These are the first 100W Server-on-Modules in the COM Express Basic form factor (95 x 125 mm) that now have new heat spreaders and heatpipe adapters for an efficient heatpipe cooling even of extremely low profile 1U servers. By designing systems in such a way that does not use rotating fans, it is possible to develop extremely robust embedded servers that are suitable for numerous applications at the IoT/Industry 4.0 edge.

These 100W systems can be used for 5G telecom cloudlets, Industry 4.0 servers, smart robot cell servers with collaborative robotics, autonomous robotic and logistics vehicles with high speed vision and other situational awareness sensors. The ecosystem is further suitable for virtualized on-premise equipment in harsh environments to perform functions such as industrial routing, tactile internet, firewall security and intrusion detection systems, as well as VPN technologies - optionally in combination with various real-time controls and neural network computing for Artificial Intelligence (AI).

"Embedded edge servers must meet ever increasing multifunctional performance requirements while operating in harsh environmental conditions where shocks and vibration are common. Rugged fanless system designs are thus required. Until today, this ecosystem was limited to a performance class of up to approximately 65 Watt. Now, congatec has extended the capabilities of fanless designs to conduction cooled 100 Watt systems. This enables an impressive performance boost of 53% for rugged fanless COM Express Type 7 designs," said Nano Chu, R&D Manager at congatec in Taipei.

In addition to the new cooling solutions, the range includes starter kits with the two different application-ready server-grade carrier boards conga-X7EVAL and conga-STX7 that, among other things, execute four 10 GbE interfaces, which are server-compatible with SFP+ cages for both copper and fiber optic cables. Exemplifying edge server rack and box system designs, the kits can be modified to customer specifications. Relevant hardware engineering services for embedded edge server platforms round off the congatec 100 Watt ecosystem for Server-on-Modules.

Software support includes real-time configurations to avoid latencies caused by processor-side TDP management and, above all, support for the comprehensive RAS (reliability, availability and serviceability) features common to all AMD EPYC Embedded 3000 processors. These enable the same efficient remote system monitoring, management and maintenance capabilities to optimise the total cost of ownership (TCO) in distributed deployments as known from commercial-grade data centres. 

Edge applications benefit from the hardware-integrated virtualisation and leading-edge security features of the AMD EPYC Embedded 3000 SoC that includes Secure Boot System, Secure Memory Encryption (SME) and Secure Encrypted Virtualization (SEV), as well as a secure migration channel between two SEV-capable platforms. Support is also provided for IPsec with integrated crypto acceleration. As a consequence, even the server administrator does not have access to such an encrypted Virtual Machine (VM). This is very important for the high security required by many edge server services, which must enable multi-vendor applications in Industry 4.0 automation while helping ward off sabotage attempts by hackers.

Tuesday, September 17, 2019

Qualcomm buys out RF360 for 5G front end filters

By Nick Flaherty

Qualcomm has bought out its partner in the RF360 joint venture that develops complex front end filters for 4G and 5G. 

RF360 was set up with TDK Electronics (formerly EPCOS) to develop RF front end (RFFE) filter technologies such as BAW, SAW, TC-SAW, as well as Thin Film SAW. These are used for developing and producing filters, duplexers, multiplexers for discrete, power amplifiers and diversity modules, as well as n-plexers and extractors.

The deal gives Qualcomm Technologies the complete signal chain from  modem to antenna, combining the Snapdragon 5G Modem-RF System with 5G New Radio (NR) sub-6 and mmWave solutions, integrating power amplifiers, filters, multiplexers, antenna tuning, LNAs, switching and envelope tracking products.

Qualcomm Technologies has already developed wideband envelope tracking and adaptive antenna tuning that combines the modem and RFFE aimed at future smartphone designs.

This acquisition is the final step in the signal chain. “Our goal in the formation of this joint venture was to enhance Qualcomm Technologies’ front-end solutions to enable us to deliver a truly complete solution to the mobile device ecosystem, and we have done exactly that,” said Cristiano Amon, president of Qualcomm. 

“We are excited about the strong adoption of Qualcomm Snapdragon 5G Modem-RF Systems in virtually all of our 150+ 5G design wins. Our systems approach has created a benchmark for 5G RFFE performance. I am very pleased to formally welcome to Qualcomm the talented employees of the joint venture, who already have been an integral part of the Qualcomm Technologies RFFE team, and I look forward to celebrating even more innovation as we continue to invent breakthrough technologies on the path towards a 5G connected world. Additionally, I would like to thank our long-time partner TDK. We look forward to continued opportunities to collaborate and to bring leading products from both companies to the market in the years ahead.”

TDK's interest in the joint venture was valued at $1.15bn in August 2019. The total purchase price, including the initial investment, payments to TDK based on sales by the joint venture, and development obligations, will be approximately $3.1bn.

Tuesday, September 10, 2019

German battery gigafactory ... Bosch teams for 48V hybrid batteries ... an 'invisible' solar roof for a car ... GaN transistors on a single crystal of diamond

Power news this week by Nick Flaherty at eeNews Europe

. Northvolt to build German battery gigafactory with Volkswagen

. Bosch teams with CATL on 48V hybrid battery production

. Faraday adds four battery research projects in £55m boost


. EV range boost from 'invisible' solar roof

. Coating boosts commercial lithium metal battery developments

. GaN transistors use single crystal of diamond as substrate


. First CAN FD Class 3 compatible common mode choke coil

. Rugged 80W DC-DC converter has 10 year warranty

. 600W medical power supply meets MIL-STD-810G shock and vibration

. Development and Deployment Strategies for Xilinx's RFSoC FPGA

. A Guide to Selecting Current Sensors and Transformersa

Facial recognition tech improves hail forecasts

By Nick Flaherty

The same machine learning technology used for facial recognition systems could help improve prediction of hailstorms and their severity, according to a new study from the National Centre for Atmospheric Research (NCAR) in the US.

Instead of zeroing in on the features of an individual face, scientists trained a convolutional neural network (CNN) to recognise features of individual storms that affect the formation of hail and how large the hailstones will be, both of which are notoriously difficult to predict.

The results, published in the American Meteorological Society's Monthly Weather Review, highlight the importance of taking into account a storm's entire structure, which has been hard to do with existing hail-forecasting techniques.


"We know that the structure of a storm affects whether the storm can produce hail," said NCAR scientist David John Gagne, who led the research team. "A supercell is more likely to produce hail than a squall line, for example. But most hail forecasting methods just look at a small slice of the storm and can't distinguish the broader form and structure."

"Hail - particularly large hail - can have significant economic impacts on agriculture and property," said Nick Anderson, an NSF program officer. "Using these deep learning tools in unique ways will provide additional insight into the conditions that favour large hail, improving model predictions. This is a creative, and very useful, merger of scientific disciplines."

Whether or not a storm produces hail hinges on myriad meteorological factors. The air needs to be humid close to the land surface, but dry higher up. The freezing level within the cloud needs to be relatively low to the ground. Strong updrafts that keep the hail aloft long enough to grow larger are essential. Changes in wind direction and speed at different heights within the storm also seem to play a role

But even when all these criteria are met, the size of the hailstones produced can vary remarkably, depending on the path the hailstones travel through the storm and the conditions along that path. That's where storm structure comes into play.

"The shape of the storm is really important," said Gagne. "In the past we have tended to focus on single points in a storm or vertical profiles, but the horizontal structure is also really important."

Current computer models are limited in what they can look at because of the mathematical complexity it takes to represent the physical properties of an entire storm. Machine learning offers a possible solution because it bypasses the need for a model that actually solves all the complicated storm physics. Instead, the machine learning neural network is able to ingest large amounts of data, search for patterns, and teach itself which storm features are crucial to key off of to accurately predict hail.

For the new study, Gagne trained the model using images of simulated storms, along with information about temperature, pressure, wind speed, and direction as inputs and simulations of hail resulting from those conditions as outputs. The weather simulations were created using the NCAR-based Weather Research and Forecasting model (WRF).

The machine learning model then figured out which features of the storm are correlated with whether or not it hails and how big the hailstones are. After the model was trained and then demonstrated that it could make successful predictions, Gagne took a look to see which aspects of the storm the model's neural network thought were the most important. He used a technique that essentially ran the model backwards to pinpoint the combination of storm characteristics that would need to come together to give the highest probability of severe hail.

In general, the model confirmed those storm features that have previously been linked to hail, Gagne said. For example, storms that have lower-than-average pressure near the surface and higher-than-average pressure near the storm top (a combination that creates strong updrafts) are more likely to produce severe hail. So too are storms with winds blowing from the southeast near the surface and from the west at the top. Storms with a more circular shape are also most likely to produce hail.

The next step is to also begin testing it using storm observations and radar-estimated hail, with the goal of transitioning this model into operational use as well. Gagne is collaborating with researchers at the University of Oklahoma on this project.

"I think this new method has a lot of promise to help forecasters better predict a weather phenomenon capable of causing severe damage," he said. "We are excited to continue testing and refining the model with observations of real storms."