The first time I saw a wireless electronic shelf label, it was virtually indistinguishable from the old-fashioned paper labels I was accustomed to. I only realized it was electronic when the price changed before my eyes. These electronic paper displays (EPDs) are changing the retail game. What once took hours or even days, with a person walking around manually updating shelf labels and industrial signage, can now be done in seconds. The EPDs have reflective properties that only require ambient light to be visible, meaning they don’t have the glare of typical electronic displays. This makes the displays more like the pages of an e-reader that mimics what it’s like to read a paper book. They are also bistable, which means they can retain an image even when no power is connected.
The pixels of an EPD are composed of millions of tiny microcapsules, each about the diameter of a human hair. E Ink, a pioneer in electronic signage, developed its 3-pigment ink system specifically for electronic shelf labels. It works by applying a charge to the pigments and to a top and bottom electrode to facilitate movement. Since EPDs have the ability to draw zero current, the power consumption of the microcontroller unit (MCU) and the rest of the application is very low, and therefore, ideally suited for these applications.
Our EFR32 MCU is a great fit for EPD applications due to its energy efficiency and storage capacity. To help developers get started, we’ve put together this Application Note showing how to drive an EPD with the EFR32xG22-based Wireless Starter Kit. You can also find more info on our GitHub page. The flexible energy modes of the EFR32 allows the MCU to draw as little current as possible and in many cases the MCU’s Energy Mode 4 can be used, resulting in power consumption as low as 170 nA. Memory is another important feature for saving frame buffers and images and the EFR32 has large memory options, both for Flash and SRAM. This application note also makes use of E Ink’s EPD extension board, which is available along with a HULK Driving Board here.
Even though the EPDs draw no current while showing a static image, they require a significant amount of current while updating the display, which is the only time they consume any power. An update can take between 12-18 seconds at room temperature, and aside from the time requirements, the MCU must complete the power-up/power-down sequences and transmit frames to the panel. For this reason, EPDs are not suited to applications that require a high update frequency.
The app note discusses ways to optimize power consumption during a display update, including putting the MCU into its optimal energy mode. Learn more about how electronic shelf labels contribute to retail infrastructure here, and if you set out to develop an EDP, we’d love to hear how your project is going.
We recently had the chance to speak with Morten Møgelmose, Co-Founder and CEO of Zliide, a Danish company merging the digital and physical realms of the fashion retail world. Zliide’s Bluetooth security tags bridge the gap between virtual and in-store retail experiences, providing a seamless and heightened customer experience. Zliide tags connect with shoppers’ smart phones, allowing them to conveniently self-checkout at any moment and access product information, photos, and videos to enhance their shopping experience. The tags also provide valuable data for retailers, giving key insights into specific stores, items, and customer preferences. Below Morten shares background on the company’s overall mission and insights behind how the company’s innovative tag technology works.
Can you tell us a little bit about Zliide?
Zliide is a Danish company founded in 2016 with a vision to always take the consumer’s point of view first. Fashion retail has always been really good at providing consumers with a great “wow” experience when they come into the stores, but a lot of the stores have forgotten the digital evolution of customers. Our solution enables fashion retailers to provide an omnichannel experience, combining offline experience with online experience. This is done through what we call the Zliide tag, which goes onto every piece of merchandise in the store. The tag operates like a standard security tag, but allows users to scan the tag with the Zliide app and gain access to a digital version of the item in the app. This can show videos and images of the item on a model or in motion, allowing shoppers to really envision themselves in the merchandise. The consumer can then pay for the item on their phone, using a mobile payment application. Once the item is paid for, the security tag unlocks, and the customer is able to leave the store with their purchase. Right now, our technology is only available in Denmark, but we are looking to expand to other Nordic countries and perhaps the U.K. in the next couple of years.
Why was the Zliide tag created?
The whole company started based on an experience I had in a Nike store in London. When I arrived in London, I used Airbnb and Uber, and everything was with one click. Then I went into a store and actually had to wait for someone to help me get rid of my money and make a purchase. I was really frustrated because over the last few years I had become accommodated to using numerous cool technologies with easy user experience and convenience across all different channels. This experience led me to start a company with a vision to always take the consumer’s point of view first.
How is your Zliide tag different from other commonly seen security tags in fashion stores?
The basic purpose of a conventional tag is securing a piece of clothing. The conventional security tags business is great and meets a basic and much-needed functionality. We definitely believe tags have a place in the market indefinitely, but we also believe that if you already mount a piece of hardware onto every single item in a store, there is so much potential to build on top of the tag for data collection and a better consumer experience.
With our product, we enable customers to interact with every item in the store and access pictures and videos of everything they want, anywhere they want. It’s all about freedom and convenience for the stores and the consumers, along with the possibilities of building a data collection for retailers. We allow communication with the end user’s mobile device by introducing Bluetooth to the tag. We've done this in the Zliide tag version we are introducing to the market now with Silicon Labs' BGM220. Also, in recent years, we’ve seen a rise in RFID tags that allow resellers to do a limited inventory count with RFID scanners. With our solution, retailers have the added benefit of doing an immediate daily inventory count.
Why did you decide to use Silicon Labs' solutions for the product?
We were introduced to Silicon Labs through Arrow and have been extremely impressed with the company's representatives, who introduced us to the BGM220 and its features.
All of the functionality we wanted was met in terms of security, battery lifetime and the possibility of over-the-air (OTA) updates, as it would be a big risk to not be able to easily update the software. On top of that, by using the module we were really able to minimize the size and the number of components on the PCB. Another important factor for us was to reduce cost of the device due to mass production – one fashion store can easily have 10,000 Zliide tags.
I would say one of the things that really made a difference for us was the superior level of support we have received from Silicon Labs. For us, it's really about the support and the commitment we've received to help a young company like ours to really thrive in a competitive world. Getting access to those valuable and knowledgeable resources to build a better product is really what made the whole difference for us.
Where do you see fashion retail IoT going in the next 5-8 years, and how has COVID-19 affected the market?
From a technology perspective, we see a lot of technology evolving in the retail sector at the moment. Recently we've seen a lot of investments going into the back end of retail companies to optimize the supply chain. I believe if you have a big footprint of stores, you need to take those stores and elevate them to the next level with consumer-facing technology. I think we will see technology in the fashion retail industry still being a little bit behind some of the other retail outlets such as supermarkets, convenience stores, etc. The fashion industry has high-value items that they want to protect, whereas in convenience stores and supermarkets, there's basically no security there; you can just use a barcode scanner to speed up the customer experience. Our technology will be the fastest solution to allow self-checkout for more high-value items.
COVID-19 had a major impact on more than just revenue streams in these fashion retail companies, and collectively the industry has realized how vulnerable it is. When it comes to shutting down all your stores, you’re losing 80-90% of the revenue from one day to another. I think it made retailers realize two things: For one, they need to do something different now. And two: they need to realize that digitalization is the only way to go. If COVID-19 restrictions go into effect again, retailers would still have access to users on the Zliide online platform with the ability to purchase something from their store. Even though stores would be physically closed, retailers could still ship out from the stores through this massive footprint.
In five years, we'll see a lot changing in the industry, and the ones who don't keep up with technological advancements will be the losing companies, no doubt about it.
Find out more about how our BGM22 Series here.
We recently had the opportunity to speak with two authors using new and unconventional animal tracking research: biologist Simon Ripperger of the Department of Evolution, Ecology, and Organismal Biology at Ohio State University and engineer Niklas Duda of the Institute for Electronics Engineering, Friedrich-Alexander-University Erlangen-Nuremberg (FAU) in Germany. The talented duo’s animal tracking research went viral in October when one of their new studies confirmed that vampire bats in the wild socially distance themselves when sick.
The social distancing study was one of several consecutive case studies published since 2019, detailing the first-of-its-kind wireless biologging network they designed to track and study wild bats. The new biologging technology allows for simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download – all of which enabled their team to collect never-before-available data and observations on bats in the wild. The wireless sensor network has not only resulted in riveting findings about the social nature of bats, it has also opened the door to a new realm of scientific knowledge concerning the spread of infectious diseases, wildlife resources, foraging strategies, and physiology. The two brilliant scientists explain how their research came about and how new technology is enabling scientists and animal conservation experts to break boundaries in animal biologging.
Tell us how you all started working together and give us some background on your bat studies.
Simon: I’ve been involved with this project since the end of 2013 and was inspired by my advisor, who is also a bat biologist. He used to go to Greece for field work all the time, but their method of tracking and biologging bats was a bit unbelievable – he was essentially running behind bats, chasing them with an antenna. We knew there had to be a better way to do this, and the university had a long history of cooperation between computer scientists, engineers, and biologists. They decided to create a big, collaborative project on wireless sensor networks using a fully automated tracking system for bats.
Bats are a great species to start with because they’re elusive –it’s hard to observe them, and they're nocturnal and tiny. If your project can succeed with bats, it can probably work with most species. This was the motivation for the research unit, which was funded by the German Research Foundation (DFG – Deutsche Forschungsgemeinschaft).
Can you tell us more about the wireless sensor network and how it gathers information?
Simon: I would say it is the most sophisticated sensor network for biologging –the degree of automation and data quality is certainly unique because we’ve combined different functionalities. We have high-resolution tracking to allow us to track animals with tags at small scales, and we also do proximity sensing. The tags can be as light as one gram, including housing and battery. If you look at systems for GPS tracking, the remote download function costs several grams because it’s so expensive in terms of energy. This all adds considerable weight to the tags, so it’s amazing to have this 1-gram tag with the option to retrieve data remotely.
For me as a biologist, the most exciting function is the proximity tracking. The tags talk to each other and exchange information, so we can get social networks of an entire group of animals every few seconds—simply mind-blowing if you have been studying social networks in animals—and the data quantity is amazing.
Why did you choose Silicon Labs for your wireless network?
Niklas: We have used Silicon Labs EFR32 SoCs since 2017 in all of our studies. Our tags have proximity logging and localization functions that operate at two different frequency levels. Before using Silicon Labs, we had to use three separate ICs to accommodate these functions. However, the Silicon Labs Flex Gecko integrates transceivers for both frequencies and a microprocessor core in one component. The ability to scale from three components to one makes the PCB smaller and makes it easier to control the radios, resulting in overall improved performance. We also wanted the Silicon Labs Gecko solution for its ultra-low-power functions. When tagging animals, we need our solution to be as small, light, and low power as possible, and Silicon Labs solutions support this need.
Can you tell us more about what you have learned about bats from your studies with the technology?
Simon: The first study we conducted was on noctule bats: European bats that live in city parks. Every few days, the bats switch their roosting site; therefore, we wanted to find out how offspring know where the group’s ever-changing roosting sites are located. Up until now, this has been impossible to track. With our wireless network, we found that mothers actually guide their pups to the new roosting sites; they leave the roost together, fly together, and arrive at the new roost together. This first simple application of our proximity sensing discovered a whole new form of maternal care in bats.
We then moved on to studying vampire bats, the most social species of bats. They have social connections similar to human friendships as they recognize each other, prefer to associate with certain individuals from a group, groom each other, and even share food. This behavior has been studied mainly in captivity because it’s so hard to observe bats in the wild. We were able to use our proximity sensors to see whether these social behaviors are simply an artifact of captivity or whether they held up in the wild. We took bats in captivity that we knew had social relationships with one another and released them back to the wild after two years. We could track associations between all the bats in their natural habitat and show that these social relationships were maintained in the wild, even with new bats to interact with and in a totally different setting. It showed for the first time that these relationships are very stable and persist in the wild. There would be no way to observe these behaviors without this technology.
One of your studies was widely covered by international media this past fall. Can you tell us about what you found?
Simon: We used our wireless network to observe bats' social networks and how they are affected when a bat is sick. We gave half the group an immune-challenging substance—a substance that doesn’t actually make them sick but makes the immune system react. With our high-resolution data, we could observe what happens to the network when the bats get sick. We found that their social encounters decreased –what we call social distancing –and after this period of sickness, the level of interaction with the “sick” bats went back to normal. Essentially, we found they manage to distance themselves from the group when they feel sick.
What are your future plans for studies?
Niklas: We’re spinning out a company, Dulog, to sell this technology to use with other animals. The technology is in development with several pilot customers and should be commercially available later this year.
Simon: The applications have no end – from preventing the spread of infectious diseases to studying information flow among social animals on food resources and even mating behavior—the sky is the limit! Why do social animals behave the way they do? With our technology, you can now observe their natural behaviors without interfering, but you can also use it to see how animals react to experimental approaches in the wild.
Where do you see the IoT going in the next 5-8 years?
Niklas: As IoT develops, sensors are getting smaller, which really benefits the scientific community – we reap the benefits of IoT that the larger commercial markets drive.
Simon: For biology, leaps forward have always been inspired by technology. Animal tracking has been around for 50 or 60 years, but advancements in IoT have allowed these recent developments to create a true renaissance in biologging and animal tracking. You can use benefits from ultra-low-power computing in various aspects of biology studies, and we not only get better data, but we can get it for a much wider range of animal species.
For more information on our EFR32 technology, visit https://www.silabs.com/products/wireless/technology.
After being forced to adopt an online-only format due to the COVID-19 crisis, CES 2021 retained its spot as the world’s premier can’t-miss tech bonanza. Though frustratingly hands-off, the event still managed to dazzle with a diverse roster of speakers, tons of virtual sessions, and hundreds of new product announcements. One speaker in particular, Walmart CEO Doug McMillon, stood out to us as a pretty apt representative for what we’ve seen from our customers in the ways they’re tackling not just the technological advancements, but the societal changes happening before our eyes. The world’s most recognizable big-box chain isn’t exactly where you’d expect to go for innovation, but Doug’s live Q&A focused on how the retail giant is updating its tech stack with an emphasis on connectivity and data management to provide better customer experiences. His remark that ‘every company is a tech company’ is a great statement going into 2021.
This was a theme this year’s speakers returned to throughout the event - the convergence of technology and social corporate responsibility – and here are some of the key insights from CES 2021 and where Silicon Labs will be making an impact.
Sustainability Through the Smart Application of Technology
Technology has always been part of farming and improving agriculture outcomes, specifically being able to grow food crops more efficiently and sustainably, and it requires an approach to technology adoption that goes beyond traditional equipment updates. John Deer hired its first chief technology officer, Jahmy Hindman, in 2020 and he’s adjusted the company’s aperture from heavy equipment to include a new Intelligent Solutions Group that will focus on hardware and devices, embedded software, connectivity, data platforms, and applications. Jahmy’s session, Feeding the World with Precision Tech, focused on the ways elevating data insights can make agriculture as predictable as possible. Global demand for food is expected to increase by 50 percent over the next 30 years, which will put enormous pressure on agricultural productivity. Bringing just a little more predictability into a notoriously unpredictable industry through data-driven, precision planting can result in smarter farming decisions that deliver larger crop yields. John Deere’s high-capacity X-Series Combine Harvester won a CES 2021 Best of Innovation Award in the Robotics category.
EVs were also heavily featured this year, including a sneak peek at GM’s Cadillac Celestiq and the further-out 2023 Cadillac Lyric electric SUV. And this was just a taste of what’s to come from automobile manufacturers in pursuit of sustainability. GM alone is planning 30 all-electric vehicles by the end of 2025 on the strength of a nearly $30 billion investment. Sono Motors also made a splash with its introduction of the Sion, a mass market solar electric vehicle (SEV). With roughly 250 solar cells integrated into the body of the Sion, the car can be 80 percent charged in a half-hour – and it can share its power to charge other EVs. Making this technology accessible is the last barrier to mainstream adoption and Sono seized its CES moment to make a compelling case for urgent sustainability from the automotive industry.
AI and Machine Learning will Drive IoT Innovation
We’ve recognized AI and machine learning in IoT edge devices as one of the keys to making IoT devices trainable, actionable, and capable of extracting information and learning from the environment. CES 2021 validated this observation with the sheer volume of contextually aware devices being introduced. At Silicon Labs we have a soft spot for developers and Unity MARS, which was recognized as a CES 2021 Innovation Award Honoree and is helping creators build AR experiences more easily. The accessibility of tools like this empowers people to create VR and AR applications who would never have been able to before, opening up the development of all kinds of new IoT products and use cases.
Moving Healthcare Away from the Doctor’s Office and into the Home
Even before CES was moved online by one of the most significant health crises in generations, health and well-being has been an even staple. But this year high-performance computing, coupled withAI, took on more significance. One of our IoT Heroes, Airthings, introduced a new function of its Wave Plus that can actually analyze rooms and determine virus risks. The sensor doesn’t actually detect the virus itself but uses other information to determine the risk of possible transmission. Variables including temperature, humidity, and the number of people present based on CO2 emissions helps score the likelihood of a virus circulating move around the room. A low score triggers a suggestion like increasing airflow or asking some guests to leave.
This aligns with our observation that COVID-19 has compelled the healthcare industry to shift care away from clinical settings and into the home. Once rarely used remote treatment options like telemedicine are going mainstream and more patients routinely use video conferencing on smartphones and tablets to minimize in-person visits to doctors’ offices, clinics, or hospitals by interacting directly with healthcare workers through their connected screens. Physicians are increasingly prescribing smart medical monitoring equipment like pulse oximeters, heart rate monitors, and blood glucose monitors to patients on a more frequent basis. Smart medical device manufacturers are racing to add new connectivity technology like Wi-Fi and Bluetooth into these devices to connect to them to the internet. Through these new connected smart medical devices, doctors can instantly assess their patients’ status and render treatment remotely, helping to ensure valuable hospital beds remain available for those who truly need inpatient care.
Like most of the industry, CES is an important part of Silicon Labs’ calendar. Learning that it would be remote this year was actually one of the true harbingers of just how serious the global pandemic was being treated. We missed being in Vegas and missed seeing our friends and colleagues, and most of all we missed being up close and personal with all of the ways these companies are bringing the power of connectivity to bear on today’s problems. But over the last four days we’ve been encouraged by the resilience of our industry and inspired by how past innovations in connectivity, networking, and access to development tools are making all of these things possible in pretty trying and unprecedented circumstances.
We’re looking forward to seeing you there in person next year!
As a developer, you know that not all dev kits are equal. The features can make a huge difference in your development process. While most development kits out there do their job just fine – i.e., allow you to convert an idea into a prototype with a decent effort, there are also poorly designed kits, which can turn your project into a nightmare. However, an excellent development kit removes many headaches from your work, speeds up tracing and debugging, and provides interfaces for expansion.
But what makes a great Bluetooth dev kit? In this blog, we look at five powerful features that can accelerate IoT prototyping and enable you to create epic IoT products rapidly!
Rapid IoT prototyping sounds like yet another buzzword brewed inside the developer community. However, it's more than that. Rapid prototyping perfectly captures the way IoT products are created today. Developers build multiple iterations of their software and hardware design quickly and get early user feedback. This allows them to adjust the design based on actual user-experience and finalize a successful prototype rapidly.
There are two types of development tools for rapid IoT prototyping. You can build a prototype on Arduino or Raspberry Pi and complete the project with another, more professional software and hardware platform. However, more advanced developers prefer to craft everything from scratch with dev kits based on commercial chipsets – they allow more room for customization, and the final build is closer to a real product rather than a hobbyist experiment.
So, what do you need from a dev kit to rapidly prototype an epic Bluetooth IoT product? Here's a rundown of five powerful Bluetooth dev kit features that speed up your development work:
You spend a significant share of your prototyping time debugging software and hardware. A debugger is perhaps the most critical component of a Bluetooth dev kit, yet many available kits do not come with a debugger!
When choosing your next Bluetooth dev kit, make sure it hosts an on-board debugger to avoid having to buy a separate board. A debugger built on the board streamlines your dev work because you can simply flash the code and debug as it runs in the target processor. Also, on-board debuggers are typically compatible with the vendor's integrated development environment (IDE), giving you more advanced debugging capabilities.
All in all, a Bluetooth Dev Kit with a built-in debugger saves you from buying an extra board, minimizes the hassle, and speeds up development work and prototyping.
Developing wireless products, including Bluetooth devices without a traffic tracer, is hard. You can't see what's going on in the wireless link when you run into issues in the Bluetooth protocol level without a tracer, which makes troubleshooting pure guesswork.
A dev kit with a built-in packet tracing interface, on the other hand, allows you to capture the raw Bluetooth traffic flowing into the system and analyze it with a network analyzer tool. The analyzer decodes the data into a human-readable BLE protocol format, which makes debugging a breeze.
A packet tracer interface on a Bluetooth dev kit offers invaluable debug information about transmitted and received packets in wireless links, removes the guesswork from debugging, and speeds up prototyping significantly.
When kicking off prototyping, the first thing you do is to set up a serial line between the target and PC to get data logging going and commands flowing back to the processor. This allows high-level debugging – you can find out which parts of the code are not working before making the first deep-dive.
Getting a Bluetooth dev kit with a built-in virtual com port will save you from buying an external board for UART-to-USB bridging, and, again, you can remove much hassle from your project and get your prototype off the dev board faster.
Let's face it; nobody wants to buy a Bluetooth IoT product in 2021 without a smooth smartphone App and over-the-air (OTA) software update. Suppose you want to develop excellent smartphone connectivity and OTA capability for your product, a Bluetooth dev kit with support for a generic BLE mobile app tester with OTA should be on your shopping list. It will save significant development time and helps you to launch a convincing, market-ready prototype rapidly.
No developer wants to waste precious time building every component from scratch, especially when many hardware ecosystems offer vast amounts of off-the-shelf components. However, with a dev kit, which lacks standard interfaces to hardware ecosystems, you can forget about rapid prototyping – you are doomed to spend ages creating everything ground-up by yourself or wiring up dodgy, no-name components without proper documentation.
A Bluetooth dev kit equipped with the MikroBUS™ socket allows you to instantly expand your project with hundreds of auxiliary hardware components, including Click boards developed by MikroE.
However, if you don't' find what you need from MikroE's portfolio, you have other options such as the Qwiic® Connect System from Sparkfun, which is compatible with a range of boards provided by Sparkfun, as well as Adafruit, and Seeed Studio. Via the Qwiic interface, you can chain up add-on boards over the I2C interface and build up your dev kit with more functionalities (e.g., sensors, LCDs, and other peripherals) as if they were Lego bricks.
The IoT revolution is like one big innovation contest – developers worldwide turn their wildest ideas into products. Only the fastest developers can win, and that's why rapid prototyping has become the most popular market entry strategy in IoT. As a developer, you want to get a head-start in this race and buy the dev kit with the best bang for your buck – such as Silicon Labs Explorer Kit, which provides you all the five power-features, and more, as the only Bluetooth Dev Kit in the $10 price range!
Home security device manufacturers in the UK are required to adhere to a complicated set of British and European standards before their products can hit the market, which typically requires professional installation. A consequence of this relatively high barrier to entry is that most of the available alarm solutions are professional grade and, due to these regulations, must be segregated from other smart home assistance. Scotland-based Boundary is working on bridging this gap with a state-of-the-art alarm system that consumers can install themselves and monitor through their smartphones. We recently sat down with Boundary co-founder, Paul Walton to learn more.
Tell Us About Boundary.
Boundary was founded in 2018 after a successful Kickstarter campaign, producing a smart intruder alarm system for the UK market based on Z-Wave technology. Our co-founder, Robin Knox, had the idea when he was on his honeymoon and realized the limitations of his existing alarm system meant that if his home was broken into, he would be unable to actually do anything other than watch the events unfold on a CCTV camera. Immediately upon his return, he set out to find a reasonably priced self-install security system but had little success. This gap in the market for DIY home security was the catalyst to build something that looked great, was user-friendly, and provided better features at a reasonable price point.
Internally, our company’s goal was to develop a great mobile app that provided a much more intuitive and enjoyable user experience. With a focus on the user journey and hardware design, we are anticipating launching our first product, a smart IoT alarm system, this month. This system consists of four components: the central hub (which is the Z-Wave gateway), a motion sensor, a contact sensor, and an external siren, all of which connect to the central hub advisory.
One thing that sets Boundary apart from our competitors is its EN50131 European Standard for Intruder Alarm Systems compliance certification. Achieving this level of certification requires some pretty tough validation, dropping the hub from two meters and making sure that it's still operational, for instance. The rigorous design detail has made us the first manufacturer of a Z-Wave 700 device that is currently undergoing this certification, which is expected to be completed in the first quarter of next year.
Why Did You Choose Silicon Labs Z-Wave Solutions for Your Products?
When it came to selection criteria, we had many requirements that needed to be met. Some were driven by the standards and some were simply a matter of the target data transmission rates the team wanted to meet. Developing a product that did not require complicated setup and provided the range required to cover a medium-to-large sized house was also important, as was maintaining connection for all devices on the network. Z-Wave emerged as the standard that could meet these challenges. Set-up is incredibly simple, requiring the customer to simply scan a QR code to pair the device.
The result is an alarm that is easy to use and exceeds the highest regulatory standards. Our product features a motion sensor with always-on detection that can be used for home automation routines like powering down smart lighting and regulating heating when a room is not in use. With a door/window sensor, any unauthorized entry will immediately set off the alarm. Users can also see the status of a window or door from the app at any time.
Looking Forward, Where Do You See the Smart Home Security Market Heading?
We believe that within the next five years, we’ll see a bit of a shift in the home security market towards proactive security. For Boundary, our focus is on bringing another product to market, one that utilizes machine vision, and to expand into Europe.
For more information on how Boundary used Silicon Labs Z-Wave solutions to deliver professional-grade security to smart homes, check out our case study and learn more about smart home offerings. If you’d like to leverage the benefits of Z-Wave technology for your smart home applications, we’d love to hear from you.
In the previous Timing 201 article, Timing 201 #7: The Case of the Dueling PLLs – Part 1, I referred to a Silicon Labs white paper that describes Silicon Labs’ DSPLL nested dual-loop architecture as used in the Si538x wireless jitter attenuators. I first discussed the general motivation for a dual-loop PLL and compared the cascaded (series) dual-loop PLL versus the nested dual-loop PLL architectures.
The practical advantages of the nested dual-loop approach in this example were to reduce the number of tuned oscillators from 2 to 1 and to eliminate the need for a sensitive external voltage control line. The tradeoff for a nested feedback control loop is that the inner loop must be faster than the outer loop. If the loop speeds (or bandwidths) are comparable, then the loops will contend or “duel” with each other.
In this Part 2 follow-up post, I will discuss in more detail how to calculate the phase noise of both these dual-loop PLL approaches.
Some Simplifying Assumptions
To emphasize the basic ideas without getting bogged down in too much detail, I will make the following simplifying assumptions:
Series Dual-Loop Phase Noise Calculations
The figure below is from the cited white paper and previous post. The two PLLs are in series with each other.
You will recall that the first PLL, PLL1, is narrowband (NB) and the second PLL, PLL2, is wideband. To calculate the phase noise, we will go left to right through the following steps.
These calculations have been done in the attached spreadsheet Timing_201_7_The_Case_of_the_Dueling_PLLs - Part 2.xlsx. See the “Series Dual-Loop” worksheet. The PLLs are assumed to be 2nd order with the NB PLL BW = 100 Hz and the WB PLL BW = 1 MHz. These parameters can be changed in the spreadsheet, but practically speaking, NB PLLs will be on the order of mHz to kHz. WB PLLs are typically 500 kHz to 2 MHz.
The resulting plot is as follows.
Nested Dual-Loop Phase Noise Calculations
The figure below is also repeated from the cited white paper and previous post. In this case, the two PLLs are nested with respect to each other.
Now the inner loop (IL) PLL is WB and the outer loop (OL) PLL is NB. To calculate the phase noise, we will proceed from the “inside out” through the following steps.
These calculations have also been done in the attached spreadsheet Timing_201_7_The_Case_of_the_Dueling_PLLs - Part 2.xlsx. As before, to keep things “apples to apples”, the PLLs are assumed to be 2nd order with the NB PLL BW = 100 Hz and the WB PLL BW = 1 MHz. See the “Nested Dual-Loop” worksheet. The resulting plot is as follows.
You will note how similar these plots are to each other. Let’s overlay the output phase noise plots together for comparison.
Series versus Nested Dual-Loop Phase Noise Plots
The output phase noise plots are overlaid on top of each other for direct comparison. As shown, they look identical. Further, if you experiment with the bandwidths of each PLL, for each topology, the best output phase noise is generally obtained by making PLL1 (or OL PLL) and PLL2 (or IL PLL) narrowband and wideband respectively. Even apart from stability considerations, both topologies benefit from wide separation between the bandwidths.
Why the Topological Equivalence?
This result is not necessarily to be expected so let’s walk through the steps again and compare the approaches.
LPF_WB (LPF_NB (Input) + HPF_NB (VCXO)) + HPF_WB (VCO)
LPF_WB * LPF_NB (Input) + LPF_WB * HPF_NB (VCXO) + HPF_WB (VCO)
The use of WB and NB notation versus PLL1, PLL2, IL PLL, and OL PLL is to help us make direct comparison between the two sets of calculations. LPF_WB means apply a wideband low pass filter to the phase noise in parenthesis. Two filter terms multiplied indicates applying both filters.
LPF_NB (Input) + HPF_NB (LPF_WB (XO) + HPF_WB (VCO))
LPF_NB (Input) + HPF_NB * LPF_WB (XO) + HPF_NB * HPF_WB (VCO)
LPF_WB * LPF_NB (Input) ≈ LPF_NB (Input)
HPF_NB * HPF_WB (VCO) ≈ HPF_WB (VCO)
In other words, the NB LPF and the WB HPF dominate the calculations for these LPF and HPF terms. This is why these topologies produce equivalent total phase noise when all else is equal.
I hope you have enjoyed this Timing 201 article. In this Part 2 follow-up post, I have discussed in more detail how to calculate the phase noise of both the series and nested dual-loop approaches. Finally, by using a simplified example with widely separated bandwidths, we can see that the approaches are essentially equivalent. There are particular advantages to the nested dual-loop approach which arise from an alternate practical implementation that yields phase noise equivalent to the series dual-loop approach.
As always, if you have topic suggestions or questions appropriate for this blog, please send them to firstname.lastname@example.org with the words Timing 201 in the subject line. I will give them consideration and see if I can fit them in. Thanks for reading. Keep calm and clock on.
RF and microwave frequency synthesizers often employ multiple connected PLLs. These architectures trade off complexity in favor of improved phase noise, smaller frequency step size, and faster switching . In timing applications we may also employ multiple PLLs to combine timing functions and/or shape phase noise.
For example, the white paper, “Optimizing Clock Synthesis in Small Cells and Heterogeneous Networks”, describes Silicon Labs’ DSPLL dual-loop architecture as used in the Si538x wireless jitter attenuators intended for small cell applications . This particular approach is a nested dual-loop as opposed to a cascaded (concatenated) dual-loop. There are definite advantages to this implementation and some important considerations.
One consideration is the necessary bandwidth relationship between the inner and outer loops. This topic leads to the play on words in the main title of this blog post, The Case of the Dueling PLLs. A second consideration is the difference in how one analyzes the phase noise for such an architecture, which arises from the fundamental difference between these two approaches as explained below.
General Motivation for a Dual-Loop PLL Architecture
As you may recall from a previous blog post, there are two basic PLL clock applications :
Low noise references are input to clock generators, which are usually wide bandwidth (e.g., 100s kHz to MHz). By contrast, jittery clocks are input to jitter attenuators, which are usually narrow bandwidth on the order of kHz or less.
But what if your clock application requires both functions? The most straightforward approach is to cascade the two PLLs in series as discussed in the next section.
Cascaded Dual-Loop PLL Architecture
The figure below, taken from the cited white paper, illustrates a single-chip, cascaded dual-loop architecture. (Note that this sense of the term cascade is different from classic control system terminology. Here we mean two PLLs concatenated or in series.)
In this case, the left hand PLL1 with an analog Voltage Controlled Xtal Oscillator (VCXO) is used as a narrow band jitter attenuator stage. The jitter attenuated clock signal is then input to the right hand PLL2, which is used as a wide band clock generator stage. The VCXO need not be very high in frequency but should have good close-in phase noise. This generally means a high Q crystal, which is why this component is typically external to the IC. This necessitates an external control voltage signal to the VCXO.
The on-chip VCO needs to be high enough in frequency so that the divided down clock can yield the necessary output clock frequencies. It also should have low phase noise at high offset frequencies.
This particular example is depicted as all analog with several external filter components and sensitive traces. However, there is no intrinsic reason why a cascaded dual-loop architecture could not be implemented more digitally and with filtering on-chip.
Because the PLLs in the example above are in-series and independent, the total output phase noise can be calculated as a cascade of phase noise processing elements as described in .
Nested Dual-Loop PLL Architecture
The figure below, also from the cited white paper, illustrates a nested dual-loop architecture. In classic control system terminology, this would actually be considered a variation of a cascade control system. For clarity, I will use the term nested here. Think of it as the PLL equivalent of nested Matryoshka dolls.
In this case, the inner loop (IL) PLL is being used as the “VCO” or rather the Digitally Controlled Oscillator (DCO) of the outer loop (OL) PLL. This is the fundamental difference between these two approaches, which will determine how one calculates the total phase noise.
How does this work?
What are the advantages to this approach?
In this particular pair of examples, we reduce the number of tuned oscillators from two (VCXO and VCO) down to one (XO and VCO). This eliminates the need for one of the loop filters (be it internal or external) and a sensitive voltage control line, which must otherwise be routed externally. This decrease in components makes for a more compact solution which reduces the overall PCB footprint.
Could you implement a nested dual-loop with a VCXO?
Yes, in principle. There is no intrinsic reason why you couldn’t implement a nested dual-loop architecture that also uses an external VCXO. Such an approach might even make sense if a particular VCXO has better phase noise performance, perhaps at a higher frequency (update rate). However, you would lose the specific advantages discussed previously. This is why the Si538x wireless jitter attenuators do not support an external VCXO.
What exactly is the Duel?
In these types of nested feedback control loops, the inner loop must be faster than the outer loop. If the loop speeds are comparable, then the loops will contend or “duel” with each other.
In PLL terms the inner loop must have a wider bandwidth than the outer loop. This should make intuitive sense if you consider the relative difference in impact of inserting a really slow “DCO” into an otherwise fast PLL versus inserting a really fast “DCO” into an otherwise slow PLL. The former case significantly impacts the PLL and may even have stability or locking issues due to inserted additional delay. By contrast, the latter case is not impacted significantly. This tells us that the inner loop must be the faster (wider bandwidth) clock multiplier and the outer loop must be the slower (narrow bandwidth) jitter attenuator. Further, it tells us that at start-up and during the lock process, we want the inner loop PLL to stabilize and lock before the outer loop.
Another way of thinking about this is to recall that PLLs function as a low pass filter for phase noise arising from any source in the loop, except when they function as a high pass filter to VCO phase noise. For the OL PLL to modulate the IL’s return path without attenuation, the signal must be well within the IL BW.
Incidentally, if you want to estimate one quantity from another, such as frequency step rise time from PLL bandwidth, you may use this relationship:
Tr [10%-90%] * BW [3dB] ≈ 0.35
See for example, Howard Johnson’s discussion in the article, PLL Response Time . Per his article, the time bandwidth product varies from 0.35 to 0.38, depending on whether the PLL behaves closer to a single-pole or double-pole response.
How much faster or wider bandwidth must the inner loop be? In mechanical engineering and process control systems, the differences in nested loop speeds can be relatively small. A mechanical IL may be 5x to 10x faster than a mechanical OL. See for example Danielle Collins’ servo loop article in . However, in timing applications, the difference in bandwidths is typically much greater. Nested dual-loop IL BWs are typically on the order of MHz, whereas OL BWs can be on the order of 10 Hz to 1 kHz, so the ratio is closer to the IL being 1000x to 100,000x faster than the OL.
Note that for Si538x devices, the IL BW is wide (~ 1 MHz), fixed, and optimized. Because it is so wide, there is no jitter attenuation at the device’s XO inputs, i.e., the XA/XB pins. Therefore, we should be careful that noise and interference does not couple into the device via the XO circuit at these pins. This is why we recommend low phase noise XOs to be placed as close as possible to the device so as to minimize PCB trace lengths.
Can this idea be extended?
Yes, in principle. The servo control loop article cited earlier discusses a servo motor control with three nested loops, inside to outside as follows: current feedback, velocity feedback, and position feedback. Similarly, you can “triple nest loop” clock PLLs to shape the phase noise to track select input clocks with different phase noise characteristics over different frequency offsets. However, this particular approach is not utilized by the Si538x devices.
I hope you have enjoyed this Timing 201 article. In the Part 2 follow-up post, I will discuss in more detail how to calculate the phase noise of the nested dual-loop approach using a simplified example.
As always, if you have topic suggestions or questions appropriate for this blog, please send them to email@example.com with the words Timing 201 in the subject line. I will give them consideration and see if I can fit them in. Thanks for reading. Keep calm and clock on.
 W. F. Egan, Advanced Frequency Synthesis by Phase Lock. Wiley, 2011. See for example section 7.1 regarding the Two-Loop Synthesizer where two loops interact via a mixer.
 Optimizing Clock Synthesis in Small Cells and Heterogeneous Networks
 Timing 101 #11: The Case of the Noisy Source Clock Tree Part 1
 Timing 101 #12: The Case of the Noisy Source Clock Tree Part 2
 H. Johnson, PLL Response Time, High-Speed Digital Design Online Newsletter: Vol. 15 Issue 04,
 D. Collins, Why is the bandwidth of a servo control loop important?, April 20, 2017, https://www.motioncontroltips.com/why-is-the-bandwidth-of-a-servo-control-loop-important/
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Features at a Glance:
There are many challenges facing embedded development engineers tasked with implementing effective security measures. Knowledge of what is being protected, the threat landscape, and specific attack vectors to be protected against is necessary. Not to mention the added urgency that comes with overreported, high-profile breaches.
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