industry news
Subscribe Now

STMicroelectronics Introduces Bluetooth® 5.2-Certified SoC, Extending Range, Throughput, Reliability and Security

Geneva, October 7, 2020 – STMicroelectronics has revealed its latest BlueNRG-LP Bluetooth® LE System-on-Chip (SoC), which leverages the latest Bluetooth features to increase communication range, raise throughput, strengthen security, and save power. The ultra-low-power radio is optimized to consume as little as 3.4mA in receive mode, just 4.3mA when transmitting, and less than 500nA quietly waiting for wake-up events, cutting by half the size of battery needed in most applications and prolonging runtime.

BlueNRG-LP, the 3rd-generation Bluetooth SoC from ST, is the world’s first Bluetooth LE 5.2-certified SoC to support concurrent connections up to 128 nodes, enabling seamless low-latency control and monitoring large numbers of connected devices, for instance from a stylish and intuitive smartphone app.

Combined with high RF-output power, which is programmable up to +8dBm, and excellent RF sensitivity up to -104dBm, the BlueNRG-LP radio SoC can now natively cover a much larger area in beacons, smart lighting, gaming, building automation, industrial and tracking applications. Furthermore, the communication range can be extended without limit by seamlessly adding Bluetooth LE Mesh, now fully certified and available as part of the comprehensive BlueNRG software and hardware ecosystem.

In addition, BlueNRG-LP supports Bluetooth Long Range mode, which uses coded physical layers (Coded PHY) with Forward Error Connection (FEC) to extend radio-communication range up to hundreds of meters and increase reliability, as well as GATT (generic attribute) caching to connect quickly and efficiently.

BlueNRG-LP comes with ST’s third-generation Bluetooth Low Energy protocol stack certified to Core Specification 5.2 and designed to match its ultra-low-power architecture. The stack is provided as a free-of-charge and compiler-independent linkable library supported by multiple Integrated Development Environments (IDEs) and is optimized for small footprint, modularity, low latency, interoperability, and lifetime over-the-air upgradability. It supports features such as extended advertising and scanning, high-duty-cycle non-connectable advertising, extended packet length, and 2Mbit/s throughput.

In addition BlueNRG-LP supports L2CAP Connection-Oriented Channel (CoC), which eases large bidirectional data transfers, multi-role simultaneous connectivity, and Channel Selection Algorithm #2 (CSA #2), which permits robust connections in noisy environments such as home, building, or industrial networks.

Enhanced security mechanisms included in the integrated Arm® Cortex®-M0+ microcontroller (MCU) comprise a secure bootloader, readout protection for the entire 256KB embedded flash, a 48-bit unique ID, as well as customer key storage, true Random-Number Generator (RNG), hardware public-key accelerator (PKA), and a 128-bit AES cryptographic co-processor. The highly efficient processing unit executes code at up to 64MHz, consuming an amazingly tiny 18µA/MHz, and features industry-standard digital interfaces, multi-channel 12-bit ADC, an analog microphone interface with programmable gain amplifier, user and system timers and watchdog, and up to 31 5V-tolerant user-programmable I/O pins.

The BlueNRG-LP SoC also integrates an embedded RF balun, DC/DC converter, and capacitors for the HSE (High-Speed External) oscillator and internal low-speed ring oscillator, minimizing bill-of-materials (BOM) costs and simplifying circuit design.

BlueNRG-LP is available in a choice of 5mm x 5mm QFN32, 6mm x 6mm QFN48, and a miniature 3.14mm x 3.14mm WLCSP49 wafer-level package. With 32KB or 64KB RAM and a choice of temperature range up to 85°C or 105°C, designers get extra flexibility to choose a configuration that best meets their needs. The devices are covered by ST’s 10-year industrial longevity commitment, assuring users of long-term parts availability.

BlueNRG-LP SoCs are in production now, in QFN48, priced from below $1.00 for volume orders.

Please visit www.st.com/bluenrg-lp-pr for more information.

You can also read our blogpost at https://blog.st.com/bluenrg-lp/

Leave a Reply

featured blogs
Oct 21, 2020
We'€™re concluding the Online Training Deep Dive blog series, which has been taking the top 15 Online Training courses among students and professors and breaking them down into their different... [[ Click on the title to access the full blog on the Cadence Community site. ...
Oct 20, 2020
In 2020, mobile traffic has skyrocketed everywhere as our planet battles a pandemic. Samtec.com saw nearly double the mobile traffic in the first two quarters than it normally sees. While these levels have dropped off from their peaks in the spring, they have not returned to ...
Oct 19, 2020
Have you ever wondered if there may another world hidden behind the facade of the one we know and love? If so, would you like to go there for a visit?...
Oct 16, 2020
[From the last episode: We put together many of the ideas we'€™ve been describing to show the basics of how in-memory compute works.] I'€™m going to take a sec for some commentary before we continue with the last few steps of in-memory compute. The whole point of this web...

featured video

Demo: Inuitive NU4000 SoC with ARC EV Processor Running SLAM and CNN

Sponsored by Synopsys

Autonomous vehicles, robotics, augmented and virtual reality all require simultaneous localization and mapping (SLAM) to build a map of the surroundings. Combining SLAM with a neural network engine adds intelligence, allowing the system to identify objects and make decisions. In this demo, Synopsys ARC EV processor’s vision engine (VPU) accelerates KudanSLAM algorithms by up to 40% while running object detection on its CNN engine.

Click here for more information about DesignWare ARC EV Processors for Embedded Vision

featured paper

Designing highly efficient, powerful and fast EV charging stations

Sponsored by Texas Instruments

Scaling the necessary power for fast EV charging stations can be challenging. One solution is to use modular power converters stacked in parallel. Learn more in our technical article.

Click here to download the technical article

Featured Chalk Talk

Addressing Digital Implementation Challenges with Innovative Machine Learning Techniques

Sponsored by Cadence Design Systems

Machine learning is revolutionizing our designs these days with impressive new capabilities. But, have you considered using machine learning to actually create better designs? In this episode of Chalk Talk, Amelia Dalton chats with Rod Metcalf of Cadence Design Systems about how Cadence is using machine learning to help us get more out of our design tools - optimizing a wide range of design automation processes go give us better results in less time.

Click here for more information about Innovus Implementation System