The idea behind the article is to introduce people to SDR from a shortwave listening point of view, so high performance HF SDRs like the Airspy HF+, Elad FDM-S2 and WinRadio Excalibur are discussed. Thomas notes that these SDRs can perform as well as traditional DX-grade receivers that can cost two to three times more. He also explains what advantages SDR's bring to the shortwave radio listening hobby. This may be a good article to show those still using older hardware radios that haven't yet converted to the SDR world.
The article is currently part one of a three part series, with parts two and three to be released in October and November.
Helium is a cryptocurrency being designed for internet of things (IoT) sensors which will be based on low cost software defined radio (SDR) technology - that's a lot of buzzwords!. The idea is to design a system that will pay people to run an internet connected gateway which will receive data from wireless sensors, and put that data onto the internet. A use case that Helium has already developed is providing services to track and monitor medicine and food supplies. The linked article gives a good example of this use case:
...let’s say you have a gateway in your house: if a vial of medicine were to enter your coverage zone, it would send its location and temperature data to your gateway, which would then send it to its proper destination in return for a previously agreed upon cryptocurrency fee. These steps would then be cryptographically verified and recorded in the distributed ledger.
In terms of IoT network competition, LoraWan and SigFox IoT networks are already popular and established in several places in the world, but wireless coverage isn't great because these networks rely on companies to build gateway infrastructure. Helium crowd sources this infrastructure instead, which could result in greater coverage.
Most cryptocurrencies base the security of their network on the 'proof of work' process, which is a way to ensure that the miners get rewarded for the heavy cryptographic computations that they do in order to secure the network. Instead of proof of work, Heliums idea is to use a 'proof of coverage' system, where other gateways will confirm if a gateway is providing coverage and is in the correct location. Helium cryptocurrency 'miners' will be the people running the internet connected gateways, and they will be paid for any devices that use their wireless coverage.
According to one of their latest blog posts, the wireless gateway radio system is to be based on a software defined radio architecture. The reasoning behind using SDR is that they need to support potentially thousands of wireless sensor channels, require the sensors to be able to be geolocated, and require the radio to be low cost and energy efficient. For geolocation of sensors they are considering the use of radio direction finding techniques that we assume will be based on pseudo-doppler, or alternatively they will use the time difference of arrival (TDoA) technique which requires the signal to be received by multiple gateways. The SDR will be developed on a dual core TI SoC, with four programmable realtime units (PRU), which they'll use to interface with the RF chips.
At the moment Helium is just a whitepaper, and we haven't seen any concrete evidence of a working SDR design yet, but according to their website they plan to launch gateway hardware in Q4 2018 for a cost of $495.
The New England Workshop on Software Defined Radio (NEWSDR) was held in May this year, and there have been several talks now uploaded to YouTube. These are typically fairly technical in nature, and discuss cutting edge research being performed with software defined radios. Below we post a few selected talks, and the rest can be viewed in this WPI playlist.
Remote Sensing of the Space Environment Using Software Defined Radio
From studies of the ionosphere to astronomical measurements with arrays of radio telescopes the manipulation and analysis of RF signals has been key to new instrumentation and many resulting discoveries. Software radio technology has been a core component of remote sensing of the space environment for several decades now. The flexibility of combining computing and radio was adopted very early on in scientific applications. This enabled new classes of scientific experiments which would otherwise have been impossible. The capability and adaptability of software radio instrumentation and systems has been growing consistently with the exponential increase in available computing power. The recent surge of low cost software radio hardware technology has enabled a new generation of instrumentation. These instruments are increasingly blurring the line between traditionally separate scientific disciplines as well as practical applications. I will discuss the science and the instrumentation enabled by software radio with highlights from studies of the ionosphere and radio astronomy. My overview will focus on the relationship to work underway at MIT Haystack Observatory. I will highlight the core architectural patterns of scientific software radio and discuss the evolution of our systems over several decades of rapid technological change. I will also look forward to the possibilities for discovery offered by the next generation of software radio and radar instrumentation.
NEWSDR 2018: Invited Presentation by Frank Lind (MIT Haystack)
Reinventing Wireless with Deep Learning
While wireless communications technology has advanced considerably since its invention in the 1890s, the fundamental design methodology has remained unchanged throughout its history – expert engineers hand-designing radio systems for specific applications. Deep learning enables a new, radically different approach, where systems are learned from wireless channel data. This talk will provide a high-level overview of deep learning applied to wireless communications, discuss the current state of the technology and research, and present a vision for the future of wireless engineering using a data-centric approach.
NEWSDR 2018: Invited Presentation by Nathan West (DeepSig)
Multi-objective SDR Optimization for Wireless Access, Actuation and Attacks
Software defined radios (SDRs) have become the foundational block of agile wireless communications. The first part of the talk presents an overview of how the same SDR can alternate between multiple different and non-traditional actuation functions, such as aerial distributed beamforming and wireless energy transfer. Furthermore, as SDR technology becomes more pervasive assuming roles beyond communication, there is a growing risk of security concerns of ID spoofing and malicious hardware attacks. The second part of this talk describes our efforts of fingerprinting individual SDRs using machine learning, where we only analyze the I/Q samples collected at the receiver. We demonstrate the feasibility of achieving 90-95% classification accuracy through experiments conducted with 12 radios, at separation distances of beyond 50 feet. The talk concludes with a summary of the challenges ahead and identifies other emerging application areas of SDRs that will impact the next decade.
NEWSDR 2018: Invited Presentation by Kaushik Chowdhury (Northeastern University)
As expected, the AIR-T is not a cheap with it coming in at US$5,699, and this is with a 10% discount off the MSRP. However, the AIR-T is likely to be more of interest to high end industry and university researchers who have research money to spend. Also, compared to Ettus E310/N310 and LimeNET Mini SDRs which have built in non-GPU based computing platforms and similar SDR performance, the AIR-T could be seen as reasonably priced assuming that the software and drivers for it are decent. In the future we expect to see the price of similar SDR-AI development boards eventually reduce down to hobbyist level prices.
The basic idea behind the AIR-T is to combine a 2x2 MIMO SDR transceiver with a NVIDIA Jetson TX2 GPU that can be used to run artificial intelligence (AI) software fast. They will include software that will allow GNU Radio and Python code to be easily ported to the GPU architecture.
Why build tomorrow’s tech with yesterday’s signal processing tools? The Artificial Intelligence Radio - Transceiver (AIR-T) is a fully integrated, single-board, artificial intelligence equipped, software defined radio platform with continuous frequency coverage from 300 MHz to 6 GHz. Designed for new engineers with little wireless experience to advanced engineers and researchers who develop low-cost AI, deep learning, and high-performance wireless systems, AIR-T combines the AD9371 RFIC transceiver providing up to 2 x 2 MIMO of 100 MHz of receiving bandwidth, 100 MHz of transmitting bandwidth in an open and reprogrammable Xilinx 7 FPGA, with fast USB 3.0 connectivity.
The AIR-T has custom and open Ubuntu software and custom FPGA blocks interfacing with GNU Radio, allowing you to immediately begin developing without having to make changes to existing code. With 256 NVIDIA cores, you can develop and deploy your AI application on hardware without having to code CUDA or VHDL. Freed from the limited compute power of a single CPU, with AIR-T, you can get right to work pushing your telecom, defense, or wireless systems to the limit of what’s possible.
The SDR transceiver chip used is a Analog Devices 9371. This is a high end chip that can be found on high end SDR hardware like USRPs. If you're interested we had a post about decapping the AD9361 recently, which is a similar chip. It provides 2x2 MIMO channels, with up to 100 MHz RX bandwidth and 250 MHz TX bandwidth. The NVDIA Jetson TX2 is a GPU 'supercomputer' module specifically designed for AI processing. Many AI/machine learning algorithms, such as neural networks and deep learning run significantly faster on GPU type processors when compared to more general CPU's.
These are not cheap chips with the AD9371 coming in at over US$250 each, and the Jetson TX2 coming in at US $467. Although we don't know what sort of bulk discounts the AIR-T manufactures could get. But it will be certain that the AIR-T will not be for the budget minded.
The board is still awaiting release of it's crowdfunding round, and you can sign up to be notified of when the project launches on their Crowd Supply page.
The melding of AI and the RF spectrum will be common in the future, and a development board like this is one of the first steps. Some of the interesting use cases that they present are pasted below:
From Wi-Fi to OpenBTS, use deep learning to maximize these applications. By pairing a GPU directly with an RF front-end it eliminates the need of having to purchase an additional computer or server for processing. Just power the AIR-T on and plug in a keyboard, mouse, and monitor and get started. Use GNURadio blocks to quickly develop and deploy your current or new wireless system. For those who need more control, talk directly with the drivers using Python or C+. And for those superusers out there, the AIR-T is an open-platform, so you can program the FPGA and GPU directly.
Communicating past Pluto is hard. With the power of a single-board SDR with an embedded GPU, the AIR-T can certainly prove out concepts before you launch them into space. Reduce development time and costs by adding deep learning to your satellite communication system.
There is an endless number of terrestrial communication systems with more being developed every day. As the spectral density becomes more congested, AI will be needed to maximize these resources. The AIR-T is well-positioned to easily and quickly help you prototype and deploy your wireless system.
The AIR-T allows you to demodulate a signal and apply deep learning to the image, video, or audio data in one integrated platform. For example, directly receiving a signal that contains audio and peforming speech recognition previously required multiple devices. The AIR-T integrates this into one easy to use package. Whatever your application is, from speech recognition to digital signal processing, the integrated NVIDIA GPU will jump start your applications.
For many communications and radar applications once the signal is collected it must be sent to an off-board computer for additional processing and storage. This consumes valuable time. The AIR-T eliminates this. From its inception, it was designed to process signals in real-time and eliminate unnecessary latency.
Several new software defined radio talks have been released on YouTube this week from the big European 2018 Friedrichshafen Ham Radio Convention which just finished this month. The full list of 14 new videos can be found on the Software Defined Radio Academy YouTube channel. Below are two of our favorites:
The OVI40 / UHSDR Project, Developing An Open Standalone SDR
OVI40 is an Open Source standalone homewbrew SDR TRX project (VLF to 2m), developed with the aim of being modular and future-proof. The talk describes the hardware and the UHSDR software including a discussion on the evolution from the "single-system" software used for the well-known mcHF (initially written by Chris, M0NKA and Clint KA7OEI) to the multi-SDR approach in the UHSDR software project.
DF8OE, DB4PLE, DL2FW, DD4WH: The OVI40 / UHSDR Project - Part 1 and 2
András Retzler, HA7ILM: Let's code a simple receiver in C
For using SDR in amateur radio applications, it is easier to use existing receiver software, or create GNU Radio flowgraphs with pre-build blocks. On the contrary, in the do-it-yourself spirit of amateur radio, this talk will guide you through the steps of implementing a simple AM/FM/SSB receiver from scratch, in plan old C, in order to get a deeper understanding of what happens actually under the hood in popular SDR software. The talk builds on the author's learning experience of creating the open source CSDR command line tool, which is used for DSP in the OpneWebRX web based SDR receiver.
András Retzler, HA7ILM: Let's code a simple receiver in C
Analog Devices has recently released a new text book for free called "Software-Defined Radio for Engineers, 2018". This is an advanced university level text book that covers communication systems theory as well as software defined radio theory and practice. The book uses the PlutoSDR as reference hardware and for practical examples. The PlutoSDR is Analog Devices $150 RX/TX capable SDR that was released about a year ago.
The objective of this book is to provide a hands-on learning experience using Software Defined Radio for engineering students and industry practitioners who are interested in mastering the design, implementation, and experimentation of communication systems. This book provides a fresh perspective on understanding and creating new communication systems from scratch. Communication system engineers need to understand the impact of the hardware on the performance of the communication algorithms being used and how well the overall system operates in terms of successfully recovering the intercepted signal.
This book is written for both industry practitioners who are seeking to enhance their skill set by learning about the design and implementation of communication systems using SDR technology, as well as both undergraduate and graduate students who would like to learn about and master communication systems technology in order to become the next generation of industry practitioners and academic researchers. The book contains theoretical explanations about the various elements forming a communication system, practical hands-on examples and lessons that help synthesize these concepts, and a wealth of important facts and details to take into consideration when building a real-world communication system.
The companion site for the book which contains links to complimentary online lectures, slides, and example MATLAB code can be found at https://sdrforengineers.github.io. MATLAB is a very powerful programming language and toolset used by scientists and engineers. MATLAB is not a cheap tool, but there is a home user licence available for a more reasonable price. To do some of the exercises in the book you'll probably at least require the core MATLAB plus the Communications System Toolkit which is an extra add on.
Over on his blog Ajoo has posted a very comprehensive introduction to the technical concepts behind RTL-SDR, as well as any other SDR in existence. His post first goes through the basic communications theory and mathematical concepts required to understand the technical concepts behind software defined radio. He then goes on to specifically discuss the RTL-SDR and how it works internally, mentioning what the major components do and providing useful block diagrams.
In part II of his introduction he moves on to the software. Here he starts to explain a bit about librtlsdr and how the RTL-SDR drivers and codebase is put together. Further on he explains higher level software such as rtl_test, rtl_fm, rtl_sdr, the pyrtlsdr wrapper and how it could be used to demodulate FM.
If you're looking at diving deeper into SDR theory then Ajoo's posts are excellent starting points. Note that the theory explanations come at about an undergraduate University level of complexity, and thus these posts are mostly for people wanting a deeper understanding of SDR. To simply use an RTL-SDR to receive signals such a deep level of understanding is not required.
In a future post which is not yet available, Ajoo will introduce GNU Radio and show how to demodulate FM signals. It appears his goal is to work his way to an understanding of how GPS L1 signals work.