The radio spectrum available is a limited resource and the number of gadgets with high data rates cannot be accommodated in the present static spectrum. The spectrum sensing is the base line on which the whole process of cognitive radio works. To avoid the interference with the licensed users and determining the accessible spectrum for increasing the spectrum's usage is the pivotal task of cognitive radio. Cognitive radio evolved to be an effective method to overcome this limitation by dynamically accessing the data. In this paper, a technique responsible for sensing the spectrum and then transmitting on that spectrum is proposed. FHSS- ED (Frequency Hopping Spread Spectrum- energy Detection) is the approach evaluated. It has two stages; firstly sensing is done using Energy Detection Technique and Transmission is done by hopping on available channels deduced from sensing stage by using FHSS technique. Comparision of the proposed technique FHSS-ED is made with the existing FHSS-OBRMB technique and simulation results prove that proposed technique has better results than the exiting. Analysis has also been made on the basis of noise uncertainty conditions.
Software defined radios possess a necessary component: the RF frontend. The RF frontend, however, has the unfortunate reputation of being the source of most of the spurious responses seen in an SDR. Fortunately, managing these spurious responses can be explained with a few simple equations and examples. Direct conversion frontends presently dominate the SDR devices. As SDR applications move into higher frequencies and data converter sample rates increase, super-heterodyne architectures and low-IF architectures will begin to be more prevalent in SDRs. Each architecture has its pros and cons regarding spurious responses. This presentation introduces the theory behind these various RF frontend architectures with an emphasis on the sources of spurious responses. Knowing how spurious responses are generated can help determine the best means to minimize these effects.
At Infostellar, we are building a worldwide ground station network to allow satellite operators to communicate with their respective satellites around the world. As each satellite uses different methods for communication, we use GNU Radio flowgraphs to quickly switch between the different communication protocols our users require. With multiple satellites passing over our ground stations daily, every ground station must dynamically run multiple GNU Radio flowgraphs everyday. To keep our ground station business logic separate from the management of GNU Radio flowgraphs, we built an open-source project called Starcoder. Starcoder is a lightweight gRPC server that allows clients to start and stop multiple GNU Radio flowgraphs at will. It also provides direct hooks into these flowgraphs to allow clients to receive and send messages from or to the various blocks inside, through the same gRPC connection. To support this, Starcoder provides a direct mapping from GNU Radio Polymorphic Types (PMTs) to Google's language-neutral and platform-neutral protocol buffer format. This lets us run GNU Radio flowgraphs and send/receive PMTs from any programming language gRPC supports. In our ground station software written in Go, we have successfully used this functionality to receive data packets from satellites, send transmission commands, correct for Doppler shift, and more. The talk will include the motivations behind Starcoder, Infostellar's experience using it in production, a roadmap for future work, and some code examples from different programming languages for a quick demonstration of Starcoder's capabilities.
This talk is intended to present a real-time adaptation scheme for video encoding and channel selection that work in tandem to facilitate HD video streaming for secondary users in a dynamic spectrum access network. Out-of-band feedbacks on instantaneous pathloss of the signal between the transmitter and the receiver, the received signal strength indicator (RSSI) at the receiver, and the quality of the reconstructed video, are used to continuously determine the most apt encoding parameters. Similarly, the radio transmitter continuously adjusts the channel parameters (i.e., center frequency, and channel bandwidth) based on the transmission activities of the primary users who have prioritized rights on those channels. We considered the physical limitations of the encoder and the channel statistics to determine when to change the encoder parameters and when to switch to a new channel. We proposed a multi-level threshold based mechanism to find the optimal number of encoding bit rates. We also proposed a threshold based algorithm to find the best available channel between the transmitter-receiver pair. We validated our theoretical propositions on an indoor testbed using universal software radio peripherals (USRPs) and GNU Radio. Live video was captured, encoded using open source H.264 software libraries, streamed using GStreamer, and transmitted over the 915 MHz ISM bands with omni-directional antennas. We used two B210s (by Ettus Research) for the transmitter and the receiver. Another B210 was programmed to sense the energy levels on all the channels to detect the presence of primary transmissions. GNU Radio was used to build the initial flowchart of all the signal processing modules--both at the transmitter and the receiver. We used PSNR and SSIM to measure the video quality metrics. Experimental results show that (i) the video encoder and the USRP transmitter-receiver pair were able to adapt to the changing RF conditions, (ii) the adaptation schemes yielded better video quality than non-adaptive schemes, and (iii) the USRPs could switch the channels fast enough allowing uninterrupted HD video streaming even when the primary users preempted the secondary user's transmission.
GNU Radio's documentation is in the process of getting a significant reorganization to improve the experience for both newcomers and experts alike. This talk covers the current state and future plans for the user manual and wiki based documentation. As the documentation must serve the needs of a wide variety of users, Marc will be polling the audience about specific features and use cases. There will also be a report about the updated Comprehensive GNU Radio Archive Network (CGRAN) website, a free open source repository for 3rd party GNU Radio applications which is maintained by the GNU Radio project. The talk will be complemented by a working group session on Friday.
Explain and encourage participation in the DVB-S2 DVB-S2X Block Party at GNU Radio Conference 2018. This Block Party will design, document, build, and test blocks that enable and improve DVB-S2/X receiver design in GNU Radio.
This presentation describes how the CASPER system uses GNU Radio and USRP hardware to detect unintended processor emissions in order to determine if there is anomalous activity occurring on a device being monitored. This approach provides a layer of security physically removed from target hardware, which does not require monitoring code running on the device itself.
Utilizing commercial SDRs and GNU Radio, RF signal features are extracted and used to classify the program states running on the target processor. By understanding the causes and the propagation of these unintended emanations, we show that RF emanations are present across the spectrum, but there are bands that lead to higher SNR features depending on the environment. We find these suitable bands empirically using an automated band scan, which employs multiple metrics to assess expected feature content including received power, kurtosis, and mode clustering. We have also developed multi-antenna processing algorithms to further extend range and increase the SNR of the extracted RF features by mitigating the interference encountered in realistic training and monitoring environments.
Of particular interest among targets are IoT devices, many of which are severely lacking in security controls, making them susceptible to a variety of threats. Due to the nature of these devices, and not having the ability to modify the source code, we rely on unsupervised machine learning methods based on clustering for both training and monitoring to identify known and unknown program states. Additionally, the system includes a framework for anomaly detection engines based on n-grams, statistical frequency, and control flow, to alert the system when the expected program execution has deviated in a newly detected way.
CASPER is an ongoing research project funded under the DARPA Leveraging the Analog Domain for Security (LADS) program. The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.
In this talk we propose three GNU Radio blocks for performing spectrum sensing based on the autocorrelation of samples captured with an SDR device such as HackRF One, RTL-SDR or USRP. The proposed blocks analyze the autocorrelation of samples through different methods to determine if they come from either noise or signals transmitted by communication devices. The reason for using the autocorrelation is that this feature is different for noise and for communication signals regardless of the noise power, which is an advantage in comparison with energy detection, another common method for spectrum sensing, which requires knowledge of the noise level to determine the presence or absence of communication signals. The first method consists in calculating the Euclidean distance between the autocorrelation and a reference line defined by the maximum values taken by the autocorrelation with high signal to noise ratio samples. To perform spectrum sensing with this method the proposed block takes the samples, calculates the autocorrelation and its distance to the reference line; if the distance is above certain threshold the block decides that the samples are signal, otherwise that the samples are noise. The second method consists in clustering the points defined by the variance and the mean of the autocorrelation samples. For implementing this method we identify one cluster containing samples with only noise, and other clusters containing samples from different communication signals. To put into practice this method, the block takes samples and estimates to which cluster they belong. The third method is based on the percentiles (25%, 50%, 75%) of the autocorrelation fast Fourier transform, better known as the power spectral density (PSD). For this method, we calculate the percentiles of the PSD of noise and communication signals at different frequencies and labeled them accordingly. We use the percentiles and their corresponding labels to train a KNN (K- nearest neighbor) classifier and create a classification model. To apply this method the proposed block takes the received samples, calculates the percentiles of their PSD and feeds them to the KNN model, which decides whether the samples come from either noise or communication signals. We implemented and tested experimentally the aforementioned methods with GNU radio companion, HackRF one, and RTL-SDR 2832u. In the talk we will present details about the proposed methods, their performance evaluation and the experiments conducted during the process.
Traditional physical layer protocols (e.g. WiFi, WiMax, etc.) are well established and are often optimal in a wide variety of channel conditions. Unfortunately, this same optimality encourages the potential for catastrophic cyber or physical attacks due to prolific knowledge of underlying physical layers. Any truly resilient communications protocol must be capable of immediate redeployment after such an event. Through software-defined radios, and deep modulation, system blocks are replaced with machine learning graphs that can be trained, used, and then discarded as needed. Simulation and experimental hardware show how deep modulation can converge to viable communications links, using the same machine intelligence, in vastly different channels.
Open Source Radio Telescopes (OSRT) is a new education program which aims to inspire students of all ages to pursue STEM careers by providing them hands-on opportunities to construct and observe with simple radio telescopes. OSRT makes open source software, instructions, and curricula available online at www.opensourceradiotelescopes.org, and is in the process of developing kits of radio telescope construction supplies to distribute to classrooms for students ranging from middle-school to undergraduate-level. OSRT has developed two simple projects to date: the small loop antenna, which can detect solar flares by monitoring changes in the signal strength of VLF submarine transmission signals, and the horn antenna, which can detect and map the neutral hydrogen (HI) gas distributed throughout the Milky Way. Both of these projects make use of GNU Radio for their digital signal processing pipelines. The straightforward and visual nature of GRC flowgraphs makes GNU Radio an ideal teaching tool to show students how signal processing and computer science works, and therefore it is a vital tool for helping OSRT achieve its goal of showing students that technical topics - like engineering, programming, physical science, and mathematics - are accessible to them, therefore opening doors for students to find their passions and pursue a future in these rewarding and lucrative fields.
Hawkeye 360 is launching a cluster of three small satellites to perform high-precision geolocation of RF emitters. In this talk, we'll discuss the architecture and use-cases of RFNoC and GNU Radio on a custom small-satellite payload with three AD9361 frontends and one Zynq 7045. Software signal processing applications are developed for the payload using GNU Radio; FPGA development uses RFNoC. In the end state, Hawkeye 360's software-defined radio has the capability to arbitrarily and asynchronously enable/disable software applications attached to different frontends, swapping in FPGA blocks as required by application. The ground-to-spacecraft data link is implemented using an FPGA-based OQPSK modem and Reed Solomon codec that were developed and tested first in software, second on COTS hardware, then finally ported seamlessly to our custom payload - We'll discuss the full life cycle of creating this OQPSK modem implementation in FPGA. Additional RFNoC applications are commonly used on the payload to perform high data-rate correlation, signal detection, and spectrum survey, with an emphasis on using the FPGA to intelligently downsample higher bandwidths than the Zynq's ARM can typically process in software (> 2 MHz or so). A raw collection application allows the Zynq to burst up to one second of contiguous 40 MHz sample-rate data to processor RAM before writing to disk. We look forward to our literal product launch when we will begin using the software in an orbital deployed environment.
The open-source FPGA-based polyphase channelizer presented in the 2017 GNU Radio conference is a great start , but is missing a few critical features to be truly useful in an embedded system: 1) an FPGA channelizer needs to be able to downselect output channels, such that the processor is not required to absorb the full bandwidth of the frontend; this enables narrowband channel selection out of a wideband signal capture. 2) baseband sample timestamp alignment for arbitrary channels needs to be calculated and aligned correctly so the timestamps are valid and accurate.
This talk addresses both concerns in detail and presents Hawkeye 360's solution. A demo application shows on-the-fly channel selection within the maritime VHF band with minimal processor usage on an embedded Zynq-based platform (Ettus E310). The FPGA and software improvements will be open-sourced to help improve the world of FPGA polyphase channelizers.
The ability to incorporate RF Ranging measurements with Internet-of-Things (IoT) devices supports device tracking in a variety of environments. Inexpensive Sub-1GHz IoT RF modules are readily available but normally don't incorporate the necessary measurements for RF ranging. We explore utilizing low cost LoRa IoT RF modules as low SWAP-C RF Ranging sensors in a RF ranging Positioning, Navigation, and Timing (PNT) architecture even when the necessary measurements for high-precision RF ranging measurements are not available from the LoRa IoT module. To facilitate this research we have developed a hybrid (active/passive) RF ranging COTS Software Defined Radio (SDR) architecture that eliminates the need to acquire physical layer RF measurements in the IoT module. We present a prototype low SWAP-C hybrid RF ranging architecture based on a PNT Sub-1Ghz SDR (PUGS). The PUGS hybrid architecture accommodates low SWAP-C swappable components using IoT RF modules for RF aided complementary PNT while using GNU Radio as the underlying processing architecture.
The PUGS hybrid architecture decouples the strict timing requirements normally associated with typical RF ranging architectures enabling a low SWAP-C solution for exploring high-precision RF ranging IoT PNT demonstrations with GNU Radio. Several features of the initial PUGS prototype include 1) a built-in Multi-Global Navigation Satellite Systems (GNSS) receiver capability, 2) Python based RF ranging protocols, 3) I/Q data capture capability to explore high-precision narrowband RF ranging algorithms with GNU Radio, and 4) an accelerometer to support waking up on motion events. Components of the PUGS architecture as well as RF ranging measurements are discussed based on inexpensive LoRa transceivers and RTL-SDRs utilizing GNU Radio. It is shown that the PUGS architecture allows the exploration of high-precision RF ranging algorithms on inexpensive LoRa transceivers without needing the physical layer RF measurements generated by the transceiver. We demonstrate the ability to leverage inexpensive IoT RF modules as RF ranging sensors for supporting a complementary PNT architecture leveraging GNU Radio.
Various forms of communication have evolved over the millennia. The spoken word can be transmitted from one person, and heard or received by another. In modern times town criers hold an annual contest to discover who can shout a comprehensible message over the greatest distance . However, while the world record is for loudest crier is 112.8 decibels, it can only be understood at less than
100 meters. The desire to communicate more effectively than shouting, is old as speech itself.
In RF, when you want to transmit at a longer distance - the answer is easier - get an amplifier. However, for the non-analog developers, many amplifier specifications are gibberish. In this talk, we will look at a variety of amplifier specifications like P1dB, Noise Figure, IMD, S Parameters, and relate this to a practical digital communications examples, and show real world results, which may not be obvious to the causal user.
 http://www.americantowncriers.com/ (yeah, its a thing)
SirenJack is a vulnerability that was found to affect radio-controlled emergency warning siren systems from ATI Systems. It allows a bad actor, with a $30 handheld radio and a laptop, to set off all sirens in a deployment. Hackers can trigger false alarms at will because the custom digital radio protocol does not implement encryption in vulnerable deployments.
Emergency warning siren systems are public safety tools used to alert the population of incidents, such as weather and man-made threats. They are widely deployed in cities, industrial sites, military installations and educational institutions across the US and abroad.
Sirens are often activated via a radio frequency (RF) communications system to provide coverage over a large area. Does the security of these RF-based systems match their status as critical infrastructure? The 2017 Dallas siren hack showed that many older siren systems are susceptible to replay attacks, but what about more modern ones?
I studied San Francisco's Outdoor Public Warning System, an ATI deployment, for two years to learn how it was controlled. After piecing together clues on siren poles, and searching the entire radio spectrum for one unknown signal, I found the system's frequency and began passive analysis of the protocol. Monitoring the weekly siren tests, I made sense of patterns in the raw binary data and found the system was insecure and vulnerable to attack.
This presentation will take you on the journey of the research, and detail the tools and techniques used, including leveraging Software Defined Radio and GNU Radio to collect and analyse massive sets of RF data, and analyse a custom digital protocol. It will also cover the Responsible Disclosure process with the vendor, their response, and subsequent change to the protocol. A proof-of-concept will be shown for good measure.
Amateur radio played a significant role in the development of early radio and communications technologies in the 20th century. However, with the maturation of wireless (and especially digital) communication systems, many amateur radio hobbyists feel that they have been left behind by radio technology. The complexity of these new technologies challenges individual hobbyists, and the hobby remains stuck, in many respects, in a communications paradigm of the 1970s.
Although digital radio has seen significant adoption by amateurs ("hams") and their commercial amateur equipment manufacturers, the knowledge gap between hams' federal licensing requirements and the state of the digital radio art has become quite wide. Many amateurs retain the curiousity and innovative spirit of their forebears, but lack the technical fundamentals to fully understand the new technologies and innovate in the amateur radio space.
GNU Radio provides an excellent tool with which to introduce modern digital signal processing to amateur radio hobbyists.
In the past eighteen months, the speaker has led four presentation/workshops on GNU Radio for local amateur radio clubs in the Vancouver, BC area.
These sessions run for three to four hours and introduce DSP and SDR concepts to hams using the freely-available "Live GNU Radio" ISO. Students build some simple flowgraphs, and finally, a working broadcast FM receiver using a cheap RTL dongle, which they must purchase and bring to the workshop.
The sessions have been received with enthusiasm by hams with a broad range of skill levels: from computing science students in their early 20s to very senior hams in their 60s who simply have an interest in keeping up with technological trends. Students leave the workshop with new knowledge and a stronger understanding of how and (importantly) why digital radio works.
GNU Radio is an excellent educational tool, and this talk will present the speaker's observations on how to best utilize GNU Radio in teaching basic DSP and SDR concepts to an audience with a broad range of technological skills.
In the Sensors & Embedded Systems Group at Oak Ridge National Laboratory (ORNL), we are exploring various sensing and instrumentation applications using software defined radio (SDR). SDR has been utilized for both wireless surface acoustic wave (SAW) sensor interrogation as well as measurement of carbon fiber tow properties during fabrication. While vector network analyzers (VNA) could be used for each application, they are much too expensive and not robust enough to be deployed in the field. A conventional hardware radio composed of commercial-off-the-shelf (COTS) components could also be used, but these tend to be difficult to fine-tune and don't offer much adaptability. SDR, on the other hand, can offer comparable performance to a VNA or conventional hardware radio and can be easily adapted for a given application.
There has been great interest in the development of passive, wireless SAW sensors for electrical grid, nuclear energy, and national security applications. With this, there is a push for small, low-cost, high-performance wireless systems that can remotely interrogate the sensors. At ORNL we have developed an interrogation system based on noise RADAR techniques that utilizes the USRP B200mini, an UDOO x86 embedded computing platform, and a custom designed RF daughterboard. The system is currently being used to test a variety of SAW sensors for temperature, methane, and HF gas detection.
The Carbon Fiber Technology Facility (CFTF) at ORNL is exploring systems that can probe carbon fiber tow in production without physical contact. The goal is to be able to provide near-instantaneous process control feedback instead of waiting for physical analysis of the tow after it has completed the entire fabrication process. We have developed an USRP B200 based system, which mimics a scalar network analyzer, to transmit microwave frequency signals through the carbon fiber as a measure of resistivity. Current results have shown good correlation between the SDR resistivity measurements and measurement obtained from physical analysis of the tow.
Current results for each system will be discussed along with plans for further testing and integration for their respective applications.
This paper will consist of two portions. We will cover the use of Red Pitaya with GNU Radio and a detailed performance analysis of the Red Pitaya will be given as well as suggested modifications to improve the performance. The second portion will be the application of the Red Pitaya to Ionospheric Measurement, Solar Emission data, and Jovian-Io radio science data. This will include discussion of the antennas needed to make each work.
This session introduces an open source software framework for fuzzing arbitrary RF protocols, all the way down to the PHY. While fuzzing has long been relied on by security researchers to identify software bugs, applying fuzzing methodologies to RF and hardware systems has historically been challenging due to siloed tools and the limited capabilities of commodity RF chipsets.
The TumbleRF fuzzing orchestration framework addresses these shortfalls by defining core fuzzing logic while abstracting a hardware interface API that can be mapped for compatibility with any RF driver. Thus, supporting a new radio involves merely extending an API, rather than writing a protocol-specific fuzzer from scratch.
Attendees can expect to leave this talk with an understanding of how RF and hardware physical layers actually work, and how to identify security issues that lie latent in these designs.
Ettus Research's USRP Hardware Driver (UHD) release 3.13 includes a new way to control and interact with USRPs, a Python API. User applications can now be developed in Python, with no need to recompile, cross languages, or use third party solutions. The Python API has already eased development of various USRP-based tests within Ettus Research.
In the recent Colosseum channel emulator project, a calibration solution was created which measured the EVM of a known waveform transmitted across pairs of USRPs. Development of this Python API-based framework was facilitated by Python's ability to rapidly iterate on and test designs.
The Python API has been used within Ettus Research to develop internal continuous integration tests. One example is the Multi-USRP API tester, which uses the Python API to probe all available Multi-USRP function calls. Because the Python API is meant to mirror the C++ Multi-USRP API, it can be used to verify that every facet behaves as expected. Additionally, many continuous integration tests which require only basic DSP have been simplified. For example, the USRP phase alignment testing has moved from GNU Radio flowgraphs to simple scripts which use only the Python API and NumPy. This has greatly reduced the amount of setup and configuration required for these tests.
Python has also grown to become a popular language for many DSP applications. Tooling for Python development has also made great strides in recent years, allowing UHD users to now leverage technologies like Jupyter Notebooks, Plotly, and others to aid in development, collaboration, and teaching. The Python API allows users to integrate their favorite Python modules with UHD without crossing languages manually, saving samples to file, or using some other form of IPC. For example, many machine learning frameworks have Python interfaces (such as TensorFlow, Scikit-Learn, and Theano), which can now be seamlessly combined with UHD. Furthermore, Ettus Research hopes that users will find new and novel ways to use Python modules in conjunction with UHD's Python API.
The ADALM-PLUTO also known as PlutoSDR can be used as a RF streaming device over High-Speed USB 2.0 to Linux's Industrial I/O (IIO) clients like GNU Radio, or custom applications written in C, C++, C# or Python. However it can also be used as a standalone device, since it is an open Linux based ARM system. Therefore signal processing applications may be targeted to also run directly on the device itself. The libiio user space library abstracts the low-level details of the hardware, and provides a simple yet complete programming interface. In addition it makes the transport transparent, so it abstracts the transport medium (USB, IP network, serial, or local) away from the application. With a single line code change, and a cross compiler, applications can move from being run on a remote host, to run local on the device itself. This tutorial uses an open source ADS-B receiver as an example and shows multiple options on how to run it on the target.
This tutorial is not just applicable for the PlutoSDR, it's of general interest for anyone using the Linux IIO subsystem for high speed data capture and libIIO. Only lately, optionally community IIO support was added for the EPIQ Sidekiq Z2 and the Ettus E310, so that the content covered in this tutorial also applies for these commercial of the shelf SDR radios.
A brief introduction to the Linux IIO subsystem will be given. This presentation will furthermore talk about bottlenecks and limitations of the IIO subsystem for high speed sampled data systems. Introduce Linux Continuous (CMA) and DMA-able memory allocation issues. Latency and overhead trade-offs between buffer size and number of buffers. How Linux Zero-Copy decreases overhead and increase performance. A few words about libiio context timeouts and how they can be avoided. Last but not least this tutorial will highlight future enhancements and show work in progress.
Michael is Open Source Engineering Manager at Analog Devices GmbH in Munich, and also passionate and licensed HAM Radio Amateur. He first talked about Embedded Linux for DSPs on the Embedded Systems Conference Silicon Valley back in 2006, since then Michael is an active Linux kernel developer and open source contributor.
GNU Radio is the go-to library when it comes to open source software-defined radio. However GNU Radio can go beyond that. In this paper we will discuss the use of GNU Radio as a base library for an end product application that requires general signal processing as well as other decoding libraries. Specifically, we will address how GNU Radio can be leveraged for applications beyond software defined radio and other communication systems.
In order to create Scopy - an open source mixed signal analysis and generation toolkit, we chose to use GNU Radio, along with a variety of open source libraries and frameworks such as libiio, libsigrok, Qt5 or Qwt. Scopy currently interfaces with the ADALM-2000 hardware which provides two analog input channels, two analog output channels, as well as 16 digital I/O pins - capable of high speed synchronized buffered operations. Future plans include extending Scopy to interface with other hardware. Scopy uses libiio to interface with ADALM-2000. This allows Scopy to connect to the hardware via USB, as well as ethernet. By using an off the shelf (COTS) Wi-Fi dongle, the hardware can connect to a wireless network and Scopy can acquire data remotely from the ADALM-2000.
GNU Radio is used in this context to multiplex the data streams received from the hardware via gr-iio to the oscilloscope/ spectrum analyzer/ network analyzer. GNU Radio's efficient vector-optimized operations are used to implement instrument functionalities such as the oscilloscope reference waveform, digital AC coupling as well as math channels. The network analyzer uses the GNU Radio flow to create a full network analyzer signal chain. Combined with the M2K hardware it is able to characterize circuits up to 30MHz and represent the results on Bode, Nichols and Nyquist plots. The spectrum analyzer allows marker operations as well as different types of windowing up to 50MHz. The signal generator uses GNU Radio to output various types of user configurable signals such as sine, square waves or the results of time-dependant mathematical equations.
We used GNU Radio for an end application that does not comply with the traditional scope of the framework. Although GNU Radio is well modularized, starting and stopping instruments has been one of the challenges we faced. Since there is no trivial way to reconfigure a GNU Radio flow, we had to develop a method that recursively deletes blocks starting with a parent. This and the use of the copy block eased up flow reconfiguration.
GNU Radio is a good fit for this application as it abstracts the complexities of signal acquisition and analysis into an efficient data flow giving us more headroom to develop a more user friendly, touchscreen compatible GUI.
The ADALM-2000 also known as M2k is a Software Defined Measurement Platform that is a cross platform (Windows, Mac and Linux) USB oscilloscope and multi-function instrument that allows users to measure, visualize, generate, record, and control mixed-signal circuits of all kinds. It features two-channel digital oscilloscope and arbitrary function generator, with Time, Network and Spectrum Analyzer views. A 16-channel digital logic analyzer and pattern generator, with a countless number of Bus Analyzers for all kind of protocols such as I2C, SPI, UART, CAN, JTAG, SPDIF, etc. just to mention a few. Besides this it also has true RMS voltmeters and programmable power supplies all in a pocket sized instrument.
In the spring of 2018, the Army Signal Classification Challenge (ASCC) was announced to enhance the state-of-the-art in signal classification and modulation recognition using machine learning. A series of I/Q data examples were provided by the US government, and for each example, the modulation type was provided as one among a class of 24 modulations. The challenge was to develop machine learning-based algorithms to perform automatic modulation recognition after training on, and learning from, the labeled examples. This talk discusses the novel solutions that were developed by Georgia Tech Research Institute (GTRI) to address the ASCC, as well as how the government dataset fits into the broader efforts by members of the GNU Radio community to develop benchmark datasets for radio machine learning (radioml). The novel aspects to be covered include:
The ability to monitor the wireless spectrum in real-time is important in a variety of environments including high-security and control-system environments such as power plants and military facilities, as well as shared spectrum environments such as the 3.5 GHz band model that was announced by the Federal Communications Commission (FCC).
In all of these cases, real-time detection and classification of signals while minimizing missed detections and misclassifications is paramount.
Motivated by these important applications, we built a real-time system for spectrum monitoring and analysis which uses GNU Radio and Universal Software Radio Peripheral (USRP) X310s.
In this paper, we focus on the GNU Radio-specific implementation challenges we face as well as the approaches we take to tackle these challenges. We also present our experiences with our implementation.
Current computer architecture trends are moving towards parallelization by means of node replication and data parallelization, which optimize the execution speed of a given application. Increasing the number of nodes is constrained by the hardware platform in use; however, effective data parallelization techniques can improve processing speeds by leveraging existing resources of the platform. This paper presents the AVX2 and AVX512 instruction addition to several kernels in the VOLK library. We discuss the capabilities of the new extensions and their interaction with the VOLK library. Finally, we show profiling results of the speed enhancements added to the library for AVX capable machines.
There are several physical phenomena that RF and Communications engineers detest. Things like non-linear distortion, resonance and multi-path make it challenging to build radio/communication systems, and always have to be worked around or compensated. However, as we drop from gigahertz to kilohertz into the audio spectrum, we can take advantage some of these "dark" behaviors and turn them into something that sounds interesting to the ear. This talk will introduce some audio effects built in GNU Radio that embrace the impairments that communications engineers try to avoid. We will explore (and demonstrate) the common guitar effects of distortion, wah-wah and phasing to show how the dark side of DSP can also be used for good. This talk should show the flexibility of the GNU Radio platform as a general DSP framework that can be used to build more than just communication systems.
In this presentation, we will discuss the current transceiver technology of Analog Devices including some next-generation components. Specifically, an in-depth view of their architecture and advanced features that exists across the family will be discussed. To motivate the talk a series of examples will demonstrate these features with actual hardware, and different tools to model and control the transceivers will be featured. Since ADI transceivers are at the heart of many existing SDR solutions from companies all over the world, this talk will benefit many SDR users from hobbyists to defense system builders.
Understanding the internal operation of such transceivers as the AD936x, AD937x, and AD900x are important for optimal configuration for a given waveform or use case. This is especially important for the automatic gain control functionality since it can heavily impact the responsiveness and fidelity of your receiver. Configuration and impact of the ADC and filtering stages will also be included since it affects system performance as well as out of band interference control.
The field of machine learning has benefited from rapid advances in recent years, and DeepSig is at the forefront of applying them to signal processing and wireless systems. Building on the foundational work presented at previous GRCons, in this talk we present the technical results and methods from our latest research and experiments, including some previously un-released methods. We will present advances in RF sensing and learned physical layers with autoencoders, new open datasets to be shared with the community, and illustrate fluid interoperability with the GNU Radio and open-source SDR ecosystem. Finally, we will demonstrate several new capabilities and discuss current and ongoing trends in the field.
In this update from Ettus Research R&D, we will first discuss open problems in the realm of SDR in general, and take a look at items the author considers to be relevant issues for software defined radio in the upcoming years. From there, we will take a look at current projects Ettus Research is undertaking and see how it is contributing to open problems of the SDR domain.
The Army Rapid Capabilities Office (RCO) conducted an initial Signal Classification Challenge with industry and academia to promote advanced research to explore deep learning algorithms and the application of artificial intelligence (AI) for blind signal classification and characterization. This was a first step towards reducing the cognitive burden on Army EW personnel by providing them with a machine learning capability to identify and classify signals of interest embedded in a dense EM environment. This presentation will describe data generation (how was gnu radio used as part of this architecture) and the composition of the datasets in addition to highlighting future Army RCO efforts and opportunities.
Projects managing multiple components, languages, build tools, package managers, and hardware environments often lead to a dependency/environment hell. Presented is an intruduction to one way of managing the complexity using a tool called Nix which exhaustively tracks all dependencies in a declarative and reproducible manner. Demonstrate management of multiple versions of libraries/applications, environment isolation, and reproducible builds. Showcase complete build pipeline for multiple architectures, deployment methods, testing frameworks, and RF-in-the-loop validation of functionality. While still a work in progress, the effort yields specific recommendations for GNURadio which benefit similiar efforts and provides a mechanism for collaboration within and between teams.
In this talk, I describe two applications of algebraic topology to the physical layer of wireless transmissions. Algebraic topology is the study of invariants of shape using abstract algebra. Building upon the growing field of topological data analysis and topological signal processing, I show how distorted radio signals can be analyzed using this field of mathematics. I will present how topology helps with unsupervised automatic modulation classification and synchronization in a noisy environment. This talk is self-contained and background in topology is not assumed.
BAE Systems, in conjunction with DARPA, has developed the world's most reconfigurable and real-time adaptable software-defined radio. Referred to as Hedgehog, the initial version of the RF exciter/receiver combines the FPGA-like MATRICs reconfigurable DC-20 GHz four-channel transceiver-on-a-chip with the Xilinx RFSoC for a compact and programmable radio asset for DoD and commercial applications. BAE Systems has also worked with National Instruments to port the UHD and RFNoC software and firmware to the Hedgehog platform for rapid prototyping with the GNU Radio framework. BAE will demonstrate the capabilities of the radio through a series of GNU Radio-facilitated waveform modulations/demodulations plus real-time reconfiguration of the front-end as an example of how the radio can respond to changing environmental conditions or system requirements. The demonstration will introduce the Hedgehog platform's considerable configurable resources and outline the programming interface between the MATRICs front-end and GNU Radio. Finally, the demonstration will inform and engage the user community on the ultimate potential of the platform.
The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.
Analog Devices is the leading global high-performance analog technology company dedicated to solving the toughest engineering challenges. For Software Defined Radio solutions, ADI’s RadioVerse™ technology is built on its award winning wide band RF transceivers like the AD9363, AD9364, AD9361, AD9371, AD9375, and ADRV9009, however with advanced features begets complexity, and in order to master this complexity the RadioVerse design ecosystem accelerates advanced radio design and development. Come learn about who ADI is, and its market leading integrated radio platforms, software tools, evaluation and prototyping platforms, a range of software and HDL reference designs, system on modules and full radio solutions.
This presentation will illustrate how to use GNU Radio and USRP SDRs to explore and manipulate the Electromagnetic Spectrum to see the world around us in extraordinary ways. In what can only be described as “real life magic”, we will challenge your horizons and redefine what is possible.
This talk will explore the development of the bladeRF's modular and portable open source Automatic Gain Control. Tradeoffs between gain selection strategies, hardware limitations, waveforms requirements, and calibration routines will be discussed. The talk will also briefly introduce the bladeRF 2.0 micro which, even with an ASIC AGC, benefits from having a standardized software (HDL) based AGC as an alternative.
When implementing radio systems or working with real-world data, signals rarely look as you might first expect given a textbook understanding of signal processing. The real-world is full of impairments and effects that change & distort signals, sometimes in surprising ways. In this talk, we will investigate what some of these effects are, their cause, and how you might mitigate them.
We present the implementation of new GNU Radio blocks that support mobile underwater acoustic communications. More specifically, to address the Doppler shift that occurs during the transmission of data frames at a very low data rate. We aim at long distance communications, which require low frequency and extremely narrow bandwidth modulation, and implies weak signals. We build upon our previous works on ad hoc underwater wireless communications, to handle constant or variable (linearly and non-linearly) Doppler shift patterns. Experimental results are discussed using simulation of underwater autonomous vehicles and underwater wireless sensors. Our main contributions are in the design of the decoder, implemented using the GNU Radio development toolkit.
September 17 - 21, 2018 - Henderson Convention Center, Henderson, NevadaRegister Now