Last September at the GNU Radio Conference in Boulder, Colorado, Ettus Research announced the RFNoC & Vivado Challenge for SDR (software-defined radio). Ettus’ RFNoC (RF Network on Chip) is designed to allow you to efficiently harness the latest-generation FPGAs for SDR applications without being an expert firmware or FPGA developer. Today, Ettus Research and Xilinx announced the three challenge winners.
Ettus’ GUI-based RFNoC design tool allows you to create FPGA applications as easily as you can create GNU Radio flowgraphs. This includes the ability to seamlessly transfer data between your host PC and an FPGA. It dramatically eases the task of FPGA off-loading in SDR applications. Ettus’ RFNoC is built upon Xilinx’s Vivado HLS.
Here are the three winning teams and their projects:
Finally, here’s a 5-minute video announcing the winners along with the prizes they have won:
Feeling like it’s time to go wireless with a Zynq SoC or Zynq UltraScale+ MPSoC? The new, $59 AES-PMOD-MUR-1DX-G WiFi/Bluetooth Pmod from Avnet.com (in stock now) is a fast way to get your Zynq on the air. It’s based on the ultra-small Murata Type 1DX module and it’s compatible with any development board that has access to a dual 2x6 Pmod connection. The product includes example guidelines for Avnet’s ZedBoard and UltraZed-EG Development Kits to demonstrate use of its wireless functions from PetaLinux.
Please contact Avnet directly for more information about the AES-PMOD-MUR-1DX-G WiFi/Bluetooth Pmod.
Novator Solutions recently licensed RFEL’s ChannelCore Flex RF channelizer IP for the heart of its NCR-2000 Channelizer server, which is built from a crate full of National Instruments (NI) PXIe modules. Using RFEL’s ChannelCore Flex RF channelizer IP, which is instantiated on NI’s PXIe-7975R FlexRIO FPGA module (based on a Xilinx Kintex-7 XC7K410T FPGA), Novator’s NCR-2000 Channelizer server can analyze thousands of RF signals with a single receiver. Ideally you’d dedicate one receiver to every signal (or RF channel) of interest. However, as the number of channels increases, that approach rapidly becomes impractical both physically and because of cost considerations. Instead, you use a channelizer.
Novator Solutions’ NCR-2000 Channelizer server
If you look closely in the photo above at the NCR-2000 Channelizer server’s stable of NI PXIe modules, you’ll see an NI Vector Signal Analyzer (VSA) on the right in addition to two PXIe-7975R FlexRIO FPGA modules towards the left. VSA options include the NI PXIe-5667 3.6GHz VSA or the PXIe-5668R High Performance 26.5GHz Wideband Signal Analyzer (based on a Xilinx Kintex-7 FPGA).
Here’s a block diagram of Novator Solutions’ NCR-2000 Channelizer server:
Novator Solutions’ NCR-2000 Channelizer server block diagram
The channelizer IP running on the FPGAs at the heart of the NCR-2000 Channelizer server are based on RFEL’s ChannelCore Flex IP, which can discriminate thousands of independently defined channels across any RF bandwidth in real time. Channel parameters that can be specified to an accuracy of better than 0.06 Hz.
Here’s a block diagram of RFEL’s ChannelCore Flex channelizer IP:
RFEL’s ChannelCore Flex channelizer IP block diagram
One key thing to note here is that this channelizer IP supports multiple inputs from multiple RF receivers. The IP block can accommodate as many as 16 inputs and dedicates separate FPGA coarse-stage resources to each input. Input parallelism can range from 1 to 16 coarse stages. With 16x input parallelism, a single ChannelCore Flex IP core can simultaneously process more than 50GHz of RF bandwidth.
Novator Solutions has also integrated the ChannelCore Flex IP into the heart of its new NCR-10 channelizer toolkit for NI’s USRP-2955 Software-Defined Radio Reconfigurable Device, which coincidentally is also based on a Xilinx Kintex-7 FPGA.
Now before you get the impression that RFEL’s ChannelCore Flex IP only runs on Xilinx Kintex-7 devices, I’d like to point out one line from the IP’s specification:
“Typical complex input sample rates of 500 Msps in mid-range FPGAs, with rates over 1 Gsps for certain channel plans in high-end devices.”
Finally, channelizers are used in a variety of applications including:
Please contact RFEL directly for more information about the ChannelCore Flex IP core for Xilinx All Programmable devices.
There’s a lot of 5G research already taking place at National Instruments’ (NI’s) new 5G Innovation Lab located in Austin, Texas (announced in May) and RCR Wireless News’ Martha DeGrasse recently published a report about the lab on the publication’s Web site. In this 5G Innovation Lab, NI’s proprietary T&M equipment and software are being used by carriers, chipmakers, and equipment vendors including AT&T, Verizon, Ericsson, and Intel to develop and test 5G hardware and protocols.
One of the research projects DeGrasse describes involves Verizon’s 5GTF—V5GTF, the Verizon 5G Technology Forum—which is developing a 28/39GHz wireless communications platform designed to replace fiber in fixed-wireless applications. There’s a running demo of this technology in the NI 5G Research Lab that uses a 28GHz link to convey a 3Gbps digital stream between a simulated basestation and a simulated fixed-location user device. Here’s a brand new, 2-minute video of a demo:
The equipment used in this V5GTF demo includes NI’s mmWave Transceiver System which includes FPGA processing modules based on Xilinx Virtex-7 and Kintex-7 FGPAs. The FPGA processing modules handle the complex, still-in-development modulation and control protocols being developed for mmWave communications.
I’ve written about SDRs (software-defined radios) built with Analog Devices’ AD9371 dual RF transceivers and Xilinx All Programmable devices before but never on the scale of VadaTech’s AMC597 300MHz-to-6GHz Octal Versatile Wideband Transceiver, which connects four AD9371 chips over JESD204B high-speed serial interfaces with a Xilinx Kintex UltraScale KU115 FPGA (the UltraScale DSP monster with 5520 DSP48 slices) and three banks of DDR4 SDRAM (two 8Gbyte banks and one 4Gbyte bank for a total of 20Gbytes). The whole system fits into an AMC form factor. Here’s a photo:
VadaTech AMC597 300MHz-to-6GHz Octal Versatile Wideband Transceiver
It’s essentially a solid block of raw SDR capability jammed into a compact, 55W (typ) package. This programmable powerhouse has the RF and processing capabilities you need to develop large, advanced digital radio systems using development tools from VadaTech, Analog Devices, and Xilinx. The AMC597 is compatible with Analog Devices’ design tools for AD9371; you can develop your own FPGA-based processing configuration with Xilinx’s Vivado Design Suite and System Generator for DSP; and VadaTech supplies reference designs with VHDL source code, documentation, and configuration binary files.
Anthony Collins, Harpinder Matharu, and Ehab Mohsen of Xilinx have just published an application article about the 16nm Xilinx RFSoC in MicroWave Journal titled “RFSoC Integrates RF Sampling Data Converters for 5G New Radio.” Xilinx announced the RFSoC, which is based on the 16nm Xilinx Zynq UltraScale+ MPSoC, back in February (see “Xilinx announces RFSoC with 4Gsamples/sec ADCs and 6.4Gsamples/sec DACs for 5G, other apps. When we say “All Programmable,” we mean it!”). The Xcell Daily blog with that announcement has been very popular. Last week, another blog gave more details (see “Ready for a few more details about the Xilinx All Programmable RFSoC? Here you go”), and now there’s this article in Microwave Journal.
This new article gets into many specifics with respect to designing the RFSoC into systems with block diagrams and performance numbers. In particular, there’s a table showing MIMO radio designs based on the RFSoC with 37% to 51% power reductions and significant pcb real-estate savings due to the RFSoC’s integrated, multi-Gbps ADCs and DACs.
If you’re looking to glean a few more technical details about the RFSoC, this article is the latest place to go.
There’s considerable 5G experimentation taking place as the radio standards have not yet gelled and researchers are looking to optimize every aspect. SDRs (software-defined radios) are excellent experimental tools for such research—NI’s (National Instruments’) SDR products especially so because, as the Wireless Communication Research Laboratory at Istanbul Technical University discovered:
“NI SDR products helped us achieve our project goals faster and with fewer complexities due to reusability, existing examples, and the mature community. We had access to documentation around the examples, ready-to-run conceptual examples, and courseware and lab materials around the grounding wireless communication topics through the NI ecosystem. We took advantage of the graphical nature of LabVIEW to combine existing blocks of algorithms more easily compared to text-based options.”
Researchers at the Wireless Communication Research Laboratory were experimenting with UFMC (universal filtered multicarrier) modulation, a leading modulation candidate technique for 5G communications. Although current communication standards frequently use OFDM (orthogonal frequency-division multiplexing), it is not considered to be a suitable modulation technique for 5G systems due to its tight synchronization requirements, inefficient spectral properties (such as high spectral side-lobe levels), and cyclic prefix (CP) overhead. UFMC has relatively relaxed synchronization requirements.
The research team at the Wireless Communication Research Laboratory implemented UFMC modulation using two USRP-2921 SDRs, a PXI-6683H timing module, and a PXIe-5644R VST (Vector signal Transceiver) module from National Instruments (NI)–and all programmed with NI’s LabVIEW systems engineering software. Using this equipment, they achieved better spectral results over the OFDM usage and, by exploiting UFMC’s sub-band filtering approach, they’ve proposed enhanced versions of UFMC. Details are available in the NI case study titled “Using NI Software Defined Radio Solutions as a Testbed of 5G Waveform Research.” This project was a finalist in the 2017 NI Engineering Impact Awards, RF and Mobile Communications category, held last month in Austin as part of NI Week.
5G UFMC Modulation Testbed based on Equipment from National Instruments
Note: NI’s USRP-2921 SDR is based on a Xilinx Spartan-6 FPGA; the NI PXI-6683 timing module is based on a Xilinx Virtex-5 FPGA; and the PXIe-5644R VST is based on a Xilinx Virtex-6 FPGA.
National Instruments (NI) has just announced a baseband version of its 2nd-Generation PXIe VST (Vector Signal Transceiver), the PXIe-5820, with 1GHz of complex I/Q bandwidth. It’s designed to address the most challenging RF front-end module and transceiver test applications. Of course, you program it with NI’s LabVIEW system engineering software like all NI instruments and, like its RF sibling the PXIe-5840, the PXIe-5820 baseband VST is based on a Xilinx Virtex-7 690T FPGA and a chunk of the FPGA’s programmable logic is available to users for creating real-time, application-specific signal processing using LabVIEW FPGA. According to Ruan Lourens, NI’s Chief Architect of RF R&D, “The baseband VST can be tightly synchronized with the PXIe-5840 RF VST to sub-nanosecond accuracy, to offer a complete solution for RF and baseband differential I/Q testing of wireless chipsets.”
NI’s new PXIe-5820 Baseband VST
How might you use this feature? Here’s a very recent, 2-minute video demonstration of a DPD (digital predistortion) measurement application that provides a pretty good example:
When someone asks where Xilinx All Programmable devices are used, I find it a hard question to answer because there’s such a very wide range of applications—as demonstrated by the thousands of Xcell Daily blog posts I’ve written over the past several years.
Now, there’s a 5-minute “Powered by Xilinx” video with clips from several companies using Xilinx devices for applications including:
That’s a huge range covered in just five minutes.
Here’s the video:
Signal Integrity Journal just published a new article titled “Addressing the 5G Challenge with Highly Integrated RFSoC,” written by four Xilinx authors. The articles discusses some potential uses for Xilinx RFSoC technology, announced in February. (See “Xilinx announces RFSoC with 4Gsamples/sec ADCs and 6.4Gsamples/sec DACs for 5G, other apps. When we say “All Programmable, we mean it!”)
Cutting to the chase of this 2600-word article, the Xilinx RFSoC is going to save you a ton of power and make it easier for you to achieve your performance goals for 5G and many other advanced, mixed-signal system designs.
If you’re involved in the design of a system like that, you really should read the article.
By Adam Taylor
Last week I mentioned, the Analog Devices AD9467 FMC in the blog and how we could use it with the Xilinx SDSoC development environment to capture data with a simple data-capture chain and then develop and accelerate the algorithm using a high-level language like C or C++.
Analog Devices AD9467 FMC and Zynq-based Avnet ZedBoard Combined
The AD9467 FMC contains the AD9467 ADC, which provides 16-bit quantization at sampling rates of up to 250Msamples/sec (MSPS). These specs allow us to use the AD9467 to sample Intermediate Frequency (IF) signals. An IF is used to move an RF carrier wave down from or up to a higher frequency for reception or transmission.
The first thing we need to do with the AD9467 board is to work out the clocking scheme we’ll use to provide the ADC with a sample clock. We have three options:
To change between the three sources, we add and remove ac coupling capacitors from the circuit to put the correct clock generator in the clock path. By default, the clock path is configured to use the external clock source.
However, before we can create an SDSoC Platform, we need to create a base design in Vivado. This base design interfaces with the AD9467 FMC and transfers the sampled data into the Zynq SoC’s PS (processing system) DDR memory using DMA. Rather helpfully, the AD9467 FMC comes with a Vivado example that we can use with the ZedBoard. This example design creates the structure to transfer samples into the PS DDR SDRAM using DMA.
To recreate this design, the first thing we need to do is download the Analog Devices Git Hub repository, which contains both the shared IP elements required and the actual Vivado design example. To ensure we are using the latest possible tool chain, select the latest tool revision from the Git Hub and download a zip of the repository or clone the repository from here.
To build this project, we need to be using either a Linux box or, if we are using Microsoft Windows, we’ll need to download and install CYGWIN. If you are using CYGWIN, you need to make sure you have Vivado in your path.
To build the project you just need to use either a terminal or CYGWIN to navigate to the AD9467_FMC directory and execute the make file for the Zed version.
Make file running in CYGWIN to recreate the project
Once this has been recreated, we will be able to open our project in Vivado, explore the design in the block diagram, and export the design. We can then use the test application software to complete the demo.
AD9467 FMC example design
As can be seen in the above example, these steps add the FMC example into the existing Zynq base hardware design so that all the other interfaces like HDMI are still available. These additional interfaces can be very useful to us. In the diagram above, you can see the highlighted path from the AD9467 receiver IP, into a DMA IP block and then an AXI Interconnect block that connects to a Zynq HP (high-performance) AXI port. This design allows the data move seamless into the PS DDR SDRAM for future processing.
Of course to do this we need to run some software on the Zynq SoC’s ARM Cortex-A9 processor to configure the AD9467, the AD9517, and the simple internal processing pipeline. You can download the demo application example from here on GitHub. Helpfully, it comes with batch files (one for Linux one for Windows), which are used to create the demo software application to support the Vivado design.
When we run this example on the Zynq SoC, we will find that it performs a number of tests prior to performing the first ADC sample capture.
Terminal Output from ZedBoard if the FMC is present
The samples will be stored at 0x0800_0000 within the DDR SDRAM. Using the debug facility within SDK, we can examine these values and see that they are updated when the sampling occurs.
DDR Memory location at 0x0800_0000 following power cycle
DDR Memory Location at 0x0800_0000 following the samples being captured
With this up and working, we can now think about how we can use the base platform efficiently to implement higher-level signal-processing algorithms.
Code is available on Github as always.
If you want E book or hardback versions of previous MicroZed chronicle blogs, you can get them below.
TI has a new design example for a 2-device power converter to supply multiple voltage rails to a Xilinx Zynq UltraScale+ MPSoC for Remote Radio Heads and wireless backhaul applications, but the design looks usable across the board for many applications of the Zynq MPSoC. The two TI power-control and -conversion devices in this reference design are the TPS6508640 configurable, multi-rail PMIC for multicore processors and the TPS544C25 high-current, single-channel dc-dc converter. Here’s a simplified diagram of the design:
Please contact TI for more information about these power-control and –conversion devices.
Epiq Solutions has announced the Matchstiq S12 SDR transceiver, an expansion to the Matchstiq transceiver family, which also includes the Matchstiq S10 and S11. All three Matchstiq family members pair a Freecale i.MX6 quad-core CPU, used for housekeeping and interfacing (Ethernet, HDMI, and USB), with a Xilinx Spartan-6 LX45T FPGA installed on the company’s Sidekiq MiniPCIe card, which performs the RF signal processing for SDR. These two devices, located on separate boards, communicate over a single PCIe lane and form a reusable SDR platform for the Matchstiq transceiver family. The Matchstiq S12 employs a Dropkiq frequency-extension board to take the bottom of its tuning frequency range below 1MHz. All three Matchstiq transceiver tuners top out at 6GHz and have 50MHz of channel bandwidth. The Matchstiq S10 and S11 SDR tuners go down to 70MHz.
Here are the block diagrams of all three Matchstiq transceivers, which illustrate the platform nature of the basic Matchstiq design:
Epic Solutions Matchstiq SDR Transceiver Block Diagrams
And here’s a family photo:
Epic Solutions Matchstiq SDR Transceiver Family
“Xilinx All Programmable FPGAs and SoCs are playing a pivotal role in building 5G systems that can be easily and rapidly updated and enhanced to align with emerging standards and opportunities. The majority of the industry’s 5G proof of concepts, test beds and early commercialization trials for eMBB, URLLC, and mMTC use cases are leveraging Xilinx technology,” because “merchant silicon does not exist and ASICs are not viable this early in the 5G standardization phase. … The first wave of commercial 5G system deployments are likely to rely on these prototypes.”
That’s the premise of a new blog written by Xilinx’s Director Communications Strategic & Technical Marketing Harpinder Matharu and posted on the knect365.com Web site. Follow the link to read Matharu’s full blog post.
For more 5G coverage in Xcell Daily, see:
MathWorks has just scheduled five dates with worldwide venues for its new “Software-Defined Radio with Zynq using Simulink” course. The full-day, hands-on class covers design and modeling of SDR systems using MATLAB and Simulink, targeting Xilinx Zynq SoCs. Here’s an overview of the course:
The course costs $750 or €700, depending on the venue. The venues and dates are:
Please contact MathWorks directly for more information about this SDR course.
The short video below from National Instruments (NI) demonstrates the use of four of NI’s PXIe-5840 VSTs (Vector Signal Transceivers) coupled over high-speed serial links to an NI ATCA-3671 FPGA Module to analyze and process multi-GHz RF signals in real time, all controlled by NI’s LabVIEW software. The result is real-time control and display of the RF analysis. That’s a lot to pack into a 3.5-minute video.
NI’s 2nd-generation PXIe-5840 VST is based on a Xilinx Virtex-7 690T FPGA (see “NI launches 2nd-Gen 6.5GHz Vector Signal Transceiver with 5x the instantaneous bandwidth, FPGA programmability”) and the ATCA-3671 incorporates four more Xilinx Virtex-7 690T FPGAs, bringing a total of 14,400 DSP slices to bear on signal-processing tasks. (For information about another interesting use of NI’s ATCA-3671 FPGA Modules, see “DARPA wants you to win $2M in its Grand Spectrum Collaboration Challenge. Yes, lots of FPGAs are involved.”)
AT&T recently announced the development of a one-of-a-kind 5G channel sounder—internally dubbed the “Porcupine” for obvious reasons—that can characterize a 5G transmission channel using 6000 angle-of-arrival measurements in 150msec, down from 15 minutes using conventional pan/tilt units. These channel measurements capture how wireless signals are affected in a given environment. For instance, channel measurements can show how objects such as trees, buildings, cars, and even people reflect or block 5G signals. The Porcupine allows measurement of 5G mmWave frequencies via drive testing, something that was simply not possible using other mmWave channel sounders. Engineers at AT&T used the mmWave Transceiver System and LabVIEW System Design Software including LabVIEW FPGA from National Instruments (NI) to develop this system.
AT&T “Porcupine” 5G Channel Sounder
NI designed the mmWave Transceiver System as a modular, reconfigurable SDR platform for 5G R&D projects. This prototyping platform offers 2GHz of real-time bandwidth for evaluating mmWave transmission systems using NI’s modular transmit and receive radio heads in conjunction with the transceiver system’s modular PXIe processing chassis.
The key to this system’s modularity is NI’s 18-slot PXIe-1085 chassis, which accepts a long list of NI processing modules as well as ADC, DAC, and RF transceiver modules. NI’s mmWave Transceiver System uses the NI PXIe-7902 FPGA module—based on a Xilinx Virtex-7 485T—for real-time processing.
NI PXIe-7902 FPGA module based on a Xilinx Virtex-7 485T
NI’s mmWave Transceiver System maps different mmWave processing tasks to multiple FPGAs in a software-configurable manner using the company’s LabVIEW System Design Software. NI’s LabVIEW relies on the Xilinx Vivado Design Suite for compiling the FPGA configurations. The FPGAs distributed in the NI mmWave Transceiver System provide the flexible, high-performance, low-latency processing required to quickly build and evaluate prototype 5G radio transceiver systems in the mmWave band—like AT&T’s Porcupine.
What do you do if you want to build a low-cost state-of-the-art, experimental SDR (software-defined radio) that’s compatible with GNURadio—the open-source development toolkit and ecosystem of choice for serious SDR research? You might want to do what Lukas Lao Beyer did. Start with the incredibly flexible, full-duplex Analog Devices AD9364 1x1 Agile RF Transceiver IC and then give it all the processing power it might need with an Artix-7 A50T FPGA. Connect these two devices on a meticulously laid out circuit board taking all RF-design rules into account and then write the appropriate drivers to fit into the GNURadio ecosystem.
Sounds like a lot of work, doesn’t it? It’s taken Lukas two years and four major design revisions to get to this point.
Well, you can circumvent all that work and get to the SDR research by signing up for a copy of Lukas’ FreeSRP board on the Crowd Supply crowd-funding site. The cost for one FreeSRP board and the required USB 3.0 cable is $420.
Lukas Lao Beyer’s FreeSRP SDR board based on a Xilinx Artix-7 A50T FPGA
With 32 days left in the Crowd Supply funding campaign period, the project has raised pledges of a little more than $12,000. That’s about 16% of the way towards the goal.
There are a lot of well-known SDR boards available, so conveniently, the FreeSRP Crowd Supply page provides a comparison chart:
If you really want to build your own, the documentation page is here. But if you want to start working with SDR, sign up and take delivery of a FreeSRP board this summer.
Gilles Garcia, Xilinx’s Communications Business Lead, recently appeared on TelecomTV in connection with the ETSI 5G Network Infrastructure Summit, held in Sophia Antipolis just outside of Nice, France on April 6. TelecomTV’s Director of Content asked Gilles about the 5G networking challenges he’s seeing as Xilinx works with the major 5G infrastructure equipment suppliers. Gilles answered with three major groups of challenges:
Here’s the TelecomTV video interview:
Here’s another amazing demo video of National Instrument’s (NI’s) PXIe-5840 VST (Vector Signal Transceiver) showing real-time, DVR-like capture of 1GHz of continuous-bandwidth RF data on a 24Tbyte RAID drive. You’d want this if you needed to capture a real-time, broad-spectrum set of RF signals for subsequent, more detailed analysis. The VST captures the broad-spectrum data and simultaneously streams it to the RAID storage box. (The NI PXIe-5840 VST is based on a Xilinx Virtex-7 690T FPGA for its real-time RF-generation and –analysis capabilities.)
Here’s the 2-minute video:
For more information about the 2nd-generation NI VST, see:
By Adam Taylor
I just received the most interesting email from Antti at Trenz, in which he pointed out that he had designed a 500MHz radio receiver using just four resistors, four capacitors, and a Xilinx series 7 FPGA. How did he do this? He is keeping that to himself for the moment. However, Antti thinks it would a great idea to open a challenge based upon this design to see if others in the FPGA community can explain how he achieved this. Of course, for the winners who supply the correct answer there will be Trenz goodies as prizes. (See below.)
The diagram below shows the components allowed to solve this challenge. You can redraw them if necessary to clarify the schematic. The values of R and C do not need to be optimized.
To prove that this is possible, the screen shots below show the input and the recovered signal inside the FPGA.
By this point I was thinking Delta Sigma ADC using the FPGA’s LVDS inputs. (There are papers and articles about this technique online.) However, Antti tells me this is not his solution and he was kind enough to provide a few hints for this challenge below:
Because they have so many Trenz prizes to give away to the winners, Antti has created three categories:
The closing date for entries is July 3rd. The judges will be Antti and myself (Adam Taylor).
If you want to enter your solution in any category email firstname.lastname@example.org
The multi-GHz processing capabilities of Xilinx FPGAs never fails to amaze me and the following video from National Instruments (NI) demonstrating the real-time signal-generation and analysis capabilities of the NI PXIe-5840 VST (Vector Signal Transceiver) are merely one more proof point. The NI VST is designed for use in a wide range of RF test systems including 5G and IoT RF applications, ultra-wideband radar prototyping, and RFIC testing. In the demo below, this 2nd-generation NI VST is generating an RF signal spanning 1.2GHz to 2.2GHz (1GHz of analog bandwidth) containing five equally spaced LTE channels. The analyzer portion of the VST is simultaneously and in real time demodulating and decoding the signal constellations in two of the five LTE channels.
The resulting analysis screen generated by NI’s LabVIEW software tells the story:
The reason that the NI PXIe-5840 VST can perform all of these feats in real time is because there’s a Xilinx Virtex-7 690T FPGA inside pulling the levers, making this happen. (NI’s 1st-generation VSTs employed Xilinx Virtex-6 FPGAs.)
Here's the 2-minute video of the NI VST demo:
Please contact National Instruments directly for more information on its VST family.
For additional blogs about NI’s line of VSTs, see:
You want to learn how to design with and use RF, right? Students from all levels and backgrounds looking to improve their RF knowledge will want to take a look at the new ADALM-PLUTO SDR USB Learning Module from Analog Devices. The $149 USB module has an RF range of 325MHz to 3.8GHz with separate transmit and receive channels and 20MHz of instantaneous bandwidth. It pairs two devices that seem made for each other: an Analog Devices AD9363 Agile RF Transceiver and a Xilinx Zynq Z-7010 SoC.
Analog Devices’ $149 ADALM-PLUTO SDR USB Learning Module
Here’s an extremely simplified block diagram of the module:
Analog Devices’ ADALM-PLUTO SDR USB Learning Module Block Diagram
However, the learning module’s hardware is of little use without training material and Analog Devices has already created dozens of online tutorials and teaching materials for this device including ADS-B aircraft position, receiving NOAA and Meteor-M2 weather satellite imagery, GSM analysis, listening to TETRA signals, and pager decoding.
Pentek has published the 10th edition of “Putting FPGAs to Work in Software Radio Systems,” a 90-page tutorial written by Rodger H. Hosking, Pentek’s Vice-President & Cofounder. As the preface of this tutorial guide states:
“FPGAs have become an increasingly important resource for software radio systems. Programmable logic technology now offers significant advantages for implementing software radio functions such as DDCs (Digital Downconverters). Over the past few years, the functions associated with DDCs have seen a shift from being delivered in ASICs (Application-Specific ICs) to operating as IP (Intellectual Property) in FPGAs.
“For many applications, this implementation shift brings advantages that include design flexibility, higher precision processing, higher channel density, lower power, and lower cost per channel. With the advent of each new, higher-performance FPGA family, these benefits continue to increase.
“This handbook introduces the basics of FPGA technology and its relationship to SDR (Software-Defined Radio) systems. A review of Pentek’s GateFlow FPGA Design Resources is followed by a discussion of features and benefits of FPGA-based DDCs. Pentek SDR products that utilize FPGA technology and applications based on such products are also presented.”
Pentek has long used Xilinx All Programmable devices in its board-level products and that long experience shows in some unique, multi-generational analysis of the performance improvements in Xilinx’s Virtex FPGA generations starting with the Virtex-II Pro family (introduced in 2002) and moving through the Virtex-7 device family.
By Dr. Rajan Bedi, Spacechips
Several of my satcom ground-segment clients and I are considering Xilinx's recently announced RFSoC for future transceivers and I want to share the benefits of this impending device. (Note: For more information on the Xilinx RFSoC, see “Xilinx announces RFSoC with 4Gsamples/sec ADCs and 6.4Gsamples/sec DACs for 5G, other apps. When we say “All Programmable,” we mean it!”)
Direct RF/IF sampling and direct DAC up-conversion are currently being used very successfully in-orbit and on the ground. For example, bandpass sampling provides flexible RF frequency planning with some spacecraft by directly digitizing L- and S-band carriers to remove expensive and cumbersome superheterodyne down-conversion stages. Today, many navigation satellites directly re-construct the L-band carrier from baseband data without using traditional up-conversion. Direct RF/IF Sampling and direct DAC up-conversion have dramatically reduced the BOM, size, weight, power consumption, as well as the recurring and non-recurring costs of transponders. Software-defined radio (SDR) has given operators real scalability, reusability, and reconfigurability. Xilinx's new RFSoC will offer further hardware integration advantages for the ground segment.
The Xilinx RFSoC integrates multi-Gsamples/sec ADCs and DACs into a 16nm Zynq UltraScale+ MPSoC. At this geometry and with this technology, the mixed-signal converters draw very little power and economies of scale make it possible to add a lot of digital post-processing (Small A/Big D!) to implement functions such as DDC (digital down-conversion), DUC (digital up-conversion), AGC (automatic gain control), and interleaving calibration.
While CMOS scaling has improved ADC and DAC sample rates, which results in greater bandwidths at lower power, the transconductance of transistors and the size of the analog input/output voltage swing are reduced for analog designs, which impacts G/T at the satellite receiver. (G/T is antenna gain-to-noise-temperature, a figure of merit in the characterization of antenna performance where G is the antenna gain in decibels at the receive frequency and T is the equivalent noise temperature of the receiving system in kelvins. The receiving system’s noise temperature is the summation of the antenna noise temperature and the RF-chain noise temperature from the antenna terminals to the receiver output.)
Integrating ADCs and DACs with Xilinx's programmable MPSoC fabric shrinks physical footprint, reduces chip-to-chip latency, and completely eliminates the external digital interfaces between the mixed-signal converters and the FPGA. These external interfaces typically consume appreciable power. For parallel-I/O connections, they also need large amounts of pc board space and are difficult to route.
There will be a number of devices in the Xilinx RFSoC family, each containing different ADC/DAC combinations targeting different markets. Depending on the number of integrated mixed-signal converters, Xilinx is predicting a 55% to 77% reduction in footprint compared to current discrete implementations using JESD204B high-speed serial links between the FPGA and the ADCs and DACs, as illustrated below. Integration will also benefit clock distribution both at the device and system level.
Figure 1: RFSoC device concept (Source Xilinx)
The RFSoC’s integrated 12-bit ADCs can each sample up to 4Gsamples/sec, which offers flexible bandwidth and RF frequency-planning options. The analog input bandwidth of each ADC appears to be 4GHz, which allows direct RF/IF sampling up to the S-band.
Direct RF/IF sampling obeys the bandpass Nyquist Theorem when oversampling at 2x the information bandwidth (or greater) and undersampling the absolute carrier frequencies. For example, the spectrum below shows a 48.5MHz L-band signal centerd at 1.65GHz, digitized using an undersampling rate of 140.5Msamples/sec. The resulting oversampling ratio is 2.9 with the information located in the 24th Nyquist zone. Digitization aliases the bandpass information to the first Nyquist zone, which may or may not be baseband depending on your application. If not, the RFSoC's integrated DDC moves the alias to dc, allowing the use of a low-pass filter.
Figure 2: Direct L-Band Sampling
As the sample rate increases, the noise spectral density spreads across a wider Nyquist region with respect to the original signal bandwidth. Each time the sampling frequency doubles, the noise spectral density decreases by 3dB as the noise re-distributes across twice the bandwidth, which increases dynamic range and SNR. Understandably, operators want to exploit this processing gain! A larger oversampling ratio also moves the aliases further apart, relaxing the specification of the anti-aliasing filter. Furthermore, oversampling increases the correlation between successive samples in the time-domain, allowing the use of a decimating filter to remove some samples and reduce the interface rate between the ADC and the FPGA.
The RFSoC’s integrated 14-bit DACs operate up to 6.4Gsamples/sec, which also offers flexible bandwidth and RF frequency-planning options.
Just like any high-frequency, large bandwidth mixed-signal device, designing an RFSoC into a system requires careful consideration of floor-planning, front/back-end component placement, routing, grounding, and analog-digital segregation to achieve the required system performance. The partitioning starts at the die and extends to the module/sub-system level with all the analog signals (including the sampling clock) typically on one side of an ADC or DAC. Given the RFSoC's high sampling frequencies, at the pcb level, analog inputs and outputs must be isolated further to prevent crosstalk between adjacent channels and clocks, and from digital noise.
At low carrier frequencies, the performance of an ADC or DAC is limited by its resolution and linearity (DNL/INL). However at higher signal frequencies, SNR is determined primarily by the sampling clock’s purity. For direct RF/IF applications, minimizing jitter will be key to achieving the desired performance as shown below:
Figure 3: SNR of an ideal ADC vs analog input frequency and clock jitter
While there are aspects of the mixed-signal processing that could be improved, from the early announcements and information posted on their website, Xilinx has done a good job with the RFSoC. Although not specifically designed for satellite communication, but more so for 5G MIMO and wireless backhaul, the RFSoC's ADCs and DACs have sufficient dynamic range and offer flexible RF frequency-planning options for many ground-segment OEMs.
The specification of the RFSoC's ADC will allow ground receivers to directly digitize the information broadcast at traditional satellite communication frequencies at L- and S-band as well as the larger bandwidths used by high-throughput digital payloads. Thanks to its reprogrammability, the same RFSoC-based architecture with its wideband ADCs can be re-used for other frequency plans without having to re-engineer the hardware.
The RFSoC's DAC specification will allow ground transmitters to directly construct approximately 3GHz of bandwidth up to the X-band (9.6GHz). Xilinx says that first samples of RFSoC will become available in 2018 and I look forward to designing the part into satcom systems and sharing my experiences with you.
Dr. Rajan Bedi pioneered the use of Direct RF/IF Sampling and direct DAC up-conversion for the space industry with many in-orbit satellites currently using these techniques. He was previously invited by ESA and NASA to present his work and was also part of the project teams which developed many of the ultra-wideband ADCs and DACs currently on the market. These devices are successfully operating in orbit today. Last year, his company, Spacechips, was awarded High-Reliability Product of the Year for advancing Software Defined Radio.
Spacechips provides space electronics design consultancy services to manufacturers of satellites and spacecraft around the world. The company also helps OEMs assess the benefits of COTS components and exploit the advantages of direct RF/IF sampling and direct DAC up-conversion. Prior to founding Spacechips, Dr. Bedi headed the Mixed-Signal Design Group at Airbus Defence & Space in the UK for twelve years. Rajan is the author of Out-of-this-World Design, the popular, award-winning blog on Space Electronics. He also teaches direct RF/IF sampling and direct DAC up-conversion techniques in his Mixed-Signal and FPGA courses which are offered around the world. Rajan offers a series of unique training courses, Courses for Rocket Scientists, which teach and compare all space-grade FPGAs as well as the use of COTS Xilinx UltraScale and UltraScale+ parts for implementing spacecraft IP. Rajan has designed every space-grade FPGA into satellite systems!
By Lei Guan, MTS Nokia Bell Labs (email@example.com)
Many wireless communications signal-processing stages, for example equalization and precoding, require linear convolution functions. Particularly, complex linear convolution will play a very important role in future-proofing massive MIMO system through frequency-dependent, spatial-multiplexing filter banks (SMFBs), which enable efficient utilization of wireless spectrum (see Figure 1). My team at Nokia Bell Labs has developed a compact, FPGA-based SMFB implementation.
Figure 1 - Simplified diagram of SMFB for Massive MIMO wireless communications
Architecturally, linear convolution shares the same structure used for discrete finite impulse response (FIR) filters, employing a combination of multiplications and additions. Direct implementation of linear convolution in FPGAs may not satisfy the user constraints regarding key DSP48 resources, even when using the compact semi-parallel implementation architecture described in “Xilinx FPGA Enables Scalable MIMO Precoding Core” in the Xilinx Xcell Journal, Issue 94.
From a signal-processing perspective, the discrete FIR filter describes the linear convolution function in the time domain. Because the linear convolution in the time domain is equivalent to multiplication in the frequency domain, an alternative algorithm—called “fast linear convolution” (FLC)—is good candidate for FPGA implementation. Unsurprisingly, such an implementation is a game of trade-offs between space and time, between silicon area and latency. In this article, we mercifully skip the math for the FLC operation (but you will find many more details in the book “FPGA-based Digital Convolution for Wireless Applications”). Instead, let’s take closer look at the multi-branch FLC FPGA core that our team created.
The design targets supplied by the system team included:
Figure 2 shows the top-level design of the resulting FLC core in the Vivado System Generator Environment. Figure 3 illustrates the simplified processing stages at the module level with four branches as an example.
Figure 2 - Top level of the FLC core in Xilinx Vivado System Generator
Figure 3 - Illustration of multi-branch FLC-core processing (using 4 branches as an example)
The multi-branch FLC-core contains the following five processing stages, isolated by registers for logic separation and timing improvement:
Figure 4 - Simple Dual-Port RAM based input data buffer and reproduce stage
Table 1 compares the performance of our FLC design and a semi-parallel solution. Our compact FLC core implemented with Xilinx UltraScale and UltraScale+ FPGAs creates a cost-effective, power-efficient, single-chip frequency dependent Massive MIMO spatial multiplexing solution for actual field trials. For more information, please contact the author.
A simple press release last month from the UK’s U of Bristol announced a 5G Massive MIMO milestone jointly achieved by BT, the Universities of Bristol and Lund, and National Instruments (NI): serving 2Gbps to 24 users simultaneously using a 20MHz LTE channel. That’s just short of 100 bits/sec/Hz and improves upon today’s LTE system capacity by 10x. The system that achieved this latest LTE milestone is based on the same Massive MIMO SDR system based on NI USRP RIO dual-channel SDR radios that delivered 145.6 bps/Hz in 5G experiments last year. (See “Kapow! NI-based 5G Massive MIMO SDR proto system “chock full of FPGAs” sets bandwidth record: 145.6 bps/Hz in 20MHz channel.”)
According to the press release:
“Initial experiments took place in BT’s large exhibition hall and used 12 streams in a single 20MHz channel to show the real-time transmission and simultaneous reception of ten unique video streams, plus two other spatial channels demonstrating the full richness of spatial multiplexing supported by the system.
“The system was also shown to support the simultaneous transmission of 24 user streams operating with 64QAM on the same radio channel with all modems synchronising over-the-air. It is believed that this is the first time such an experiment has been conducted with truly un-tethered devices, from which the team were able to infer a spectrum efficiency of just less than 100bit/s/Hz and a sum rate capacity of circa two Gbits/s in this single 20MHz wide channel.”
The NI USRP SDRs are based on Xilinx Kintex-7 325T FPGAs. Again, quoting from the press release:
“The experimental system uses the same flexible SDR platform from NI that leading wireless researchers in industry and academia are using to define 5G. To achieve accurate, real-time performance, the researchers took full advantage of the system's FPGAs using LabVIEW Communications System Design and the recently announced NI MIMO Application Framework. As lead users, both the Universities of Bristol and Lund worked closely with NI to implement, test and debug this framework prior to its product release. It now provides the ideal foundations for the rapid development, optimization and evaluation of algorithms and techniques for massive MIMO.”
Here’s a BT video describing this latest milestone in detail:
National Instruments (NI) has just added two members to its growing family of USRP RIO SDRs (software-defined radios)—the USRP-2944 and USRP-2945—with the widest frequency ranges, highest bandwidth, and best RF performance in the family. The USRP-2945 features a two-stage superheterodyne architecture that achieves superior selectivity and sensitivity required for applications such as spectrum analysis and monitoring, and signals intelligence. With four receiver channels, and the capability to share local oscillators, this SDR also sets new industry price/performance benchmarks for direction-finding applications. The USRP-2944 is a 2x2 MIMO-capable SDR that features 160MHz of bandwidth per channel and a frequency range of 10 MHz to 6 GHz. This SDR operates in bands well suited to LTE and WiFi research and exploration.
NI USRP RIO Platform
Like all of its USRP RIO products, the NI USRP-2944 and USRP-2945 incorporate Xilinx Kintex-7 FPGAs for local, real-time signal processing. The Kintex-7 FPGA implements a reconfigurable LabVIEW FPGA target that incorporates DSP48 coprocessing for high-rate, low-latency applications. With the company’s LabVIEW unified design flow, researchers can create prototype designs faster and significantly shorten the time needed to achieve results.
Here’s a block diagram showing the NI USRP RIO SDR architecture:
USRP RIO Block Diagram
Adam Taylor just published an EETimes review of the Xilinx RFSoC, announced earlier this week. (See “Game-Changing RFSoCs from Xilinx”.) Taylor has a lot of experience with high-speed analog converters: he’s designed systems based on them—so his perspective is that of a system designer who has used these types of devices and knows where the potholes are—and he’s worked for a semiconductor company that made them—so he should know what to look for with a deep, device-level perspective.
Here’s the capsulized summary of his comments in EETimes:
“The ADCs are sampled at 4 Gsps (gigasamples per second), while the DACs are sampled at 6.4 Gsps, all of which provides the ability to work across a very wide frequency range. The main benefit of this, of course, is a much simpler RF front end, which reduces not only PCB footprint and the BOM cost but -- more crucially -- the development time taken to implement a new system.”
“…these devices offer many advantages beyond the simpler RF front end and reduced system power that comes from such a tightly-coupled solution.”
“These devices also bring with them a simpler clocking scheme, both at the device-level and the system-level, ensuring clock distribution while maintaining low phase noise / jitter between the reference clock and the ADCs and DACs, which can be a significant challenge.”
“These RFSoCs will also simplify the PCB layout and stack, removing the need for careful segregation of high-speed digital signals from the very sensitive RF front-end.”
“I, for one, am very excited to learn more about RFSoCs and I cannot wait to get my hands on one.”
For more information about the new Xilinx RFSoC, see “Xilinx announces RFSoC with 4Gsamples/sec ADCs and 6.4Gsamples/sec DACs for 5G, other apps. When we say ‘All Programmable,’ we mean it!” and “The New All Programmable RFSoC—and now the video.”
Yesterday, Xilinx announced breakthrough RF converter technology that allows the creation of an RFSoC with multi-Gsamples/sec DACs and ADCs on the same piece of TSMC 16nm FinFET silicon as the digital programmable-logic circuitry, the microprocessors, and the digital I/O. This capability transforms the Zynq UltraScale+ MPSoC into an RFSoC that's ideal for implementing 5G and other advanced RF system designs. (See “Xilinx announces RFSoC with 4Gsamples/sec ADCs and 6.4Gsamples/sec DACs for 5G, other apps. When we say ‘All Programmable,’ we mean it!” for more information about that announcement.)
Today there’s a 4-minute video with Sr. Staff Technical Marketing Engineer Anthony Collins providing more details including an actual look at the performance of a 16nm test chip with the 12-bit, 4Gsamples/sec ADC and the 14-bit, 6.4Gsamples/sec DAC in operation.
Here’s the video:
To learn more about the All Programmable RFSoC architecture, click here or contact your friendly, neighborhood Xilinx sales representative.