Thank you all for a great year of support, feedback, and interesting projects. With your encouragement and the passion we have see from the community, we see a very fun 2014 ahead of us. In the dev-uart_speedup branch (https://github.com/nuand/bladerf/tree/dev-uart_speedup ) you will see that we have been meticulously working on a couple of things:

• Mitigating any remaining buffering, and spectral inversion issues some of you may be experiencing.

• Increasing the baud rate of the UART bridge, which is the link that is used to communicate with the LMS and Si5338 through the Nios core. The new baud rate is 4Mbps, which is up from 115kbps so dumping registers on the CLI, changing channels and others configurations in UIs like GNURadio and OsmoSDR is now much faster.

• Adding hardware accelerated IQ correction. This HDL based DSP coprocessor corrects for magnitude and phase imbalances right as the samples are captured. The core greatly lessens the computational load on small embedded devices that still want to operate in entirely embedded environments (be it a RaspberryPi or the onboard FX3) and still achieve great system SNR.

• Acquiring parts for the mass production of the transverter boards. We have made some changes to the system performance that should greatly improve some of the RF characteristics of the expansion board. We will confirm these new specifications once we are sure that all new boards are capable of comfortably achieving them. If you have any questions or concerns about an order you placed that contained a HF/VHF transverter board please send an email to us at [email protected] .

• The OpenBTS branch (https://github.com/nuand/bladerf/tree/dev-openbts) adds timed RX and TX capabilities to bladeRF’s HDL through a metadata interface. The metadata packet format also allows for the development of drop-in HDL based modulators and encoders/decoders. More on this, and full instructions for OpenBTS in early January.

PS. We would like to thank Ben for adding bladeRF support to OpenLTE ( http://openlte.sourceforge.net/ )!

Hope everyone has a happy new year!

We have added many new exciting features and improvements to bladeRF in the past couple of weeks. By upgrading to the latest FX3 image ( http://nuand.com/fx3/latest.img ) you can now store FPGA images on the SPI flash by running `bladeRF-cli -L hostedx40.rbf`. This will allow your bladeRF to read an FPGA image from flash and program the FPGA without the need of a host computer. Autoloading was used to get the UAV-SDR operational ( http://www.nuand.com/blog/heading-to-defcon/ )!

Simon Brown of SDR-Radio fame has recently added bladeRF support to SDR-Radio v2.1 (which is still in beta). To download and try out SDR-Radio follow this link: http://v2.sdr-radio.com/Download.aspx . Scrolldown for a screenshot of SDR-Radio looking at 38.4MHz of bandwidth in the 2.4GHz band. A moderately active 802.11 device can be seen at 2.437GHz (which coincides perfectly 802.11 channel 6!). The narrower signals between 2.448GHz and 2.451GHz belong to Bluetooth devices.

Preliminary Matlab support with included instructions can be found at http://nuand.com/downloads/matlab.tar.gz . We will update everyone as soon as a separate git repository is launched to address Matlab support for bladeRF! There is also preliminary support for bladeRF in PyBOMBS now at https://github.com/nuand/pybombs . A quick guide to using PyBOMBS can be found at http://gnuradio.org/redmine/projects/pybombs/wiki/QuickStart , please ensure you clone our git repository when following those instructions.

Lastly, the HF/VHF transverter has undergone multiple architecture revisions, although they all seem to work we have felt like there might be room for a little more performance increase. We have taken into consideration many people’s requests and suggestions about the overall architecture of the transverter on IRC, the forums, and over email. We hope the proposed improvements we have come up with will be well worth the wait. We will present the semi-final block diagram and performance characteristics of the expansion board shortly.

We have come a long way with our platform support in the past couple of weeks. We have added and tested DC calibration, sped up FPGA programming, added a new bladeRF-flash tool and several streaming examples, and moved most of the API over to asynchronous calls.

To benefit from these changes you must upgrade your device, instructions on upgrading the bladeRF can be at https://github.com/Nuand/bladeRF/wiki/Upgrading-from-v1.0 .

Within the next week we will merge the SPI flash based FPGA loader, which allow the bladeRF to not require a computer to load the FPGA and in effect run headless. Afterwards, our focus will switch to back to merging in timestamped transmissions support, this will enable OpenBTS to run on the bladeRF.

There is now a Windows based installer for the bladeRF that will install all of the relevant drivers, user mode utilities, and FX3/FPGA images. The file can be directly downloaded from http://nuand.com/downloads/bladerf_win_installer.exe .

We would also like to thank the community contributors that have provided patches, and pointed out issues to us. (Bugs and requests for features can be filed via Github athttps://github.com/Nuand/bladeRF/issues/new ).

Lastly, RTucker (HoopyCat) has created an autobuilder for the FX3 and FPGA images. The autobuilder recompiles everything on every commit that is merged into master on Github. The autobuilder can be found at http://hoopycat.com/bladerf_builds/ .