OQPSK Modem Simulation

A friend of mine is developing a commercial OQPSK modem and was a bit stuck. I’m not surprised as I’ve had problems with OQPSK in the past as well. He called to run a few ideas past me and I remembered I had developed a coherent GMSK modem simulation a few years ago. Turns out MSK and friends like GMSK can be interpreted as a form of OQPSK.

A few hours later I had a basic OQPSK modem simulation running. At that point we sat down for a bottle of Sparkling Shiraz and some curry to celebrate. The next morning, slightly hung over, I spent another day sorting out the diabolical phase and timing ambiguity issues to make sure it runs at all sorts of timing and phase offsets.

So oqsk.m is a reference implementation of an Offset QPSK (OQPSK) modem simulation, written in GNU Octave. It’s complete, including timing and phase offset estimation, and phase/timing ambiguity resolution. It handles phase, frequency, timing, and sample clock offsets. You could run it over real world channels.

It’s performance is bang on ideal for QPSK:

I thought it would be useful to publish this blog post as OQPSK modems are hard. I’ve had a few run-in with these beasts over the years and had headaches every time. This business about the I and Q arms being half a symbol offset from each other makes phase synchronisation very hard and does your head in. Here is the Tx waveform, you can see the half symbol time offset in the instant where I and Q symbols change:

As this is unfiltered OQPSK, the Tx waveform is just the the Tx symbols passed through a zero-order hold. That’s a fancy way of saying we keep the symbols values constant for M=4 samples then change them.

There are very few complete reference implementations of high quality modems on the Internet, so it’s become a bit of a mission of mine. By “complete” I mean pushing past the textbook definitions to include real world synchronisation. By “high quality” I mean tested against theoretical performance curves with different channel impairments. Or even tested at all. OQPSK is a bit obscure and it’s even harder to find any details of how to build a real world modem. Plenty of information on the basics, but not the nitty gritty details like synchronisation.

The PLL and timing loop simultaneously provides phase and timing estimation. I derived it from a similar algorithm used for the GMSK modem simulation. Unusually for me, the operation of the timing and phase PLL loop is still a bit of mystery. I don’t quite fully understand it. Would welcome more explanation from any readers who are familiar to it. Parts of it I understand (and indeed I engineered) – the timing is estimated on blocks of samples using a non-linearity and DFT, and the PLL equations I worked through a few years ago. It’s also a bit old school, I’m more familiar with feed forward type estimators and not something this “analog”. Oh well, it works.

Here is the phase estimator PLL loop doing it’s thing. You can see the Digital Controlled Oscillator (DCO) phase tracking a small frequency offset in the lower subplot:

Phase and Timing Ambiguities

The phase/timing estimation works quite well (great scatter diagram and BER curve), but can sync up with some ambiguities. For example the PLL will lock on the actual phase offset plus integer multiples of 90 degrees. This is common with phase estimators for QPSK and it means your constellation has been rotated by some multiple of 90 degrees. I also discovered that combinations of phase and timing offsets can cause confusion. For example a 90 degree phase shift swaps I and Q. As the timing estimator can’t tell I from Q it might lock onto a sequence like …IQIQIQI… or …QIQIQIQ…. leading to lots of pain when you try to de-map the sequence back to bits.

So I spent a Thursday exploring these ambiguities. I ended up correlating the known test sequence with the I and Q arms separately, and worked out how to detect IQ swapping and the phase ambiguity. This was tough, but it’s now handling the different combinations of phase, frequency and timing offsets that I throw at it. In a real modem with unknown payload data a Unique Word (UW) of 10 or 20 bits at the start of each data frame could be used for ambiguity resolution.

Optional Extras

The modem lacks an initial frequency offset estimator, but the PLL works OK with small freq offsets like 0.1% of the symbol rate. It would be useful to add an outer loop to track these frequency offsets out.

As it uses feedback loops its not super fast to sync and best suited to continuous rather than burst operation.

The timing recovery might need some work for your application, as it just uses the nearest whole sample. So for a small over-sample rate M=4, a timing off set of 2.7 samples will mean it chooses sample 3, which is a bit coarse, although given our BER results it appears unfiltered PSK isn’t too sensitive to timing errors. Here is the timing estimator tracking a sample clock offset of 100ppm, you can see the coarse quantisation to the nearest sample in the lower subplot:

For small M, a linear interpolator would help. If M is large, say 10 or 20, then using the nearest sample will probably be good enough.

This modem is unfiltered PSK, so it has broad lobes in the transmit spectrum. Here is the Tx spectrum at Eb/No=4dB:

The transmit filter is just a “zero older hold” and the received filter an integrator. Raised cosine filtering could be added if you want a narrow bandwidth. This will probably make it more sensitive to timing errors.

Like everything with modems, test it by measuring the BER. Please.

Links

oqsk.mGNU Octave OQPSK modem simulation

GMSK Modem Simulation blog post that was used as a starting point for the OQPSK modem.

Codec 2 700C

My endeavor to produce a digital voice mode that competes with SSB continues. For a big chunk of 2016 I took a break from this work as I was gainfully employed on a commercial HF modem project. However since December I have once again been working on a 700 bit/s codec. The goal is voice quality roughly the same as the current 1300 bit/s mode. This can then be mated with the coherent PSK modem, and possibly the 4FSK modem for trials over HF channels.

I have diverged somewhat from the prototype I discussed in the last post in this saga. Lots of twists and turns in R&D, and sometimes you just have to forge ahead in one direction leaving other branches unexplored.

Samples

Sample 1300 700C
hts1a Listen Listen
hts2a Listen Listen
forig Listen Listen
ve9qrp_10s Listen Listen
mmt1 Listen Listen
vk5qi Listen Listen
vk5qi 1% BER Listen Listen
cq_ref Listen Listen

Note the 700C samples are a little lower level, an artifact of the post filtering as discussed below. What I listen for is intelligibility, how easy is the same to understand compared to the reference 1300 bit/s samples? Is it muffled? I feel that 700C is roughly the same as 1300. Some samples a little better (cq_ref), some (ve9qrp_10s, mmt1) a little worse. The artifacts and frequency response are different. But close enough for now, and worth testing over air. And hey – it’s half the bit rate!

I threw in a vk5qi sample with 1% random errors, and it’s still usable. No squealing or ear damage, but perhaps more sensitive that 1300 to the same BER. Guess that’s expected, every bit means more at a lower bit rate.

Some of the samples like vk5qi and cq_ref are strongly low pass filtered, others like ve9qrp are “flat” spectrally, with the high frequencies at about the same level as the low frequencies. The spectral flatness doesn’t affect intelligibility much but can upset speech codecs. Might be worth trying some high pass (vk5qi, cq_ref) or low pass (ve9qrp_10s) filtering before encoding.

Design

Below is a block diagram of the signal processing. The resampling step is the key, it converts the time varying number of harmonic amplitudes to fixed number (K=20) of samples. They are sampled using the “mel” scale, which means we take more finely spaced samples at low frequencies, with coarser steps at high frequencies. This matches the log frequency response of the ear. I arrived at K=20 by experiment.

The amplitudes and even the Vector Quantiser (VQ) entries are in dB, which is very nice to work in and matches the ears logarithmic amplitude response. The VQ was trained on just 120 seconds of data from a training database that doesn’t include any of the samples above. More work required on the VQ design and training, but I’m encouraged that it works so well already.

Here is a 3D plot of amplitude in dB against time (300 frames) and the K=20 frequency vectors for hts1a. You can see the signal evolving over time, and the low levels at the high frequency end.

The post filter is another key step. It raises the spectral peaks (formants) an lowers the valleys (anti-formants), greatly improving the speech quality. When the peak/valley ratio is low, the speech takes on a muffled quality. This is an important area for further investigation. Gain normalisation after post filtering is why the 700C samples are lower in level than the 1300 samples. Need some more work here.

The two stage VQ uses 18 bits, energy 4 bits, and pitch 6 bits for a total of 28 bits every 40ms frame. Unvoiced frames are signalled by a zero value in the pitch quantiser removing the need for a voicing bit. It doesn’t use differential in time encoding to make it more robust to bit errors.

Days and days of very careful coding and checks at each development step. It’s so easy to make a mistake or declare victory early. I continually compared the output speech to a few Codec 2 1300 samples to make sure I was in the ball park. This reduced the subjective testing to a manageable load. I used automated testing to compare the reference Octave code to the C code, porting and testing one signal processing module at a time. Sometimes I would just printf rows of vectors from two versions and compare the two, old school but quite effective and spotting the step where the bug crept in.

Command line

The Octave simulation code can be driven by the scripts newamp1_batch.m and newamp1_fby.m, in combination with c2sim.

To try the C version of the new mode:

codec2-dev/build_linux/src$ ./c2enc 700C ../../raw/hts1a.raw - | ./c2dec 700C - -| play -t raw -r 8000 -s -2 -

Next Steps

Some thoughts on FEC. A (23,12) Golay code could protect the most significant bits of 1st VQ index, pitch, and energy. The VQ could be organised to tolerate errors in a few of its bits by sorting to make an error jump to a ‘close’ entry. The extra 11 parity bits would cost 1.5dB in SNR, but might let us operate at significantly lower in SNR on a HF channel.

Over the next few weeks we’ll hook up 700C to the FreeDV API, and get it running over the air. Release early and often – lets find out if 700C works in the real world and provides a gain in performance on HF channels over FreeDV 1600. If it looks promising I’d like to do another lap around the 700C algorithm, investigating some of the issues mentioned above.

Physics of Road Rage

A few days ago while riding my bike I was involved in a spirited exchange of opinions with a gentleman in a motor vehicle. After said exchange he attempted to run me off the road, and got out of his car, presumably with intent to assault me. Despite the surge of adrenaline I declined to engage in fisticuffs, dodged around him, and rode off into the sunset. I may have been laughing and communicating further with sign language. It’s hard to recall.

I thought I’d apply some year 11 physics to see what all the fuss was about. I was in the middle of the road, preparing to turn right at a T-junction (this is Australia remember). While his motivations were unclear, his vehicle didn’t look like an ambulance. I am assuming he as not an organ-courier, and that there probably wasn’t a live heart beating in an icebox on the front seat as he raced to the transplant recipient. Rather, I am guessing he objected to me being in that position, as that impeded his ability to travel at full speed.

The street in question is 140m long. Our paths crossed half way along at the 70m point, with him traveling at the legal limit of 14 m/s, and me a sedate 5 m/s.

Lets say he intended to brake sharply 10m before the T junction, so he could maintain 14 m/s for at most 60m. His optimal journey duration was therefore 4 seconds. My monopolization of the taxpayer funded side-street meant he was forced to endure a 12 second journey. The 8 second difference must have seemed like eternity, no wonder he was angry, prepared to risk physical injury and an assault charge!

Horus 39 – Fantastic High Speed SSDV Images

A great result from our high speed SSDV image (Wenet) system, which we flew as part of Horus 38 on Saturday Dec 3. A great write up and many images on the AREG web site.

One of my favorite images below, just before impact with the ground. You can see the parachute and the tangled remains of the balloon in the background, the yellow fuzzy line is the nylon rope close to the lens.

Well done to the AREG club members (in particular Mark) for all your hard work in preparing the payloads and ground stations.

High Altitude Balloons is a fun hobby. It’s a really nice day out driving in the country with nice people in a car packed full of technology. South Australia has some really nice bakeries that we stop at for meat pies and donuts on the way. Yum. It was very satisfying to see High Definition (HD) images immediately after take off as the balloon soared above us. Several ground stations were collecting packets that were re-assembled by a central server – we crowd sourced the image reception.

Open Source FSK modem

Surprisingly we were receiving images while mobile for much of the flight. I could see the Eb/No move up and down about 6dB over 3 second cycles, which we guess is due to rotation or swinging of the payload under the balloon. The antennas used are not omnidirectional so the change in orientation of tx and rx antennas would account for this signal variation. Perhaps this can be improved using different antennas or interleaving/FEC.

Our little modem is as good as the Universe will let us make it (near perfect performance against theory) and it lived up to the results predicted by our calculations and tested on the ground. Bill, VK5DSP, developed a rate 0.8 LDPC code that provides 6dB coding gain. We were receiving 115 kbit/s data on just 50mW of tx power at ranges of over 100km. Our secret is good engineering, open source software, $20 SDRs, and a LNA. We are outperforming commercial chipsets with open source.

The same modem has been used for low bit rate RTTY telemetry and even innovative new VHF/UHF Digital Voice modes.

The work on our wonderful little FSK modem continues. Brady O’Brien, KC9TPA has been refactoring the code for the past few weeks. It is now more compact, has a better command line interface, and most importantly runs faster so we getting close to running high speed telemetry on a Raspberry Pi and fully embedded platforms.

I think we can get another 4dB out of the system, bringing the MDS down to -116dBm – if we use 4FSK and lose the RS232 start/stop bits. What we really need next is custom tx hardware for open source telemetry. None of the chipsets out there are quite right, and our demod outperforms them all so why should we compromise?

Recycled Laptops

The project has had some interesting spin offs. The members of AREG are getting really interested in SDR on Linux resulting in a run on recycled laptops from ASPItech, a local electronics recycler!

Links

Balloon meets Gum Tree
Horus 37 – High Speed SSTV Images
High Speed Balloon Data Link
All Your Modem are Belong To Us
FreeDV 2400A and 2400B Demos
Wenet Source Code
Nov 2016 Wenet Presentation

Balloon Meets Gum Tree

Today I attended the launch of Horus 38, a high altitude ballon flight carrying 4 payloads, one of which was the latest version of the SSDV system Mark and I have been working on.

Since the last launch, Mark and I have put a lot of work into carefully integrating a rate 0.8 LDPC code developed by Bill, VK5DSP. The coded 115 kbit/s system is now working error free on the bench down to -112dBm, and can transfer a new hi-res image in just a few seconds. With a tx power of 50mW, we estimate a line of site range of 100km. We are now out-performing commercial FSK telemetry chip sets using our open source system.

However disaster struck soon after launch at Mt Barker High School oval. High winds blew the payloads into a tree and three of them were chopped off, leaving the balloon and a lone payload to continue into the stratosphere. One of the payloads that hit the tree was our SSDV, tumbling into a neighboring back yard. Oh well, we’ll have another try in December.

Now I’ve been playing a lot of Kerbal Space Program lately. It’s got me thinking about vectors, for example in Kerbal I learned how to land two space craft at exactly the same point on the Mun (Moon) using vectors and some high school equations of motion. I’ve also taken up sailing – more vectors involved in how sails propel a ship.

The high altitude balloon consists of a latex, helium filled weather balloon a few meters in diameters. Strung out beneath that on 50m of fishing line are a series of “payloads”, our electronic gizmos in little foam boxes. The physical distance helps avoid interference between the radios in each box.

While the balloon was held near the ground, it was keeled over at an angle:

It’s tethered, and not moving, but is acted on by the force of the lift from the helium and drag from the wind. These forces pivot the balloon around an arc with a radius of the tether. If these forces were equal the balloon would be at 45 degrees. Today it was lower, perhaps 30 degrees.

When the balloon is released, it is accelerated by the wind until it reaches a horizontal velocity that matches the wind speed. The payloads will also reach wind speed and eventually hang vertically under the balloon due to the force of gravity. Likewise the lift accelerates the balloon upwards. This is balanced by drag to reach a vertical velocity (the ascent rate). The horizontal and vertical velocity components will vary over time, but lets assume they are roughly constant over the duration of our launch.

Now today the wind speed was 40 km/hr, just over 10 m/s. Mark suggested a typical balloon ascent rate of 5 m/s. The high school oval was 100m wide, so the balloon would take 100/10 = 10s to traverse the oval from one side to the gum tree. In 10 seconds the balloon would rise 5×10 = 50m, approximately the length of the payload string. Our gum tree, however, rises to a height of 30m, and reached out to snag the lower 3 payloads…..

Horus 37 – High Speed SSTV Images

Today I was part of the AREG team that flew Horus 37 – a High Altitude Balloon flight. The payload included hardware sending Slow Scan TV (SSTV) images at 115 kbit/s, based on the work Mark and I documented in this blog post from earlier this year.

It worked! Using just 50mW of transmit power and open source software we managed to receive SSTV images at bit rates of up to 115 kbit/s:

More images here.

Here is a screen shot of the Python dashboard for the FSK demodulator that Mark and Brady have developed. It gives us some visibility into the demod state and signal quality:

(View-Image on your browser to get a larger version)

The Eb/No plot shows the signal strength moving up and down over time, probably due to motion of our car. The Tone Frequency Estimate shows a solid lock on the two FSK frequencies. The centre of the Eye Diagram looks good in this snapshot.

Octave and C LDPC Library

There were some errors in received packets, which appear as stripes in the images:

On the next flight we plan to add a LDPC FEC code to protect against these errors and allow the system to operate at signal levels about 8dB lower (more than doubling our range).

Bill, VK5DSP, has developed a rate 0.8 LDPC code designed for the packet length of our SSTV software (2064 bits/packet including checksum). This runs with the CML library – C software designed to be called from Matlab via the MEX file interface. I previously showed how the CML library can be used in GNU Octave.

I like to develop modem algorithms in GNU Octave, then port to C for real time operation. So I have put some time into developing Octave/C software to simulate the LDPC encoded FSK modem in Octave, then easily port exactly the same LDPC code to C. For example the write_code_to_C_include_file() Octave function generates a C header file with the code matrices and test vectors. There are test functions that use an Octave encoder and C decoder and compare the results to an Octave decoder. It’s carefully tested and bit exact to 64-bit double precision! Still a work in progress, but has been checked into codec2-dev SVN:

ldpc_fsk_lib.m Library of Octave functions to support LDPC over FSK modems
test_ldpc_fsk_lib.m Test and demo functions for Octave and C library code
mpdecode_core.c CML MpDecode.c LDPC decoder functions re-factored
H2064_516_sparse.h Sample C include file that describes Bill’s rate 0.8 code
ldpc_enc.c Command line LDPC encoder
ldpc_dec.c Command line LDPC decoder
drs232_ldpc.c Command line SSTV deframer and LDPC decoder

This software might be useful for others who want to use LDPC codes in their Matlab/Octave work, then run them in real time in C. With the (2064,512) code, the decoder runs at about 500 kbit/s on one core of my old laptop. I would also like to explore the use of these powerful codes in my HF Digital Voice work.

SSTV Hardware and Software

Mark did a fine job putting the system together and building the payload hardware and it’s enclosure:

It uses a Raspberry Pi, with a FSK modulator we drive from the Pi’s serial port. The camera aperture is just visible at the front. Mark has published the software here. The tx side is handled by a single Python script. Here is the impressive command line used to start the rx side running:

#!/bin/bash
# 
#	Start RX using a rtlsdr. 
# 
python rx_gui.py & 
rtl_sdr -s 1000000 -f 441000000 -g 35 - | csdr convert_u8_f | csdr bandpass_fir_fft_cc 0.1 0.4 0.05 | csdr fractional_decimator_ff 1.08331 | csdr realpart_cf | csdr convert_f_s16 | ./fsk_demod 2XS 8 923096 115387 - - S 2> >(python fskdemodgui.py --wide) | ./drs232_ldpc - - | python rx_ssdv.py --partialupdate 16

We have piped together a bunch of command line utilities on the Linux command line. A hardware analogy is a bunch of electronic boards on a work bench connected via coaxial jumper leads. It works quite well and allows us to easily prototype SDR radio systems on Linux machines from a laptop to a RPi. However down the track we need to get it all “in one box” – a single, cross platform executable anyone can run.

Next Steps

We did some initial tests with the LDPC decoder today but hit integration issues that flat lined our CPU. Next steps will be to investigate these issues and try LDPC encoded SSTV on the next flight, which is currently scheduled for the end of October. We would love to have some help with this work, e.g. optimizing and testing the software. Please let us know if you would like to help!

Links
Mark’s blog post on the flight
AREG blog post detailing the entire flight, including set up and recovery
High Speed Balloon Data Link – Development and Testing of the SSTV over FSK system
All your Modems are belong to Us – The origin of the “ideal” FSK demod used for this work.
FreeDV 2400A – The C version of this modem developed by Brady and used for VHF Digital Voice
LDPC using Octave and CML – using the CML library LDPC decoder in GNU Octave

SM2000 – Part 8 – Gippstech 2016 Presentation

Justin, VK7TW, has published a video of my SM2000 presentation at Gippstech, which was held in July 2016.

Brady O’Brien, KC9TPA, visited me in June. Together we brought the SM2000 up to the point where it is decoding FreeDV 2400A waveforms at 10.7MHz IF, which we demonstrate in this video. I’m currently busy with another project but will get back to the SM2000 (and other FreeDV projects) later this year.

Thanks Justin and Brady!

FreeDV and this video was also mentioned on this interesting Reddit post/debate from Gary KN4AQ on VHF/UHF Digital Voice – a peek into the future

Codec 2 Masking Model Part 5

In the last post in this series I was getting close to a fully quantised 700 bit/s codec. However as I pushed through I discovered a bug in the post-filter. I was accidentally cheating and using some of the encoder information in the decoder. When I corrected the bug the quality dropped significantly. I’ve hit these sorts of bugs before – the simulation code is complex and it’s easy to “declare victory” prematurely.

So I have abandoned the AbyS approach for now. Oh well, that’s “research and disappointment” for you. Plenty of new ideas though….

For the last few months I have been working on another solution that vector quantises a “fixed rate” version of the spectrum. The masking functions are still used to smooth the spectrum before sampling at the fixed rate. Much like we low pass filter time domain samples before sampling, the masking functions reduce the “bandwidth” and hence sample “rate” we need to represent the spectrum. Here is a block diagram of the current “700C” candidate codec:

The bit allocation is pitch (Wo) 6 bits, 1 bit for voicing, 16 bits for the amplitude VQ, 4 bits for energy and 1 bit spare. All updated every 40ms. The new work is in the “Decimate in Frequency” block, expanded here:

As the pitch of the speech varies, the number of harmonics used to represent the speech, L, varies. The goal is take a vector of L amplitude samples, vector quantise, and send them over a channel. To vector quantise them we need fixed length vectors. So a Discrete Fourier Transform (DFT) is used to resample the L amplitude samples to fixed vectors of length 20 (I have chosen k=10).

BTW a DFT is the generic form of a Fast Fourier Transform (FFT). A FFT is a computationally efficient (fast) way of computing a DFT.

The steps are similar to sampling a time domain signal. The bandwidth of the signal is limited by using the masking function to smooth the variations in the amplitude envelope. The use of masking functions means the smoothing matches the response of the ear, and no perceptually important information is lost.

I’ve recently been playing with OFDM modems, so I used a “cyclic suffix” to further smooth the DFT coefficients. DFTs like cyclic signals. If you have a DFT of an 8kHz signal, the sample at 3900Hz is the “close” to the sample at 0 Hz. If there is a step jump in amplitude – you get a lot of high frequency information in the DFT coefficients which is harder to quantise. So I throw away the last 500Hz of the speech signal (3500-4000 Hz), and replace it with a curve that ensures a smooth match between 3500 Hz and 0 Hz.

Yeah, I don’t know how I dream this stuff up either …… do I use the Force? Too much red wine or espresso? Experience? A life mispent on computers? Subconscious innovation? Plagiarism?

In the past I’ve tried to resample and VQ the spectrum of sinusoidal codecs a few times, without much success. Jean Marc also suggested something similar a few posts back. Anyhoo, getting somewhere this time around.

Here are some plots that show the algorithm in action for a frame of female speech:

Here are the amplitude samples (red crosses). The blue line has the cyclic suffix, note how it meets the first amplitude sample near 0Hz.

This figure shows the difference in the DFT coefficients with (blue) and without (green) the cyclic suffix:

Here is the cumulative energy of DFT coefficients, note that with the cyclic suffix (blue) low frequency energy dominates:

This figure shows a typical 2k=20 length vector that we vector quantise. Note it has zero mean – we extract the DC coefficient and separately quantise this as the frame energy.

Samples

Sample 1300 700C Candidate
hts1a Listen Listen
hts2a Listen Listen
forig Listen Listen
ve9qrp_10s Listen Listen
mmt1 Listen Listen
vkqi Listen Listen
cq_ref Listen Listen

Through a couple of years of on-air operation we have established that the 1300 bit/s codec (as used in FreeDV 1600 with 300 bit/s of FEC) has acceptable speech quality for HF. So the goal of this work is similar quality at 700 bit/s.

For some samples above (e.g. hts1a and mmt1a), 1300 is superior to the current 700C candidate. For others (e.g. hts2a and vk5qi) 700 sounds a little better. So I think I’m in the ball park.

There’s a bit of clipping at the start of cq_ref, and some level variations between the two modes on some samples. The 700C candidate has a few problems with unvoiced sounds, e.g. the intake of breath on ve9qrp_10, and the “ch” sound at the start of chicken in hts2a. Not sure why.

The cq_ref_1300 sample is a bit poor as the LPC technique used for spectral amplitudes falls over when the spectral dynamic range is high. In this sample the LF energy has much higher energy than the HF, i.e. a strong “Low Pass Filter” effect or spectral slope.

Next step is some refactoring – the Octave code is an untidy mess of 6 months of dead ends and false starts. A mirror of real world R&D I guess. Creating something new is not a tidy process. At least in my head. So many aspects of this algorithm that I could explore but I’d rather get this on the air and see if we really have something here. Would love to have some help with a port from Octave to C. Contact me if you’d like to work in this area.

SM2000 Part 7 – Prototype Ready for Manufacture

Rick, KA8BMA, has been working steadily on the CAD work for the SM2000 VHF Radio and the Rev A (prototype) PCB layout is now complete and ready for manufacture. Neil, VK5KA, an experienced RF Engineer, has been working with Rick on the PCB layout to ensure RF integrity. Thank you both for your fine work!

Here is the top layer of Rev A, which is 160mm x 160mm:

It’s a modular design, if you zoom in you can see the names of each module.

Edwin at Dragino is kindly assembling some prototypes for us, and I hope to start bringing up the board in early June.

Links

SM2000 Part 1 – Introducing the SM2000 project

SM2000 SVN – CAD Files for the project

FreeDV 2400A and 2400B Demos

Brady O’Brien, KC9TPA has put together a couple of videos demonstrating the new FreeDV VHF modes.

Here is a video demonstrating FreeDV 2400A, check out how well it performs next to analog FM:

The sample transmitted was generated using freedv_tx, audacity, and gnuradio (for FM modulation). The transmitting software was a gnuradio pipeline, to convert the 16 bit 48k short samples up to 4M 8bit hackrf samples. The HackRF was hooked straight up to j-pole antenna, about 25 feet in air. The power output was about 10mW.

Brady was 2.7 km away from the transmit site. On the receive end, a rtlsdr was connected to a 5/8 wave 2m antenna on his car. Software used on the receive end was gqrx, piped into freedv_rx over UDP, also recording a wav from which the DV and FM were later extracted.

Here is FreeDV 2400B, DV over a $50 commodity HT! This mode will run on any legacy FM analog radio, with roughly the same performance:

The transmitted sample was generated by freedv_tx and audacity. The TX rig was a yaesu FT-100, connected to a PC using a USB rigcat cable and isolated audio cable. The FT-100 was controlled by rigctl and hamlib, with 1W of transmit power. On the RX end, Brady was 3.8 km away. The UV-5R was configured with a SMA->BNC connector and MFJ magmount antenna. The UV-5R was interfaced to his laptop via a ‘kludge’ cable and USB audio interface.

Some errors can be heard in the decoded audio of this sample – we think the modem tones were clipping on the HT’s audio and introducing a few bit errors.

These new VHF modes are available in the FreeDV API and can be tested on the command line using freedv_tx and freedv_rx (example at the end of this post).

We would like to integrate FreeDV 2400B into the FreeDV GUI program and SM1000. It would be great to have some volunteers help with these tasks – please contact me if you can help!

FreeDV 2400A requires a SDR with a 5kHz RF bandwidth, and will be integrated into the SM2000 VHF radio.

Links

Modems for VHF Digital Voice
FreeDV 2400A
FreeDV 2016 Roadmap