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Re: Are the uBITX receivers ripe for improvement? -- And some other miscellaneous thoughts.

 

I don't see a way to re-edit a post, so here it is again, I hope, in an easier to read font. It looks like the issue is with writing in another editor and pasting that into the on-line editor here.

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I see a lot of good conversations here about improving the uBITX transmitter output. However, I see very little about how good the receiver is. My question is, have many people done comparisons of the uBITX receiver vs their other radios; particularly on SSB?

In my case I have noticed that my SDR using a cheap dongle seems to outperform the uBITX receiver substantially. Even though I don¡¯t consider the SDR dongles to be the pinnacle of RF design, I guess throwing brute force real time math at the receiver side makes up for some of it.

Are the uBITX receivers ripe for improvement?


Additional miscellaneous thoughts:

Rather than cutting up the uBITX or trying to cram more software into the one Arduino Nano on the uBITX I was pondering running multiple Nano¡¯s communicating on the I2C bus. They are only about $3.50 apiece. (The 3.3v bus [albeit barely] is in spec for the Nano.)?

But, rather than cutting up the radio I think I¡¯d rather simply treat the uBITX as a peripheral to a Raspberry Pi. I¡¯d place the Pi (and USB audio adaptors) in a metal box packaged in the same case as the uBITX.

What I¡¯d do with the Pi is:?

  1. Process and level the microphone audio for transmitting.

  2. Process, level and noise filter the receive audio, as well use a DSP library to add bandpass and notch filters.

  3. Use one of the digital mode libraries for digital mode communication.?

  4. Maybe get rid of the T/R audio pop while processing the receive audio.?

  5. Control other gizmos I may add to the transceiver.

  6. Put a fancy touch screen display on the whole thing.

Additionally, I¡¯m doing a literature search to see what work has been done on training Neural Nets to decode Morse Code. It would seem that a technology that can identify people, dogs and cats from low resolution photos (although there was a study that found AI could mistake pictures of muffins for chihuahuas), could finally realize an adaptable, reliable CW decoder. (This would run on the Pi, also).

I¡¯m sure others must be working on the same things. Anyone know about such projects. That would save time over starting from scratch.

Tom, wb6b
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