K4 Predistortion planned? timetable?

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K4 Predistortion planned? timetable?

Robert Sands
Is the processor in the K4 fast or big enough to handle the demand of the
anticipated predistortion algorithm? Is this predistortion algorithm a
proprietary matter or is it constructed de novo from existing knowledge?
Any information on what is planned would be appreciated. Have not seen much
other than "later". Big attraction to me.
Robert
K7VO
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Robert Sands
K7VO
Olympia, WA
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Fwd: K4 Predistortion planned? timetable?

Robert Sands
Is this topic allowed? Original post did not come  through.

---------- Forwarded message ---------
From: Robert Sands <[hidden email]>
Date: Thu, Sep 10, 2020 at 10:57 AM
Subject: K4 Predistortion planned? timetable?
To: Elecraft Discussion List <[hidden email]>


Is the processor in the K4 fast or big enough to handle the demand of the
anticipated predistortion algorithm? Is this predistortion algorithm a
proprietary matter or is it constructed de novo from existing knowledge?
Any information on what is planned would be appreciated. Have not seen much
other than "later". Big attraction to me.
Robert
K7VO
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Robert Sands
K7VO
Olympia, WA
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Re: K4 Predistortion planned? timetable?

wayne burdick
Administrator
> Robert Sands <[hidden email]> wrote:
>
> Is the processor in the K4 fast or big enough to handle the demand of the anticipated predistortion algorithm?

Yes. Modulation and demodulation is handled by a dedicated, very fast floating-point DSP with various on-chip accelerators. The panadapters run from separate hardware, so the DSP has plenty of cycles to burn, especially in transmit mode.


> Is this predistortion algorithm a proprietary matter or is it constructed de novo from existing knowledge?

There are three parts to this.

First you need the appropriate hardware paths, which we already have in place: RF sampling of the reference waveform as well as the internal or external transmit signal.

Second, the DSP has to apply complex curve fitting at baseband. This is typically done with several terms of a Volterra series, etc.

Finally you need an algorithm for adaptive convergence on the ideal coefficients. This can range from LMS (least-mean-squares) to back-propagation (neural net). This is the "fun" (time consuming) part of the R&D, with tradeoffs in performance vs. processing time vs. staff availability. Given the multitude of distractions I can't say exactly how long this will take. It's likely that a simpler version of the algorithm will be available initially, allowing for early evaluation.

73,
Wayne
N6KR
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Re: K4 Predistortion planned? timetable?

Doug Turnbull

Wayne and friends, This recent correspondence is one of the reasons why I value Elecraft.   The design engineers come down to their users and give insight.   It was the right decision to plonk down that deposit.The smoke will clear and Elecraft will be in the California sun; there is reason for naming it the golden state.   I pray you are left with plenty of forest for your hikes.73 Doug EI2CNSent from my Samsung Galaxy smartphone.
-------- Original message --------From: Wayne Burdick <[hidden email]> Date: 13/09/2020  18:42  (GMT+00:00) To: Robert Sands <[hidden email]> Cc: Elecraft Reflector <[hidden email]> Subject: Re: [Elecraft] K4 Predistortion planned? timetable? > Robert Sands <[hidden email]> wrote:> > Is the processor in the K4 fast or big enough to handle the demand of the anticipated predistortion algorithm?Yes. Modulation and demodulation is handled by a dedicated, very fast floating-point DSP with various on-chip accelerators. The panadapters run from separate hardware, so the DSP has plenty of cycles to burn, especially in transmit mode.> Is this predistortion algorithm a proprietary matter or is it constructed de novo from existing knowledge?There are three parts to this. First you need the appropriate hardware paths, which we already have in place: RF sampling of the reference waveform as well as the internal or external transmit signal. Second, the DSP has to apply complex curve fitting at baseband. This is typically done with several terms of a Volterra series, etc.Finally you need an algorithm for adaptive convergence on the ideal coefficients. This can range from LMS (least-mean-squares) to back-propagation (neural net). This is the "fun" (time consuming) part of the R&D, with tradeoffs in performance vs. processing time vs. staff availability. Given the multitude of distractions I can't say exactly how long this will take. It's likely that a simpler version of the algorithm will be available initially, allowing for early evaluation.73,WayneN6KR______________________________________________________________Elecraft mailing listHome: http://mailman.qth.net/mailman/listinfo/elecraftHelp: http://mailman.qth.net/mmfaq.htmPost: mailto:[hidden email] list hosted by: http://www.qsl.netPlease help support this email list: http://www.qsl.net/donate.htmlMessage delivered to [hidden email]
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