In the analogue world you throw up an antenna, turn on your radio, tune to a station and sound comes out. Aside from propagation restrictions, you don’t particularly care when you do this. In contrast, if you fire up a WSPR or Weak Signal Propagation Reporter, each transmission lasts 110.6 seconds, every 120 seconds, starting on the even minute. An FT8 signal takes 12.6 seconds within a 15 second window. In other words, to use WSPR or FT8 you need to both transmit and receive at the right time for this to work.

You don’t need to go to modern modes to get the idea that time matters.

Listening to any CW signal will give you an idea that time and timing is important. To give you a sense of what I mean, if you turn on your radio in the middle of a dah, in the middle of a letter, you’re likely to hear the wrong symbol, perhaps decoding the partial dah as a dit and missing the first part, hearing a partial letter Q, dah dah dit dah as a dit dit dah, the letter U, and that is completely ignoring inter letter and inter word spacing.

The point being that time matters for radio signals.

So, if we’re going to build a system that can handle radio signals inside a computer, we’ll need to deal with time.

Decoding is one thing, but what if you want to compare two radio signals from two different antennas? You can build a direction finding tool consisting of multiple antennas that can determine the direction of a signal by calculating the difference in time between when a signal arrived at one antenna and when it arrived at another. Of course, the distance between each antenna matters, so we’d need to deal with time in such a way that we can actually measure this. RF travels about 30 centimetres in a nanosecond.

If that’s not enough, what happens if you’re digitising an analogue signal and sending it across the network to be processed? Not only do you need to track if information arrived at its destination or was lost in transit, if you’re combining multiple signals, you’ll also need to know when the information was captured.

Which brings us to something entirely different and perhaps surprising. If I say “now”, that moment is not the same for everybody on the planet. You might be listening to this on the train to work, your local repeater, on YouTube, or reading it on social media or in your email. Even me writing the word and reading it out loud are two different times.

In other words, agreeing on time is not obvious.

We could all look at the clock and share the information, but is that accurate enough? Do we tell each other how many seconds past midnight UTC, or do we need to know half or tenths of seconds? To use WSPR and FT8 it’s generally enough to use the NTP or Network Time Protocol. It can be as accurate as 1 millisecond, but is that enough?

To give you a sense of how precise we might need to be, a HF signal takes about 66 milliseconds to travel halfway around the globe. A mobile phone tower signal travels 6 kilometres in about 0.02 milliseconds, so NTP isn’t really precise enough for what we might need.

If you’ve played with a GPS, you might know that you can use it to determine when “now” is. It’s theoretically capable of a 14 nanosecond accuracy, but by the time you actually use it, it’s more like 100 nanoseconds.

There’s a million nanoseconds in a millisecond and a billion nanoseconds in a second. If you were to store nanoseconds as a 64-bit unsigned number, you could count between now and just over 584 years from now.

Something else to consider. If you had two analogue to digital converters and you wanted to synchronise them, 1 nanosecond would allow you to get two 1 GHz signals to start at the same time, providing that you knew what time it was to that level of accuracy. If you’re keen, look up maser.

Before you point out that this means we’d be limited to anything below the 23cm band at 1.2 GHz, I’d like to mention that this is about representing all of it, 0 Hz to 1 GHz as one chunk of spectrum at the same time. In reality, you’re much more likely to only want part of that, not to mention that we’d need to transport and process all that data as well.

Which brings us to bandwidth considerations, but that’s a conversation for another time.

Credit to Nick VA3NNW, Kent AC1HJ, Dave VK6KV and Randall VK6WR for their thoughts and explanations. Any mistakes are all mine, feel free to point them out.

I’m Onno VK6FLAB