The Secret Life of Modern RF Signals - Part 2
If you’ve ever spent time discussing electromagnetic (EM) fields as an undergrad, you may not have thought of EM as a simple topic… the math looked impressive and the concepts were new. But unless you specialized in wireless, the discussion of fields most of us saw was pretty cursory. It was tough enough getting our heads around Maxwell’s equations without involving any seriously realistic field scenarios. Most of us learned enough about fields to move on to transmission line theory, which is where we had our first real exposure to the nature of reflecting signals.
The real world, of course, is not made up of point charges in infinitely empty space. In the real world, any EM field reflects off of nearby surfaces. If you think about it for a second, the simplest case involving a transmitter, receiver, and reflector is fairly complex. Even if you assume that one antenna transmits a sinusoid with a perfectly spherical transmission pattern, that the reflective surface is stationary and flat, you can imagine that the signal that as seen by the receive antenna is pretty complicated. It is the sum of an infinite number of sinusoids, each delayed by a different amount (due to the differing distances traversed) and with different attenuation.
The phase differences caused by delays can be constructive or destructive. An analogy in wired technologies is the existence of stubs which create reflections on the transmission line, for example unterminated taps in a cable modem system. Assuming no attenuation, if the phase difference between two sinusoids is between 120° and 240°, the amplitude of their sum is smaller than the amplitude of either of the two original sine waves; outside of this band signals add constructively (here we’re talking about amplitude only, ignoring the phase of the resultant signal). Since propagation speed is fixed, phase difference is a function of frequency. If you take a band-limited channel, add a delayed copy of itself to the original, and look at the output on a spectrum analyzer, the resultant signal looks like the teeth of a comb… alternating attenuated and intensified frequencies.
In wireless there are other variables. In the first place, the environment changes in time… even when the user is not moving, reflective objects do. Cars, trucks, and even trees moving in the wind affect the user’s signal. This time-varying environment continuously create frequency-specific losses, and these are what we call “fading”.
This raises an interesting question: intuitively the nature of fading is such that there is not a lot of predictability involved. Still, you need repeatability in the test lab. So, how random does “random” need to be, and how do you get it without giving up the stability required for DVT, debugging, firmware development and testing? For the answer, look for the next installment of this blog.