This video is remarkable.
You’re hearing these words months, maybe years,
after I’ve spoken them, yet everything is as clear as if
we were sitting in the same room.
The ability to record and transmit different
kinds of information is a core part of modern
engineering – and the world as we know it.
That’s why some say we’re living in the
information age.
Whether you’re using your phone, turning on
the radio, or strumming your electric guitar, you’re
sending and receiving signals all the time.
And to get all that information where it needs
to go, you’ll need signal processing.
[Theme Music]
As an engineer, communicating means more than
having a chat in the break room.
Whether you’re watching YouTube videos, using
satellite navigation, or just making a phone call,
there’s communication happening.
Signals are representations of the information
we’re sending when we do this.
Text, sounds, images, and even computer files
will all be converted into a signal when you send them.
And that’s really what communication is,
sending stuff from one place to another to
convey information.
The basic task is to take content, turn it
into a signal, transmit it, and then turn it
all back into content on the other end.
These steps are known as signal processing.
The signal itself will be a current running
through a wire or an electromagnetic wave,
like radio or light.
However you choose to relay it, the overall
process is basically the same.
The problem of communicating remotely is one
engineers faced long before digital computers
came onto the scene.
We saw an example of this in the history of
electrical engineering, with Samuel Morse’s
1837 telegraph.
In his design, the operator pushed down a lever,
called a key, to complete a circuit and transmit an
electric current down a wire.
At the other end, a machine called a register
would receive that current and mark a piece
of paper.
By pressing down the key for different lengths of
time, the operator could make the register draw little
dots and dashes that spelled out a message.
The key and register in Morse’ telegraph
are both examples of what are called transducers.
Transducers take physical information, like
the operator’s press of the lever, and turn it
into a signal or vice versa.
To record this video, for example, the input
transducers were the microphone and the
camera I’m speaking to,
which measures the sound and light in this
environment and converted them to electrical
signals.
Watching the video involves output transducers,
things like your headphones and monitor.
Unlike Morse’ system, however, the signal
won’t stay in one form between transducers.
It might start out as an electric current
in the camera that gets converted into a file
on a memory card.
That’s transmitted again as a signal when we send
the file to a computer or upload it to the internet,
where it’s stored on YouTube’s servers.
At least, until you request that the signal
be sent to you in its final form, to be converted
back into light and sound.
Morse’s system was popular because it was simple
and remarkably easy to use, ushering in the era of
instant communication we enjoy today.
The ingenious part was finding a way to take
information as people understand it, in terms
of ordinary letters and words,
and encode it in a form that could be
transmitted as electricity.
Encoding is a key part of signal processing.
Signals need a transmission-friendly way of
representing the information you’re trying to relay.
A hundred years after Morse unveiled his telegraph, it
was replaced by more sophisticated and convenient
forms of communication, like telephones and radios.
But these methods – and everything up to
the internet today – are still based on encoding.
It’s the way the information is encoded
and how it’s transmitted that’s changed.
Consider radio waves, like the kind used to
transmit signals between your phone and a cell tower.
It’s the wave nature of radio that lets
your phone encode the information you need
to make a call.
Engineers design hardware that changes, or modulates,
the behavior of that wave to encode information about
the pressure of the air near the microphone –
in other words, the physical effects of sound.
Two of the most common ways of doing this
are Amplitude Modulation and Frequency Modulation,
or AM and FM – that’s where the names
on your radio dial come from!
One adjusts the amplitude, or strength of the wave,
while the other changes the frequency, or distance
between one peak and the next.
Much like telegraph signals, the transmitted
wave carries the information you want, which
is then decoded on the other side.
Similar methods can even represent sounds
and images, which is how television broadcasts
work.
But these methods have two pretty big limitations!
The first is capacity.
The signal of a radio wave can be thought
of as a combination of other, simpler waves
put together.
Specifically, you can represent a signal as
the sum of radio waves with different frequencies.
The range of different frequencies you can
represent is called the bandwidth,
and it limits how much information can be
encoded by your signal, as well as how many of
them can be sent at the same time.
Think of signals as fluids and radio channels
as pipes; the bandwidth is like the size of the pipe,
which controls how much fluid can flow at once.
The other problem is noise.
As they travel through the atmosphere, radio waves
interfere with each other and are warped by objects
in their path, which both cause distortions.
So the signal the other person receives usually
ends up pretty different from the one that you sent!
Noise is anything that changes your signal
from its original form, usually in a random way.
The greater the noise, the more distorted and
unrecognizable the received message will be.
That’s why old TV sets sometimes ended up
with ‘static’ in the image!
To go back to the pipe analogy, noise would
be any contamination the pipe puts into the
fluid, changing its concentration.
A tiny, contaminated pipe does a pretty terrible
job of delivering lots of clean water.
So as you can imagine, noisy channels with low
bandwidth aren’t great for sending signals that can
be reliably decoded on the receiving end.
Worse still, both of these problems happen
for wired communications as well.
The signal traveling down a wire is also a wave,
where the amplitude is represented by the the power
of the electric current at any given point in time.
That’s how we modulate electric currents to
carry signals, but it also means that those signals
suffer from noise and capacity issues, too.
Radio and wired communications faced these
sorts of problems during World War II,
which brought them to the attention of engineer
and mathematician Claude Shannon.
In 1948, he published A Mathematical
Theory of Communication,
which revolutionized how engineers
consider information itself, and what it
takes to send information reliably.
Among Shannon’s contributions was a mathematical
formula for determining the conditions needed for
sending a signal at a particular rate.
Imagine sending a Morse Code message down
a noisy wire.
Each segment of the code represents a dot or a
dash, what you might call a “bit” of the message.
“Bit” stands for “binary digit”, because
each part of our message only occupies one
of two states.
In his paper, Shannon developed a formula
that determines the number of bits you can
transmit per second, or “bit-rate” –
given the power of your signal, the amount
of noise, and the bandwidth of the channel.
When your internet provider advertises a speed
of 50 megabits per second, that’s Shannon’s bit rate!
He figured out that it’s the ratio of the
power of the signal to the power of the noise
that determines the bit rate.
So either the signal needs to be strong enough,
or the bandwidth needs to be large enough
for there to be so many frequencies representing
the signal that noise can’t affect them all at once.
As well as this handy formula, Shannon laid out
lots of groundwork for calculating the exact
conditions needed for reliable communication.
Just as importantly, he worked out what
kinds of signals you might need to represent
the information you’re trying to communicate.
That work would be vital once signal processing
entered the digital age.
Digital signals represent information using
a small set of distinct states rather than the
continuous variation of a wave.
Instead of FM radio, where changes in frequency
translate exactly to changes in sound,
digital radio sends the data piece by piece and
everything is reassembled on the receiving end.
Because the different states of the signal
can be more distinct, they’re much less
susceptible to noise.
A large difference is easier to distinguish
than a small one, even when it gets distorted.
Morse code, with its dots, dashes, and spaces,
was an early digital communication system.
But it would take the advent of computers
for digital signaling to really take off.
And it was Shannon’s work that allowed computer scientists and electrical engineers to find ways of encoding different kinds of information in terms of 1s and 0s – what we now call binary code.
Digital signals have come to form the basis
of computing, and every form of data associated
with it.
All of which are still used today!
Of course, we’ve only just skimmed the surface.
Signal processing overlaps with some serious
technical challenges.
There’s the task of actually encoding different sorts
of information as signals, and creating channels like
phone lines and WiFi routers to transmit them.
And there’s the challenge of building hardware
that transmits the final output, like computer
monitors and headphones.
But the end result is that you can stream
videos like this one at the click of a button,
virtually anywhere in the world.
I might be a little biased, but I think that
it’s pretty darn cool.
In this episode, we looked at the fundamentals
of signal processing.
We saw the need to represent information
as a signal so it can be transmitted, and an
example of that in Morse Code.
We explain how wired and wireless
communications can suffer from the problems
of bandwidth capacity and noise,
and how Claude Shannon helped quantify the
problem so that engineers could build around
those limitations and bring about the digital age.
Next time, we’re headed out to sea to talk
about moving physical objects with ships and
marine engineering.
Crash Course Engineering is produced in association
with PBS Digital Studios,
which also produces It's Okay To Be Smart, a show
about our curious universe and the science that makes
it possible, hosted by Dr. Joe Hanson.
Check it out at the link in the description.
Crash Course is a Complexly production and this
episode was filmed in the Doctor Cheryl C. Kinney
Studio with the help of these wonderful people.
And our amazing graphics team is Thought Cafe.
