Understanding Cell Phone Technology: Analog and Digital Signals

Since the invention of the telegraph, people have been transmitting messages using electrical signals. In early telegraph and telephone systems, the electrical signals traveled over physical wires. Over time, inventors found ways to harness the radio frequencies of the electromagnetic (EM) spectrum for wireless telegraphic and telephonic communications.

The invented words –  “telegraph” and “telephone” – reflected the important functionality delivered by these new technologies. The Greek prefix of these words, “telē”, means far. The terminating part of telegraph comes from the Greek word, “graphein”, meaning to write.  Telephone ends with “phōnē”, meaning “voice, sound”. Telegraphy and telephony suddenly allowed people to write and speak at a distance.

Let’s consider speech. Speech is an analog signal, a continuous wave constantly varying in amplitude, frequency and phase. If you want to see your speech as squiggly waves in the time domain,  or as an envelope in the frequency domain, you can use the oscilloscope and spectrum analyzer in the Physics Toolbox Sensor Suite app (https://www.vieyrasoftware.net/). Note that the app transforms the original time domain signal into the frequency domain using the Fast Fourier Transform (FFT). In case you missed it, I talked about the FFT in this blog on 22 June 2020.

Besides analog signals, there are also digital signals. A digital signal contains individual samples at discrete levels. For example, the discrete levels can just be 0’s and 1’s, in which case we call it a binary system, and the message looks like a bit stream

01010100 01101000 01101001 01110011 00100000 01101001 01110011 00100000 01110100 01101000 01100101 00100000 01110100 01101001 01101101 01100101 00100000 01100110 01101111 01110010 00100000 01100001 01101100 01101100 00100000 01100111 01101111

You can try out converting a text string to a binary string at this website: http://www.unit-conversion.info/texttools/convert-text-to-binary/#data

Another digital system, familiar to computer science types, uses sixteen discrete levels. That system is called hexadecimal, and a stream of it looks like

4e 6f 77 20 69 73 20 74 68 65 20 74 69 6d 65 20 66 6f 72 20 61 6c 6c 20 67 6f 6f 64 20 6d 65 6e 20 74 6f 20 63 6f 6d 65 20 74 6f 20 74 68 65 20 61 69 64 20 6f 66 20 74 68 65 69 72 20 70 61 72 74 79 2e 0d 0a

Modern communications systems require the signals to be presented to most of their components as digital signals. They are able to digest analog signal inputs, like speech and music, by converting the original signal from analog to digital (A/D) at the source. These digital messages are converted back from digital to analog (D/A) at the destination.

A/D conversion is accomplished in two steps. First the signal is sampled (sampling), then it is assigned to a discrete level (quantization). Neither sampling theory nor quantization theory are trivial subjects. For example, Claude Shannon proved in the 1940’s that signal sampling must be performed at at least twice the width of the signal’s frequency envelope in order to preserve all the information content. Over the decades, different types of quantization have been devised to take advantage of the characteristics of the signal and the channel over which it travels. You can get your feet wet with these ideas here:

https://courses.engr.illinois.edu/ece110/fa2020/content/courseNotes/files/?samplingAndQuantization

So let’s review what we’ve learned today:

1.     People like to communicate, using speech and text (and today, video).

2.     Telegraphy and telephony allowed people to communicate at a distance using text and speech.

3.     Speech is an analog signal, a continuous signal constantly varying in amplitude, frequency and phase.

4.     A digital signal is not analog; it is composed of individual samples at discrete levels.

5.     Modern communications systems use digital signals, so analog inputs must be converted to the digital domain using sampling and quantization.

Why, you ask, do modern communications systems prefer to handle the data digitally? Because it allows them to achieve higher data rates across limited bandwidth. This is a set of ideas we’ll investigate much more thoroughly in the coming weeks.