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34
bibliography.bib
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@ -1,10 +1,26 @@
@article{testy,
title={Citation analysis},
author={Nicolaisen, Jeppe},
journal={Annual review of information science and technology},
volume={41},
number={1},
pages={609--641},
year={2007},
publisher={Wiley Subscription Services, Inc., A Wiley Company Hoboken}
@ARTICLE{shannon,
author={Shannon, C.E.},
journal={Proceedings of the IEEE},
title={Communication In The Presence Of Noise},
year={1998},
volume={86},
number={2},
pages={447-457},
keywords={Acoustic noise;Distortion;Telegraphy;Telephony;Communication systems;Bandwidth;Radio transmitters;Signal processing;Signal mapping;Teleprinting},
doi={10.1109/JPROC.1998.659497}}
@BOOK{huffman,
author={Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein},
title={Introduction to Algorithms},
volume={2},
year={2001},
pages={385-392},
isbn={0-262-03293-7}
}
@article{modulation,
title={Principles of digital modulation},
author={Fitton, Mike},
journal={URL http://www. berk. tc/combas/digital\_mod. pdf},
year={2002}
}

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main.typ
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#set page(
paper: "a4",
numbering: "-1-",
numbering: "1",
margin: (top: 2.5cm, left: 2.5cm, right: 2.5cm, bottom: 2cm)
)
@ -16,7 +16,7 @@ Process Essay\
May 17th, 2025
#align(center, text(size: 17pt, weight: "bold")[
*Around the world in 133 ms*
*The Digital Journey of Your Voice*
])
#set align(left)
@ -29,39 +29,67 @@ May 17th, 2025
#show: word-count
Have you ever wondered what really happens with your voice when you talking to someone on the phone?
Have you ever wondered what happens with your voice when you are talking to someone on the phone?
From the instant the soundwaves leave your throat until they reach the ear of the person you are talking to,
a series of analog and digital processes collaborate to carry your message.
In fact, this whole process can be broken down into three major steps -- sampling, quantisation and modulation.
In the course of this essay, we will investigate each of these steps in more depth to understand how modern
communication works on a technical level.
//To understand how we communicate across the globe on a technical level, we begin with the most primitive
//instrument of all: the human voice.
In the sampling process, an analogue signal is transformed into its digital representation.
This signal can be interpreted as any kind of waveform or motion that has not been processed by
a digital device yet.
For example, the sound of your voice or the tone of a guitar string is a suiting type of signal that we
want to digitize.
However, a digital device like a computer or a phone cannot unterstand such an analogue signal, thus we have
to first convert it into some kind of electrical signal the device can unterstand.
We can achieve that by taking repeated "snapshots" of the current state of the analogue signal and saving
the corresponding value.
The resulting signal is now so called "time discreet", because we went from a continuous signal that has a value
for every imaginable point in time to one where such values only exist at fixed, predefined points in time
(i.e. every second).
Going on, we now have a signal that consists of repeated snapshots of the originating signal where each value
can still be considered as continuous
To start, we will take a closer look at the analoue signal that reaches your phone's microphone.
Every sound wave, like your voice or the tone of a guitar string, is so called time and value continuous.
That means, such a signal has an infinitely accurate value at each imaginable point in time.
However, an electronic device, for example a computer or a phone, cannot understand such an analogue signal, thus we have to first transform it into some kind of electrical signal the device can understand.
In general, we can assume that an electrical device can only process time and value disteet signals.
To transform our original continuous signal into its discreet or rather digital representation, we can make use of the sampling and
quantization steps in our communication process.
//To see how sampling works, we start with the sounds you make when you speak -- combinations of multiple sound waves at varying frequencies.
/*For our purposes, however, we can simplify this complexity by modeling your voice as a single
continuous sine wave, since this idealization does not affect the sampling process.
Furthermore, we can think of this sine wave as the very first input into our communication pipeline.
With the analogue signal established, we can go on and discuss the way our signal is transformed into a digital
representation.
*/
In the sampling process, the analogue signal is transformet into a time discreet and value continuous signal.
Conceptually, an analog-to-digital converter (ADC) takes rapid "snapshots" of the amplitude of the input signal at uniform intervals and records each reading.
The rate at which these snapshots occur is called sampling frequency.
Ideally, we do want to maximize the timespan between each of these snapshots, using the lowest possible sampling frequency so to speak.
The Nyquist Frequency defines this lowest possible sampling frequency as double the frequency of the originating signal @shannon.
For example, if the frequency of our original signal is 1 MHz, the analog-to-digital converter will need to take a snapshot of the signal at a frequency of at least 2 MHz.
At this moment, our signal now is time-discreet and value-continuous.
To convert these time-discreet values into real bits and bytes we will make use of the quantizer in the next step.
Essay has a total of #total-words words.
Quanization describes the operation of transforming a continuous value into a discreet form.
Imagine placing random dots in a row on a piece of paper.
A simple quantization process now would be to take a ruler and for each point record which is the next highest marking on the ruler.
In the same sense, the quantizer of an electronic device maps the continuous input vaulues to predefined codewords -- a collection of bits (for example "000", "110" or "011").
Our signal has now fully arrived in the digital domain.
// Note: Maybe expand more what happened up until now
Up to this point we have completeley encoded our analogue message digitally.
During the next steps, the digital signal will be further processed and prepared for transmission.
A digital signal in its raw form is very inefficient to transmit because of the limited underlying bandwidth.
Because we need to transport our message over some kind of communication channel, the amount of information we can transport in a fixed period of time is limited.
The first step in solving this issue is using compression by removing irrelevant and redundant information from the signal.
A popular example for a compression method is called Huffman Coding @huffman.
Conceptually, the Huffman Code consists of multiple codewords of varying length where symbols with a higher probability of occurrence are assigned to the shorter codewords, thus reducing the overall size of the message.
Since the assignment of symbols to codewords is based on their probability of occurrence, this method of compression requires information about the statistics of the incoming symbols.
If these statistical information are not known, other compression methods such as the Lempel–Ziv–Welch algorithm can be used.
Furtheremore, compression algorithms specifically tailored for different signal sources can be used, for example PNG for pictures, MP3 for audio or MPEG for video signals.
With the analogue message digizited and compressed for easier transport over our communication channel, we will now need to prepare our message on a physical level for it to be able to be transmitted using a radio wave or a data cable.
Currently, the message to be transmitted can be represented as a set of codewords like "00 01 10 11".
To prepare our message digital and compressed message for transmission over a physical channel, digital modulation -- like amplitude modulation -- is used.
This works by defining a specific signal amplitude for every possible codeword, which is called Amplitude-Shift Keying (ASK) @modulation.
The simplest form of ASK is called On-Off Keying (OOK), where we will either transmit a wave -- and signaling a binary 1 -- or not transmit anything -- and signal a 0.
In our example we may define four sine functions with varying amplitutes as the modulated signal that is being transported over the physical communication channel.
Because we defined four different Amplitude-Shifts, this type of modulation is called "4 ASK" @modulation.
Signal modulation is not limited to changing the ampliude of our transmission signal, thus we can also alter the phase or frequency of the signal.
Depending on the type of communication channel we may want to choose a different modulation type using either one or a combination of different modulation parameters.
For example, a popular modulation type that uses a combination of amplitude shifts and phase shifts is called "Amplitude-Phase-Shift Keying (APSK) @modulation.
Using modulation, we prepared our signal on a physical level to instruct a communication interface -- like an antenna or an optical transmitter -- to finally transmit our message.
As final step, the receiver of the message has to process the received signals in exactly the reverse order to create a comprehensible message.
The most important prerequisite for this to work is that both sender and receiver have agreed on the same transmission and reception conditions.
The receiver will first need to use the correct modulation type to convert their received signal back to a set of codewords.
Going on, they will decompress the message based on the used compression algorithm and use a Digital-to-Analog Converter (DAC) to transform the digital message back into sound waves which will be output by the speaker of their phone.
This whole process now happens at such a high speed that makes it possible for us to talk to a person on the other side of the world.
//Essay has a total of #total-words words.
#pagebreak()