How is Data Sent? An Overview of Digital Communications
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- เผยแพร่เมื่อ 28 ส.ค. 2021
- Explains how Digital Communications works to turn data (ones and zeros) into a signal that can be sent over a communications channel. Gives basic examples for optical fibres, wireless and mobile communications, as well as an example of data compression and error control coding.
* Note that there is a minor "typo" near the end, where I wrote "19 bits" when it should have been "18 bits". I've fixed it on the summary sheet: drive.google.com/file/d/1q9FN...
Related videos: (see iaincollings.com)
• How is Data Received? An Overview of Digital Communications • How is Data Received? ...
• How are Data Rate and Bandwidth Related? • How are Data Rate and ...
• How are Throughput, Bandwidth, and Data Rate Related? • How are Throughput, Ba...
• How are Bit Error Rate (BER) and Symbol Error Rate (SER) Related? • How are Bit Error Rate...
• What are Channel Capacity and Code Rate? • What are Channel Capac...
• What is Entropy? and its relation to Compression • What is Entropy? and i...
• What is Pulse Shaping and the Square Root Raised Cosine? • Pulse Shaping and Squa...
Full Categorised list of videos and PDF Summary Sheets: iaincollings.com
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Clear and specific!!! There is so much attention to detail in what is taught in my university that I am confused about the overall flow🤣Until today I did not know that digital baseband coding and digital bandpass coding are both channel coding(I've mistaken baseband coding such as HDB3 as source coding before....) Thanks for your explanation! 😊
I'm so glad you found the video useful.
11111111 (2) = 255. We can add 1 since we would never transmit a "non-bit"... Just in case anyone else was confused by this. Excellent video. I'm hooked on your clear explanations. I work with electrical engineering concepts but never was able to take the necessary coursework - thank you for helping fill my knowledge gap!
That's great to hear. I'm so glad the videos are helpful to you.
A great source of information for anyone interested in communication systems
These videos are very simply well done, clear and complete. Really usefull, thanks a lot!!!
Glad you like them!
Awesome! I finallly understood the redundancy part of MCS index!
Glad it helped!
The best video! This clarifies all my doubts! Thanks a lot sir!
Glad you found it useful.
It is amazing what you do with just a pen and paper. This was very helpful! Thanks
Glad you found it helpful!
Superbly explained 👏👏
Thank you! 🙇♂
You're welcome 😊
Why I'm so late to find this amazing channel. Amazing lecture. I subscribed this channel. Thanks God. 🙏
Welcome! I'm glad you like the videos.
This is an excellent high level view of information transmission over a channel, with valuable insights in each operation. The hints for further investigation in concepts like capacity, entropy, etc. are also great.
Just a question: in source encoding the number of compressed bits are 18 (1+8 for white pixels and 1+8 for black pixels) and not 19, right?
Yes, sorry about that. I have a note in the description below the video about it. Unfortunately I'm not able to re-upload an edited version of the video to correct it. Thanks.
Excellent! Thanks for sharing your vast knowledge
Glad it was helpful!
Great presentation! Thank you.
Glad it was helpful!
Great explanation!
I'm glad you liked it.
You are a great teacher really
Thanks. I'm glad you like the video.
Thank you so much for your good explaination👌
You are welcome 😊
Perfect explanation.
Glad you liked it.
Super helpful ! Thank you very much
Glad it was helpful!
Thank you for your time and effort
My pleasure! I'm glad the videos are helping.
great video as usual
Glad you enjoyed it
These are the basics of whole digital communication system
you are amazing! Thank you so much!
You're so welcome!
Dear Professor, can you please share some articles/pdf links for the Detailed RF transceiver chain in wireless?
Excellent. Thank you.
How do I STOP the radio frequency channel when I am the receiver? There is a radio frequency integrated mesh harness on my head, and and I have a digital oscillating sequence system being put into my body, WITHOUT MY CONSENT
Thanks Prof. Collings, for all the videos you post which help me understand everything related to the physical layer of wireless communication!
I have one question: If I consider encryption of the payload as an additional process, where does it fit into the diagram with respect to source coding? Is the original data being source coded before encryption, or does source coding happen after encryption? Would source coding even make sense when data is already encrypted, since there may be limited compression performance? My current view is that the original data is encrypted at the application layer whereas all processes in your diagram happen at the physical layer (including source coding which seem to be of limited benefit when performed on an encrypted payload).
Source coding occurs in the higher layers. For example, a voice codec is a version of a source coder. It digitises the analog signal, and does so in a way that tries to minimise the amount of data required to be stored/sent, while maintaining a given allowable level of distortion in the reconstructed signal. And this can be done in video processing software (application layer). Encryption is applied to the digital signal that is to be sent (ie. after source coding has been done).
Your digital communication video is amazing! Thank you sir! How about a video for a receiving end of the digital communication? This addition will conclude your concise and easily explained video.
Great suggestion. I've put it on my "to do" list.
Good to hear you agree!
EXCELLENT.❤❤
Glad you liked it.
Really good very high level video. A slightly more in-depth explanation of the relationship between the baseband and the carrier band would have been instructional and filled in a knowledge gap.
Glad you liked the video. Perhaps this video might help to give more insight between the baseband and the carrier band, through the examples of DSL (baseband) and OFDM (carrier/pass band): "How are OFDM and xDSL (DMT) Related?" th-cam.com/video/CET2UuGeEqs/w-d-xo.html
Hi Jeff, I've just published a video on this topic, which will hopefully help: "What is a Baseband Equivalent Signal in Communications?" th-cam.com/video/etZARaMNN2s/w-d-xo.html
@@iain_explains Thanks for the videos. helps to brush off the rust.
love your tiny letters and your hand..so satisfying..
Thank you so much 😀
Excellent video. Thanks sir for this sharing. I have a question on the gif image examples. Why we have 19bits after coding instead of 18 bits (2 times 8 bits (16 bits) + 2 bits (0 and 1) ?
Yes, sorry, that was a "typo". I updated it on the summary sheet. drive.google.com/file/d/1q9FNbYawaMqujNh1NkrI8uSn3GM59Utj/view
thank you!
You're welcome!
As nice as always!!Sir can you add to your list about Baseband representation of passband signal....
Thanks for the suggestion. I've had it on my "to do" list, but I've just moved it up the priority order.
I've just published a video on this topic, which will hopefully help: "What is a Baseband Equivalent Signal in Communications?" th-cam.com/video/etZARaMNN2s/w-d-xo.html
Thank you very much!!Please keep up the noble work
Hi Lain,
I saw somewhere
"New channel coding schemes like low⁃density parity check (LDPC) and polar codes can extremely reduce the decoding complexity for scenarios with large block sizes and/or high coding rates. Also, it can improve the performance of those with short block sizes. Moreover, a lot of processing power of a receiver is consumed by the decoding of channel codes."
My questions are:
1) What is the relation of complexity with block sizes and high coding rates? If I understand correctly, higher coding rate means more information bits and less correction bits which can increase the decoding complexity, right?
then, "The design and specification for URLLC are enabled by fast decoding. With the super⁃wide bandwidth foreseen for 5G up to 1 GHz, channel codes efficient for large block sizes become a must, not an option. the frame structure of NR without it will be only a hollow place holder."
My question is:
How larger block size is linked to bandwidth as indicated in the above?
For question 1) : Information Theory tells us that the way to achieve the maximum possible error-free rate, is to use long codewords. In practice, there are a number of ways to achieve codes that are effectively the same as having long block lengths - and in general these have high complexity to implement. For your second question: The wider the bandwidth, the higher the maximum possible rate. This doesn't necessarily mean the codewords need to be any longer though. The key for URLLC is to have the shortest codewords possible, subject to stringent BER requirements, so that there is the smallest possible latency.
Can we make the clock signal with just coding in embedded C? Directly just through code, controlling voltage on any gpio pins of uC?
Sure. Just change the voltage between two levels on a regular time period. Of course it will only be able to switch as fast as that output pin can change its voltage.
sir is it not possible to improve our SNR at the receiver by using a low noise amplifier until such extent so that we need not have to use channel coding because channel coding is anyhow decoding the error caused due to noise and sir also we are using the regenerative repeater to increase the strength of the signal
Certainly it is good to use a receiver amplifier with a low noise figure, but truely "low noise" amplifiers require cryogenic cooling (eg. the ones used in radio astronomy), so they are expensive and impractical for most communication systems. Unless you are operating at 0 deg Kelvin, then there will be "noise" in the received signal.
hello lain, first of all thanks for the video i have a question
channel coding is done to prevent what shorts of error means what damage can a channel do to our transmitted signal could you please explain it in breif
The channel can distort the signal in such a way that the receiver thinks a digital "1" was sent when actually a digital "0" was sent, and vice versa. This can happen randomly, based on time variations in the channel, and noise in the receiver electronics. Coding is needed to try to correct these errors.
Hey professor, I have a question regarding Decimation and interpolation in a sense of bandwidth. I have your videos about these topics, but I still haven't managed to understand how the operation od up/down sampling influences the bandwidth. In Decimation, you get an expanded spectrum when each value of theta is multiplied by the decimation factor. What I get from that is that the bandwidth increases (=this expansion that I mentioned earlier?), but it doesn't make sense because when applying decimation, you get a new discrete signal which has less components than the previous one, hence less frequency components. Once again, I am bot sure, and would some clarification.
Thanks in advance!
Great question. The answer lies in the difference between the DTFT and the DFT. You said that "when applying decimation, you get a new discrete signal which has less components than the previous one, hence less frequency components." ... it's only fewer frequency components, if you're talking about the DFT. Note that the DFT has a discrete frequency transform, whereas the DTFT has a continuous frequency transform. And yes, the DFT of a decimated discrete-time signal, is a shorter vector, but the length of the vector is only part of the story. The frequency gap between the elements of the DFT vector also needs to be considered/understood. Hopefully these videos will help: "How are the Fourier Series, Fourier Transform, DTFT, DFT, FFT, LT and ZT Related?" th-cam.com/video/2kMSLqAbLj4/w-d-xo.html and "How does the Discrete Fourier Transform DFT relate to Real Frequencies?" th-cam.com/video/pIFz84oj9cA/w-d-xo.html
@@iain_explains thanks for the quick response!
I have watched the videos, and I have a question: if the gap/spacing and between the dft samples in defined as Fsamp/N , so when implementing decimation you reduce the value of Fsamp, but also you effectively change the value of N because now the vector of the samples is smaller (-> N is smaller). In this scenario, how does the gap/sapcing change because you reduce the values of both the numerator and denominator of the expression. That's what doesn't make sense to me- how is the gap related to my original question considering what I have just mentioned (if I wrote some incorrect things, please let me know 🙏)
Thanks again!
Maybe this video will help: "Discrete Time Sampling Example" th-cam.com/video/vGxvrq5kCzQ/w-d-xo.html
@@iain_explains I have watched the video you recommended. It explains well how decimation influences the DTFT spectrum, but not quite the DFT spectrum. I still don't get the idea of how the bandwidth is affected by implementing decimation or even interpolation. If you can recommend me another video or a lecture that I can watch which will help me understand this topic, it will be much appreciated!
Thanks a lot!
Perhaps try these: "How does the Discrete Fourier Transform DFT relate to Real Frequencies?" th-cam.com/video/pIFz84oj9cA/w-d-xo.html and "How do the Frequency, Sample Rate and Duration affect the DFT of a Sinusoid?" th-cam.com/video/5diC6XLLVoA/w-d-xo.html and "Discrete / Fast Fourier Transform DFT / FFT of a Sinusoid Signal" th-cam.com/video/lwQTNcWtN7w/w-d-xo.html
@ Iain Explains Signals, Systems, and Digital Comms DAC is also called as Line coding ?
Partly yes. "Line Coding" is a term that refers to digital baseband modulation.
@@iain_explains thanks...Not sure what makes it partly though..Why not fully ?
Well it's not just the DAC. It matters what you put into the DAC, so a "line coder" would include a function to generate the "digital" waveform, and then a DAC to make the waveform continuous time.
@@iain_explains thanks. Clear
@@iain_explains I came back to ask few more questions! To me, the terms like 'line coding', digital baseband modulation, symbol mapper, pulse shaping are used differently in diffferent resources available. Can you please distinguish them for me or for other users of your videos? Thanks
sir the DAC used in the above explanation has confused me as the output of the circuit is converting a binary bits o,1 in to the voltage level which is having binary value (0,5) so sir the output is itself a digital signal as it has only two values, is it not correct to give it a name of pulse shaping filter rather than calling it a DAC ?
No. The input to the DAC is just a sequence of 1's and 0's stored in discrete memory. It is not a waveform. The output of the DAC is a continuous-time waveform (eg. a time domain voltage signal on a wire).
@@iain_explains for analog signal
1) value is defined at every point
2) also the analog signal has uncountable amplitude in a particular range of time
these two conditions are not satisfied as the signal has countable amplitude and signal is not defined at the zero crossings
I don't know what you are talking about, sorry. The output of the DAC is an analog continuous time signal. Just because we say it switches between the values 0V and 5V, doesn't mean the output is finite-valued - it just means that the waveform switches between those analog values.
So source coding is the same as compression?
Yes.
in order to remove the adverse effect of the channel, we are using the process of equalization, than what's the point of using channel coding if we are doing it for the same purpose, why we are using extra bits for channel coding?
Channel coding is generally aimed at overcoming random noise in the channel. Most common is when the noise is independent from one symbol to the next, but it could also be bursty. In contrast, when the channel introduces inter symbol interference (ISI), the "interference" is from the signal itself (not random noise), and so specific techniques are needed for this, eg. equalisation. See "What is Intersymbol Interference ISI?" th-cam.com/video/I087FUvW2ys/w-d-xo.html
Is channel capacity the same is frequency capacity?
Sorry, I've never heard the term "frequency capacity". I really don't know what it would refer to. I suspect whoever you've heard it from was either confused, or you've mis-heard them. Channel capacity is a function of bandwidth, but I wouldn't call it "frequency capacity". See this video for more details: "What are Channel Capacity and Code Rate?" th-cam.com/video/P0WY96WBUyA/w-d-xo.html
How does line coding comes into play ?
Thanks for the suggestion. I'll add it to my "to do" list.
Thanks for this! Pretty sure it's pronounced "gif" though