I don't have videos on antenna design yet (it's in my future plans), but I do have videos on the signal processing with multiple antennas, eg. MIMO, Beamforming, ... You can find a listing of all my videos at: iaincollings.com
So if i understand correctly, rician fading still offers increase in channel capacity despite a strong LoS availability between Tx and Rx, we just need to chose a and b intelligently. So for typical use case in which the transmitter is moving and the receiver is stationary, how can we design the balance of a and b such that the capacity enhancement can be achieved? how to control a and b in a real time mobile transmitter scenario?
You don't get a chance to "design" a and b. Nature sets them for you, based on the scattering environment. And I'm not sure you've understood the point I was trying to make, about the scaling. You say "rician fading still offers increase in channel capacity despite a strong LoS availability", but it's not "despite" a strong LoS, it's _because_ of the strong LoS. If you can receive more energy at the receiver, you will be able to do a better job of detecting the signal/data, and you'll have a higher capacity.
Great Video Sir! But I'm surprised only 100 people liked it when 4.3K people have already benefitted from it . Guys please give Thumbs Up to good content like this so its visibility increases and could be found by people looking for such content.
I'm from India sir..and final year student of electronics and communication engineering in India..I would suggest you to solve and upload the questions of GATE examination which is technical exam of India for technical students these questions are of very good level and teaches the beauty of concepts..your explanation is very good sir.. thank you
But isnt there will be a problem with channel estimation due to LOS? Another issue is the more LOS you got the more columns are identical and hence channel matrix will be less invertible(or precicely will have bigger entries). Moreover, even if there will not be problem with channel estimate, your pseudo-inverse channel matrix may add 10s of dB gain to noise during eqalization. So this gain of capacity due to increased K can be also tricky. I want to ask: is 5G spec talk what model of K normalization should be used? 38.901 section 776 talk only about k=a^2/b . Logicly will be to use model A otherwise with K increase i need to manipulate SNR to compare "apples to apples". Which is SNR = 1/(No*K)? Increase noise power knowing you will get "K" power more then you should? Sorry, I am just overwhelmed ... i thought recian literlly kill multipath by fading itself on top of it, the fact is you its harder to send multi layer transmission with LOS in MATLAB simulation. But when you check transmitter and reciever in the box condition in real life, sudenly you got 4 layer in MiMO4x4.
Sorry, I don't have all the answers with regards to the specifics of the 5G standard in this aspect, but from a fundamental perspective this video might help: "Why doesn't MIMO work in Line-of-Sight (LoS) Channel Conditions?" ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-xqmdOXhZ2D4.html
When comparing different communication modulation schemes, it is common to look at the performance with respect to the receive SNR. In doing this, the "channel gain" is often normalised to unity. This motivates the use of Model A. However, it hides the reality of the channel characteristics, and is not (in my view) the relevant metric when considering/comparing different types of channels (where I would suggest Model B is more appropriate).
@@iain_explains This is really fascinating but I feel that I do not understand the subtlety details thoroughly. Anyway thank you so much for leaving the name of the relevant paper/book in the video description for us to read. I have a habit of watching your video and reading the reference together to have a feel of the subject. Could you kindly make a video about using model A to compare between different modulation schemes ?
