Ep 38. Things We Learned at the 6G Symposium [Wireless Future Podcast]

Many topics are studied within the 6G research community, from hardware design to algorithms, protocols, and services. Erik G. Larsson and Emil Björnson recently attended the ELLIIT 6G Symposium in Lund, Sweden. In this episode, they discuss ten things that they learned from listening to the keynote speeches. The topics span from integrated sensing, positioning, and localization via machine-learning applications in communications to fundamental communication theory, such as circuits for universal channel decoding and jamming protection. The expected 6G spectrum ranges, energy efficiency in base stations, and new use cases for electromagnetic materials are also covered. You can find slides from the symposium at elliit.se/news... Music: On the Verge by Joseph McDade. Visit Erik’s website liu.se/en/empl... and Emil’s website ebjornson.com/
Chapters:
3:22 Integrated sensing and communication
12:45 Positioning using phase-coherent access points
20:42 Experimental work on positioning from ELLIIT Focus period
24:02 Trained activation functions in machine learning
30:25 Learning to operate a reconfigurable intelligent surface
37:15 Guessing Random Additive Noise Decoding (GRAND)
44:30 Protecting digital beamforming against jamming
53:02 6G frequency spectrum
1:01:50 Energy efficiency in base stations
1:08:47 New use cases for electromagnetic materials
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#wireless #wirelessfuture #6g #GRAND #jamming #energyefficiency #spectrum

[@franciscogerardohernandezr4788]

This is elite stuff, and their valuable opinions are a great start to "calibrate" our own on opinions, many of which are outside our area of expertise.

[@BilelMnasri13]

Thank you both for this wonderful episode.
I was really shocked when listening to Prof. Larsson talking about the idle time energy consumption of base stations and how the level increases just a bit when they are active..
I remember those BCH and many other control channels from some mobile networks courses I had during my bachelor. But I did not know about the energy they had to consume while the BS is not communicating..

[@McD-j5r]

I am learning that, most possibly, the 5, 6, or 7Gs have nothing to do with our physical, mental, or psychic health since we are upgrading it regardless.

[@jasminnadic2103]

A short question regarding the a more general point. For e.g. localization purposes, do I need contiguous bandwidth or can it be from different spectrum parts (e.g. 100 MHz from sub 6 GHz and additional 300 MHz from the 24 GHz part)?
The equation says nothing about that, just Ts=1/B.
Thanks a lot.

[@WirelessFuture]

Hi! The formula applies to the case with contiguous bandwidth. But one can certainly use signals sent in multiple spectrum parts to perform localization. Algorithms must be designed specifically for that case.

[@knutlohmann8205]

Thanks for all of your work,
do you happen to know array deployments with varying antenna element spacing?

[@WirelessFuture]

The antenna arrangement determines the shapes of the beams that the array can generate.
If you consider uniformly spaced arrays with varying spacing, then you can find the theory for studying this many textbooks. Including Chapter 4 of my book new book www.nowpublishers.com/article/BookDetails/9781638283140
In essence, the width of the main lobe is inversely proportional to the total length of the array, while the interference outside the main lobe depends on the spacing between the antennas.
If you consider irregular antenna arrangements, it is harder to predict how the signals will look like, but one can simulate it.

[@knutlohmann8205]

@@WirelessFuture Thanks, I meant one array with different element spacing in between - I have not heard about such a case so far.
I think there is no real benefit for that but special space constraints.

[@WirelessFuture]

I haven't studied this in detail myself, but if you do a Google search on "non-uniform linear array", you can find some papers that study the topic. They are, for instance, optimizing the antenna locations for particular performance metrics.