Hang tight while we fetch the video data and transcripts. This only takes a moment.
Connecting to YouTube player…
Fetching transcript data…
We’ll display the transcript, summary, and all view options as soon as everything loads.
Next steps
Loading transcript tools…
Tao Luo: Understanding integrated sensing and communications | RCR Wireless News | YouTubeToText
YouTube Transcript: Tao Luo: Understanding integrated sensing and communications
Skip watching entire videos - get the full transcript, search for keywords, and copy with one click.
Share:
Video Transcript
to in the conversations I've had during
Mobile World Congress around 6G one
thing keeps coming up and that's
integrated sensing and communication so
to start maybe you could just sort of
explain to us what that is so that's a
good question so integrated sensing and
communication which means you can
leverage existing Cellar infrastructure
for the sensing and communication
traditional c s only for communication
now you add additional function for
Network that's why it's called integrate
sensing and Communications okay so it
seems like there'd be two sort of
primary buckets of use cases for this
one the network understands its own
physical environment so it become more
adaptable as things around it change but
then you could also use that sensing
capability to do other types of services
that might be of use to various vertical
Industries but can you kind of take us
through both of those yeah so first you
can do the sensing assisity
communication you know you can improve
the radio performance by knowing the
environments better you you know for
example the demo we showing here you
know they were showing by using this
understand this environments better you
can do better communication on the other
hand you also have other use case for
example security detect a person you
know or drone detection flying around
you can track detect so you can better
uh track the uh enable is a l attitude
economy for example in different
countries you know so on what sort of
timeline should we think about this
going from uh research Focus to
something that would be a little more
real world a little more tangible so in
some of the case it's already happening
in some of the uh country you know they
doing the trial for this Jun you know on
the other hand there also are there more
use case weely more research so it takes
some time to actually to realize the
full potential of this one then I wanted
to also get some uh perspective from you
on a wireless AI so I know this is a
priority for you and your colleagues can
you give us a bit of an overview of uh
where your focus today is today our
Focus AI is one to improve the wireless
air interface which means you can do
better algorithm save the energy either
at the LK side or device side you know
and also potentially even improve the
performance so it's focus on the air
interface the one we're currently doing
and so then how do you operationalize
Wireless AI I guess if you have a a
model of a of a real Network and all of
the variability that that entails you
know how do you how do you take that and
then create that sort of closed loop
where you're able to reap the benefit of
the adaptability that you put into the
network yeah there's a two aspect on
this one one is called a model switching
so want you move to one scenario to
another scenario for example Urban to
Suburban you may want to do the model
switching you have a different model has
been trained know on the other hand also
want to say is UND devised training you
continue just learning just like a human
you get more information you update your
model and use it
immediately so is it fair to think of it
as a device to network Continuum where
there's intelligence throughout and it's
uh continuing to learn continuing to
adapt and improve yes that would be best
optimize your performance and also
provide a lot of advantage to able to
scale this AI AML model for air
interface right very good well T I
really appreciate you taking a few
minutes to tell us about the work you
and your colleagues are doing thank you
so much [Music]
Click on any text or timestamp to jump to that moment in the video
Share:
Most transcripts ready in under 5 seconds
One-Click Copy125+ LanguagesSearch ContentJump to Timestamps
Paste YouTube URL
Enter any YouTube video link to get the full transcript
Transcript Extraction Form
Most transcripts ready in under 5 seconds
Get Our Chrome Extension
Get transcripts instantly without leaving YouTube. Install our Chrome extension for one-click access to any video's transcript directly on the watch page.
Chrome Extension