Re: [Discuss-gnuradio] Project enquiry/interest

[Marcus Müller]

Hi Sajeev,

thanks for adding more information!

There's two things I'd like to mention at this point; after that, I
think it might be a good idea to let this discussion thread die. I feel
I'm digressing too much, and it'll be easier for you to come up with a
new email that says "Hey, do you know research on XY, possibly related
to GNU Radio", now that we have mentioned so many concepts with names,
and you can pick one or a few XYs from these. Bombarding you with more
terms really won't help either of us, I guess :)

So these two things are 1. quantifying your ideas, and 2. cognitive
communications:

1. telecommunication with electromagnetic waves is not very much like
looking at objects with the human eye, I agree.
But that's basically because the sensory apparati involved are so
different: The eye is a focussable matrix detector for photons, which
means you kind of get a whole set of per-frequency-bin intensities at
once, whereas digital communication usually needs to rely on a single
(or a few) antennas receiving a signal, which only has a single quality
-- voltage over time.
Thus, your comparison kind of needs to take a step back: First of all,
you'd need to make some kind of "image" out of the temporal signal,
before you can do anything cognitive on it. In fact, projecting a
received signal into a vector space is a method very common to almost
all digital transmission systems:
RF engineers of think of signals as combination of points in a
N-dimensional room, constructed by base vectors of independent vectors,
just like a 2D image might be constructed by mapping colors to points in
the plane.
The art of finding appropriate signal representations has led to a whole
lot of different transmission schemes, some of which are
constellation/pulse shape based (think of a PSK with a matched filter),
some employ orthogonality of specific frequency components to first map
a set of symbols to a time signal (OFDM), some simply represent
different symbols/users by different sequences of chips (CDMA);
detectors for these different representations use the characteristics of
the signal model to optimize correct decoding. "Optimize" is a hard
word, here: It demands that the signal model is somewhat mathematical,
which allows the engineer to find an *optimal* decoder, in many cases.

After that, there's the art of channel coding (as opposed to source
coding, and largely unrelated to CDMA), which approaches the actual
information to be sent from a information theoretical point of view; it
adds redundancy at the transmitter to make it easier for the receiver to
correctly decode what has been sent, and it gives the receiver
appropriate methods to maximize probability of correct decoding. Network
Coding is somewhat related to this, and is yet another discipline of
communications engineering you should have a look at.
Again, there's a *large* mathematical background to this, and a lot of
things have upper bounds for how well things can possibly work, there
are solutions to specific cases that are proven mathematically to be the
optimum, and there are lots of research to be done -- most of the codes
we know today are rather bad compared to what we know must exist, but
science has not been able to find better ones, so far[1].

Somewhere in between the mapping of physical quantities to code words,
and finding good codes to encode information, to maximize
speed/reliability/spectrum efficiency of transmission [2], or somewhere
across, sits equalizing. Now, equalizers have a lot of properties that
people consider "smart", "adaptive", and thus somewhat "cognitive", but
that brings me to my second issue

2. "cognition" is one of the buzzwords of RF communication of the last
15 years, thanks to Mitola '98, who coined the term "cognitive radio",
to describe systems that are aware of their RF environment and act based
on this awareness. This comes with a whole lot of theory on what a radio
must/can/could know, how to exchange that kind of info etc. Network
coding once again comes into play -- you should definitely have a look
at that.

Now, I'm not totally sure you're going after cognitive radio -- from
what you describe, designing a good channel code that reaches the
channel capacity[3], maybe combined with an equalizer, fits what you're
looking for, which is recognizing advanced patterns in a
more-than-1-dimensional representation of the signal. There's a lot of
approaches that do this -- chose the one you want to dig deeper into :)
Computer vision is a fairly mature field of research, and it has led to
a lot of signal models for 2D images; all the things I said about
mathematical optimization above apply to these models, too, and the
point here is that it's always crucial to find a good representation
(ie. a well-fitting model) that explains the signal to your detection
algorithm.

There are a lot of decoder classes that are what one could call learning
-- iterative methods that use the information gathered in the last
processing step to aid and improve the next step -- be it a definite
decision about the (N-1)th bit employed to calculate the likelihoods of
the Nth bit, or be it a soft decision state used in a iterative decoder
arbitrary times. Have a look at Turbo Decoders -- they interleave
decoding and equalizing, and thus learn from symbols of the past to
interpret the coming symbols more accurately.

So, to conclude: 1. you say you want to see things being done better,
but you'll need to mathematically define "better"; in many cases, the
structures employed are mathematically proven to be optimal, and 2.
you're comparison to recognition of things by the human eye needs to
first find a mathematical model that makes an image from the signal, and
for which you can be smarter than the solutions that are already known.

Best regards,
Marcus



[1] which, to me, was one of the core things I took away from my channel
coding course.
[2] Note that I use these three different goals as one thing here -- you
can often do this, because the common problem is "for this given
channel, how can we get a maximum of bits across", and a good solution
solves all the three problems.
[3] Wow, my footnotes are getting channel coding centered these days.
Reaching channel capacity means: No matter what you do, for the SNR in
this channel you can't get more bits across (with arbitrarily little
error) than possible with this code.

On 02/23/2015 06:02 PM, Sajeev Manikkoth wrote:
> Thanks Marcus, and adding some more details. Current signal detection
> mechanisms for years totally rely on signal attributes (frequency, timing,
> amplitude) for differentiation of signals. Cognitive detection mechanisms
> and new PHY layer techniques which emulate human eye like detection and
> differentiation need to be developed. One simple scheme I can think of is:
>
> Human eye can differentiate 2 similar items or let us say identical twins.
> And when we find it difficult, we add different identification marks on
> those twins to differentiate and identify. In a similar fashion may be a
> transmitter can add a unique identification while modulating/transmitting,
> and the receivers can look for those. Receivers shall first tune to the
> channel frequency, and then to the unique transmission id to latch to the
> desired transmitter.
>
> In general my interest was to see interest and projects which develops
> cognitive detection mechanisms and associated new PHY and MAC layer
> techniques. Hope I am making some sense now...
>
> Best regards,
> Sajeev 
>
> -----Original Message-----
> From: Marcus Müller [mailto:address@hidden 
> Sent: 23 February 2015 19:55
> To: Sajeev Manikkoth; address@hidden
> Subject: Re: [Discuss-gnuradio] Project enquiry/interest
>
> Hi Sajeev,
>
> On 02/23/2015 10:56 AM, Sajeev Manikkoth wrote:
>> Hi Marcus,
>>
>> Thanks again for the detailed explanation of current access technologies.
> As
>> discussed current scheme allows shared access of the channels in time,
>> frequency, and space.
> Yes, that's how I understood this discussion.
>>  What I am talking is about a full simultaneous
>> parallel use or access of channel.
> I really really don't understand what you mean with that -- what other
> dimensions than time, frequency, space (incl. polarization) and code can
> you imagine, that would distinguish one electromagnetic wave from another?
>
>>  This is kind of necessity as wireless
>> bandwidth demands are ever growing and we are hitting spectrum scarcity.
> Spectrum scarcity has been a reality ever since Marconi!
>> The
>> scheme I am discussing is close to CDMA/MIMO. CDMA base stations already
>> differentiate handsets using same frequency with signature sequences.
>> Implementing a similar approach on the handset side also to differentiate
>> base stations or similar approaches can be in place.
> CDMA handsets of course already do CDMA -- otherwise, they wouldn't be
> able to communicate with the base station (which would be
> disadvantageous, I reckon).
> LTE handsets (at least from what I remember about LTE Release 8, which
> is the original LTE release) can make use of MIMO. Probably they already do.
>> In its simplest form the requirement is to allow 2 FM stations using same
>> frequency in a location area. And the receivers tune to the station names
> to
>> enjoy different music rather than just to the frequency !
> Well, that would then necessarily be some kind of diversification by
> coding -- be it CDMA, or be it multiple lower-rate streams embedded in a
> broadcast transport stream, which is what DVB does. That doesn't
> inherently increase spectrum efficiency -- instead of 100 channels with
> bandwidth b, you get 1 channel with bandwidth 100*b, because you can't
> cheat channel capacity, and as long as you can't change SNR, the only
> thing you can increase to get more information from transmitter to
> receiver is to increase bandwidth.
>>  Nothing new as a
>> concept, limitations to achieve this reasons we have all the existing
>> implementations, but 100s of years of engineering fineness. Now this
> should
>> be possible with soft transceivers using today's digital radio techniques
>> combined with soft techniques...
> What kind of soft techniques? Soft decision decoders?
> I still don't really understand where you think that current technology
> falls short and what's to improve, but I think I'm getting closer to
> understanding exactly what kind of research is of interest to you;
> please do elaborate!
>
> Greetings,
> Marcus
>