Project enquiry/interest

GNU Radio
1

Hi,

I am looking for some references on the following subject.

Simultaneous transmissions, multiple users transmitting and receiving on
the
same channel frequency simultaneously, Multi user detection, etc.

Is there any one here involved or aware of any research project or
interested in the above subject. Any pointers will be highly
appreciated.

Thanks and Regards,

Sajeev Manikkoth

2

Hi Marcus,

Thanks for your input and as suggested I can check on the GNU radio
presentations. As far as I know none of the current wireless access
technologies allow simultaneous transmissions on same channel. And we do
all
form of frequency planning and interference avoidance schemes offline
and
deploy wireless solutions. I was looking for research interests on new
PHY
and MAC layer techniques which can allow 2 or more transmitters at the
same
location to use same frequency, but receivers being capable of turning
to
the desired transmitters.

Thanks and regards,
Sajeev

3

Hello Sajeev,

Simultaneous transmissions, multiple users transmitting and receiving
on the same channel frequency simultaneously, Multi user detection, etc.
that is a bit wide – every multi-user transmission system has
considered these aspects, so you’re basically asking us to list all
communication systems that have been implemented.

Maybe have a look at the presentations given at the GNU Radio
conferences the last couple of years, search for GNU Radio and any of
these key words on IEEExplore, or look at specific communication
standards and look for GNU Radio implementations of these.

Best regards,
Marcus

4

Hi Sajeev,

On 02/22/2015 05:37 PM, Sajeev Manikkoth wrote:

Hi Marcus,

Thanks for your input and as suggested I can check on the GNU radio
presentations. As far as I know none of the current wireless access
technologies allow simultaneous transmissions on same channel.
Um, being access technologies, that’s actually exactly what they do, and
why they’re existing.

“Simultaneous” is kind of a difficult term, and of course TDMA systems
like GSM allow different people to use the same channel “at the same
time” only from a higher-up point of view; functionally, the same
channel is shared simultaneously. “Same Channel” is yet another
difficult term, but for example in the context of GSM, the same channel
estimate applies to successive access by different users to the same
subchannel, which is, from a information theoretical perspective, what
I’d call “accessing the same channel”.

There are various different FDMA schemes, which allow parallel access to
the spectrum (think the OFDM-based LTE, where you as a user are assigned
resource blocks), and of course, CDMA systems share the same
time-frequency ranges without interfering; that’s what they use codes
for.

And we do all
form of frequency planning and interference avoidance schemes offline and
deploy wireless solutions.
And that is a must, no matter what you’ll do technically, because being
absolutely synchronous and knowing the channel exactly would be the only
alternative to that. You might want to read up on stuff like
inter-symbol-interference and why you can’t allow unlimited interference
power in any channel, no matter how good your system becomes at handling
that (channel capacity).
I was looking for research interests on new PHY
and MAC layer techniques which can allow 2 or more transmitters at the same
location to use same frequency, but receivers being capable of turning to
the desired transmitters.
What you describe applies to things like CDMA, and basically any form of
MIMO.
These are not new research, though, since CDMA has at least been in
use/development since the mid-1950s (cold war) and is used in many
mobile phone standards (2G: IS-95, 3G: UMTS, CDMA2000 etc), and GPS.
MIMO is a umbrella term for systems that use a single channel with
multiple “observers” and “signal producers” (e.g., antennas): It’s
wide-spread in many access technologies (WiFi, WiMax, LTE, but even
stuff like home-network powerline standards) and allows for the
“creation” of multiple let’s say “virtual” channels over one medium.

Best regards,
Marcus M.

5

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. What I am talking is about a full simultaneous
parallel use or access of channel. This is kind of necessity as wireless
bandwidth demands are ever growing and we are hitting spectrum scarcity.
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.

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 ! 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…

Thanks and Regards,
Sajeev Manikkoth

6

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

7

Hi Sajeev,

the problem is that there are so many projects that you’ll find when you
use google with ’ “GNU Radio”’, that it’s very hard to know what
you’re looking for – notice how you still say

“my references on this topic”

whilst I’m still totally confused what your topic actually is. I’ve
talked to some other people and they don’t think you’ve made it clear
what your talking about, either.

You should really, really find the technical terms, the jargon, that
describes what you’re looking for, and then it will be easy for us to
recommend something. Up until now, I feel you’ve been extremely vague –
and yet you make it all sound so interesting :slight_smile:

Greetings,
Marcus

8

Hi Marcus,

Sorry that I did not made my point clear. To conclude this thread, I was
looking for projects and people who think and work following topic is a
realizable goal.

Radios which transmit and receive without interference worries
(co-channel,
adjacent channel, etc) by overcoming the hardware and radiator
limitations
with software algorithms. Perhaps with new hardware techniques too.

Regards,
Sajeev

9

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

10

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 :slight_smile:

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

  1. “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 :slight_smile:
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.