Dear Marcus Müller:
Actually my problem is:
y=useful information+x*h(channel)*cfo(carrier offset due to
the local oscillator between the interference and the radar)+noise.
I want to turn y to
new_y=useful information+noise.
So I need know the channel(h) and the cfo exactly(I know the x in advance while
I don't know the cfo and h.So I have to estimate them).The root question I
faced is the cfo estimated from the SCA isn't enough.
Thank you so much. I will read the paper you mentioned.Maybe helpful.Thanks.
Best regards,
zs
At 2015-06-24 17:08:16, "Marcus Müller" <marcus.muel...@ettus.com> wrote:
Hi zs,
this reminds me very much of OFDM radar technologies, as your problem boils
down to finding a good estimator for the spectral properties of your OFDM frame
as well as the time it reached you.
I think you should have a look at chapter 3, "OFDM Radar Algorithms" of [1];
you might find that considering the unknown timing being a result of the time
it took a OFDM signal to reach you (and hence an effect of range) a useful
approach. You can find some shorter information on the accuracy of these
estimates in [2].
The difference in the algorithms described in [1] and your problem is that you
don't a priori know the transmitted signal -- you'll have to figure that out by
using something like S&C to receive and decode the OFDM symbol prior to "clean"
reconstruction; you could then use the parameters (range == timing, doppler ==
frequency) that the radar estimators give you to model the symbol like you
received it, and subtract it from your incoming signal. Of course, the mistakes
you make when decoding the incoming symbol will have an influence on the
accuracy of your estimates.
Best regards,
Marcus
[1] Braun, Martin. OFDM Radar Algorithms in Mobile Communication Networks.
Diss. Karlsruhe, Karlsruher Institut für Technologie (KIT), Diss., 2014, 2014;
http://nbn-resolving.org/urn:nbn:de:swb:90-388921
[2] Braun, Martin, Christian Sturm, and Friedrich Jondral. "On the
single-target accuracy of OFDM radar algorithms." PIMRC. 2011.;
http://www.cel.kit.edu/download/PIMRC2011_BraunSchuSturmJondral.pdf
On 06/24/2015 10:29 AM, zs wrote:
Dear Marcus Müller:
Thank you so much for your kindly reply.
The SCA is adequate for a correct demodulation of the signal while maybe
inadequate for estimate the precise frequency shift.I don't have the
synchroniztion device.In my application,I need to reconstruct one transmit
signal in time domain,and remove it from the received signal.For
example,y=x1+x2,and I want to remove x2 from the baseband recevied signal.
Now my idea is no only used the SCA algorithm mentioned in the new ofdm
example, but also use other similar finer carrier frequency estimation
algorithm.I want to combined the algorithms.So I ask the question in the
maillist.
Thank you so much.
Best regards,
zs
At 2015-06-24 15:54:30, "Marcus Müller" <marcus.muel...@ettus.com> wrote:
Dear zs,
basically, Schmidl and Cox is a very good algorithm, because it can achieve the
same quality of synchronization with half of the synchronization overhead
compared to other approaches, or a better performance with the same amount.
I must admit that from the top of my head, there's probably not much that's
better than S&C in a real world OFDM receiver, but I must admit that I haven't
implemented many OFDM synchronizers myself.
However, you say
> Now in my application,maybe this algorithm isn't enough.
which means that you have a mathematical measure that's not OK for S&C, I
guess. So in what way doesn't S&C suffice? What is it about your application
that makes S&C insufficient or impossible to use?
Best regards,
Marcus
On 06/24/2015 09:00 AM, zs wrote:
Dear all:
Thank you in advance.
1.
I want to ask a question about the new ofdm example.And I know
the receiver have used the SCA(schmidl and cox algorithm) algorithm.Now in my
application,maybe this algorithm isn't enough.And I want to ask whether have
other good frequency offset correction algorithm which have been implemented.
2.What is the algorithm used by the old version of the ofdm
example?Thanks.
Best regards,
zs
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