Signal Processing for Communication - Science topic

Dear researcher

I see in this book an important relationship to your question, I hope you read it.

Best regards

Digital Signal Processing Using MATLAB & Wavelets

by Michael Weeks

Use log normal _shadowing path loss model in microcell region if factory area is confined within 500 meters of radius. You will have to consider the several case...

1_ within building

2_From building to open space.

3_within open space

3_open space with scatters etc

I would recommend to look at (cooperative) rate-splitting instead. This works much better than (cooperative) NOMA. See for instance

Let me check on that.

Dear Mr. Shrotey.

This paper can help you: https://arxiv.org/pdf/1303.1795.pdf to improve your knowledge and synchronize between the results of simulation and analytic because in this paper be able formulas dan step-by-step to solve the problems.

Regards,

Syahrial Shaddiq, S.T., MIET., M.M.

Buy the book!

Dear Majid,

I suggest to you links and attached files in topics.

-IEEE Xplore: IEEE Transactions on Wireless Communications ...

-Multi-User Interference Suppression by Using Frequency Domain ...

www.intechopen.com/...user.../multi-user-interference-suppression...

 Best regards

Hello Sir,

Yes you are correct, but that is not my question. Please check my attachment with the question.  In LTE TDD we switch from downlink to uplink and uplink to downlink. there is always a special subframe in between two symbols while switching from uplink to downlink but there is no subframe or guard period while switching from downlink yo uplink. why?

According to me we always subtract the modulation factor. Let suppose modulation order is 2 (4 QAM), that means we are mapping 2 bits to 1 complex symbol. Energy of 2 bits is given to 1 complex symbol.

(It means if there is error in 2 bits then only one symbol will be wrong)

So in linear scale 

Es/No = (Eb/No)*(1/2) ;

and in dB 

Es/No = Eb/No + 10*log10(1/2) = Eb/No - 10*log10(2) 

Here is the explanation from Matlab: http://in.mathworks.com/help/comm/ug/awgn-channel.html

Please correct me if I'm wrong. 

Calculating LLRs requires generating a set of vector symbol candidates. Once you have a set of candidates, the LLRs can be computed the same way as a sphere decoder does it. How to generate such set? As an starting point, I'd suggest you to try the following approach:

1. Calculated the the ZF/MMSE equalized vector symbol.

2. Before performing hard decision, find the K closest constellation vectors to  your   ZF/MMSE equalized vector symbol.

3. Then you will have K+1 candidates from which you can compute the LLRs. (K obviously depends on the size of the constellation set).

Hope this helps.

Rate matching is accomplished by resampling the baseband signal by an interpolation of  5 divided by four, that is for every four  samples are substituted by five samples..You can assume that the fifth sample i an average value of the other four  and inserted in the middle of then, that i two samples before and two samples after.

Wish you success

I agree with answers above, but if "var" should be the true variance then you write it as

sqrt(var/2)*(randn(1,N)+1i*randn(1,N))

so that the real and imaginary parts each contribute to one half of the variance.

As an ED needs information about the noise level it can not be considered as fully blind.

In principle, why not?

Walkie talkies typically operate either in the citizens band, high HF, or in the VHF spectrum. Whereas mobile phones operate at high UHF, above 700 MHz to the GHz ranges. So that's one problem. The antenna requirements, for small hand held devices with no external antenna, would make use walkie talkie frequencies quite inefficient.

But mobile phones are already multiband devices, after all, so why not (in principle)? Mobile phones already detect frequencies available at any given location, and pick the best one to use. So I don't think there's anything intrinsically impossible about designing a "mobile phone" to use other frequency bands than those allocated to cellular. However, the spectrum allocation authority in your country would most likely not allow this.

"THREE STATE FONTAN LMS CHANNEL MODEL" does not include:

Cheers,

Kai

To get some ideas you might want to look at work done on deghosting on marine seismic data. Loot at seg.org or eage.org. There are several approaches that are described. The most common is to apply an inverse filter. However, you may also find a finite difference algorithm that might be suitable. Even though the theory is simple, a practical implementation in 2 or 3-D might be rather tricky.

Hello

You can see these links:

Best regards

FTP is ok to transfer files on whatever IP network. If you need security, use SFTP or SCP.

On the basis of required accuracy of the channel estimation, optimal training sequences of minimum length are determined and it is given by

NP ≥ NT (L + 1) + L

Where, Where, Np = the number of training symbols per transmit antenna and per frame.

The training sequences very much effect the channel capacity, and by implementing the Optimal training sequence length improved MSE and capacity both.

I agree with Johannes that this "pure" view is not very practical. SDR was always envisioned as a slow evolution from completely unconfigurable systems (i.e., hardware-defined systems) to reconfigurable systems (defined by software which may be uploaded to effect different personalities). For instance, see Mitola 99 "Software Radio Architecture: A Mathematical Perspective", the block diagram in that work is far more complex than what you are calling an SDR. I would suggest that at today's processing capabilities and expectations of extremely (or even moderately) high data rates from consumers the ultimate goal that you describe is not in reach. But this thing you speak of is not the one-and-only definition of SDR.

To me, the advantage of an SDR is its reconfigurability and its flexibility. Why else would you want one? So, here's my question to you. If you have a truly reconfigurable radio (say something even better than the prototyping platforms on the market today) that can be reprogrammed (by a host computer or its own "intelligence") to modify its carrier frequency, data rate, modulation format, etc... Albeit based on some "custom" but reprogrammable hardware. What is the difference whether we call it massively reconfigurable hardware-defined radio (MRHDR?) or software-defined radio (SDR)? Aren't the end goals of both the same? What more does the platform you describe offer us above and beyond this reconfigurability? I would argue that the amount of software and programmable hardware that goes into platforms currently available merits the name software-defined radio as it is the software that gives the radio its definition (operating parameters, signal characteristics, etc). Most of the SDR research that interests me would not be classified as SDR by your definition. I think this definition is too narrow. After all, I would suggest that our personal computers are software-defined even though they may have custom hardware attached (e.g., high performance video cards).