SDR - Science topic

The simulation should involve mobile users, dynamic environments with data, voice, command & control, position location, and ISR video transport over waveforms in UHF, L-band, and S-band frequencies. I am using NetSim, but guidance involving other tools is also welcome.

I want to design a diversity reciver (in a single input multiple output (SIMO)) where i have the following specifications.

1. i have 100MHz RF bandwidth

2. i use simple BPSK

3. No of transmitting antennas are only one.

4. I want to achive 1Gbps speed

I want to know is there any clear procedure to find the number of antennas required to achieve the desired data rate. Please let me know if any one has done such a design with an SDR board or any thing. Thank you.

I try to transmit LFM signal using SDR platform (usrp-2932) and receive The Signal using another usrp of The same version , The TX and RX ports are connected through RF Cable With certain length .

MY question is : it Must appear single bin at certain frequency after applying FFT, but The received pin is very fast , what is The factors that affect this phenomena?

Does anyone know is there is an Open-Source Software-Defined-Radio (SDR) implementation of the Bluetooth Low Energy (BLE) Physical Layer ?

Different Global Navigation Satellite Systems are vulnerable to different kinds of intereferne, some are intentional while others are unintentional. Jamming and spoofing are 2 types of intentional intereferne that affect the accuracy of a GNSS or RNSS measurements

This managed to throw me for a loop. When I'm assessing the presence of outliers before I conduct my moderation analysis I use SPSS to split the data file based upon the dichotomous moderator. I test my assumptions separately and perform a simple linear regression of the IV on the DV at each level of the moderator to generate studentized deleted residuals (SDR) and Cook's distances, so far so good!

The confusion I'm running into is that in Cohen et al. (2003) he recommends a different cutoff score for considering potential outliers: SDR +- 2 for small sample sizes and +- 3 for large sample sizes. This sort of information makes a lot of sense in the context of a standard multiple regression but when dealing with a dichotomous moderator in which assumptions are tested separately for each level I'm just wanting to do a bit of a sanity check.

I've assumed that if there is a small group size in one dichotomous level that I am applying these SDR cutoffs separately based upon size of the group and NOT overall sample size.

Similarly, I prefer using the 4/n cutoff of Cook's distance for considering potentially high leverage values rather than just looking for values greater than 1 (I could swear these are only present in artificial datasets).

All the articles I've come across so far always express n as sample size and so again I run into this slight confusion about if it's correct of me to have two different cut off scores of Cook's distance that is specific to the group size. I mean after all, the regression line, the residuals, and the produced Cook's distance are specific to that level of the moderator and therefore should have their own group cutoff.

Thanks in advance for taking the time to read and weight in!

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Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

Hello,

As in the topic i want to decode transmission recorded from 433MHz humidity and temperature sensor. I have file with recorded transmission, and i want to read this two values in MatLAB.

Dear all, I would like to start a discussion on ASTM D 2843-16 a technical standard for measuring the smoke density. The standard has usually a poor repeatability and you need to make a lot of measurements to understand the “direction” of your results.

The smoke chamber works with a burner and a photometric system measuring the absorbance (A%) in 4 minutes and smoke density rating, SDR, is the ratio b/w the area below A (%) curve and total area multiplied x 100.

We usually check the calibration of photometric system before each set of measurements, the temperature of the chamber (stopping the measurements if temperature is over 50 °C), but I guess the critical point is the burner. We noted that slight differences of flux, caused by partial clogging of nozzle due to carbonaceous deposits from particularly dense smokes, can give results with huge differences. That because a flame with less energy causes a delay of the emission of the smokes affecting a lot the area below the curve. Usually we can prevent the clogging error with repeated measurements of an internal standard with known SDR and verifying if some drift is about to start. So we open the burner, we clean the nozzle and the remaining items of the burner in ultrasound bath, we reassemble the burner and we checked again the SDR of the standard. Obviously this procedure is time consuming with the risk to compromise the correct functioning of the burner itself.

Another problem affecting the results is related on kind of formulations. Test specimens obtained with quite soft PVC formulations tends to “follow” the flame. So the flame shape them and the top of test specimen remains unburnt (see the picture). We usually tie the sample or we block it with a wide mesh net but the problem remains.

Any tips or suggestions to perform the standard with more repeatable results?

Thank you

Hello Sir,

I working on SDR implementations. I did not have good idea on cellular communication systems, means, I am not much aware of synchronization channels, transport channels, and PHY implementation algorithms used in cellular systems. Can you please suggest any books related to these?

We are using WaTEM/SEDEM to estimate soil erosion and SDR in a watershed. Although we prepared all the input layers with appropriate format according to the attached model manual, we can not run the model software because of some unknown errors. All kindly helps are appreciated.

The model software is attached, but introducing any different version of the software to solve the problem is also appreciated.

Me and a group of first year undergrads from my college are working on building a horn-antenna for radio astronomy similar to this http://rishi-patel.blogspot.in/2013/10/summary-of-horn-antenna-project.html.

How to analyse the raw samples from the RTL-SDR USB dongle receiver using Python. I know basic programming in python. is that enough to analyse the data? If not what additional courses should I learn ?

I would like to plot the rotation curve of galaxies and calculate the dark matter distribution. Is it possible using the horn-antenna?

I need to test on SDR hardware and compare the results both software and hardware results

Hello, please I would like to know if it is possible to re-prgramme a commercial SDR like those proposed by OUTERNET (http://outernet.is/) which are designed to receive satellite data so that the SDR receive GSM data?

Actually , I need to test the performance ,capabilities of Software defined radio and cognitive radio modules (spectrum sensing algorithms) on an USRP platform.Then depending on the results I want to see if it is applicable on wireless sensor networks.

For sensing a real time signal by using SDR what is the procedure to follow to set the threshold value. In most of the documents its mentioned as trial and error method. Is it the average of the power. But then if noise power is more  or less then it leads to mis-detection  and false alarm. Can any one suggest a way to set the threshold to detect a real time signal using SDR?

I'm wondering if there are any low cost SDR Satellite Channel Emulators.

I'm looking at emulating the Doppler Shift for VHF & UHF frequencies as seen by ground stations that don't dynamically tune. In this instance the ground stations have a fixed central frequency.

Has anybody tried using a HackRF to emulate Doppler Shift? Probably for something like GPS and or GNSS?

This:

versus:

i want to test the efficiency of my sensing algorithm using R820T2 RTL-SDR. Is any one there who is working on this

There are many models for estimating sediment delivery ratio, often for large watersheds have been developed but few models have been introduced for small watersheds.

Is it in any way related to spectrum sensing, e.g. is it a part of the spectrum sensing process? And what will be the course of action if the channel quality of the sensed spectrum (white space) is very poor?

Currently the USRP I am using for my work can be equipped with 2 RF daughter boards so that you can connect 2 antennas. How can I extend this to more antennas?

Can I use the technique of antenna selection and use a RF switch between the antennas and daughter boards?

H/W boards which support SDR components, open source tools to verify and develop.