shout_testing

Hands-on Session: Over-the-air Narrowband QPSK Modulation and Demodulation

Measurement collection via SHOUT

We use the SHOUT measurement framework to automate TX/RX functions across multiple POWDER nodes. The measurements of different communication links will later be assigned to several groups for QPSK demodulation.

Instantiate an Experiment

1. Log onto POWDER
2. Select the shout-long-measurement profile. If you do not have access to the profile, one can be created via: Experiments → Create Experiment Profile → Git Repo → add repo link → select the profile
3. Start an experiment by specifying all necessary parameters [compute node type, radio types and frequency range] and finish. If the radios are not available, please create a reservation ahead of time.

SSH into the orchestrator and clients

Once the experiemnt is ready, go to List View for the node hostname.

1. Use the following commands to start ssh and tmux sessions for the orchestor:

   ssh -Y -p 22 -t <username>@<orch_node_hostname> 'cd /local/repository/bin && tmux new-session -A -s shout1 &&  exec $SHELL'
   ssh -Y -p 22 -t <username>@<orch_node_hostname> 'cd /local/repository/bin && tmux new-session -A -s shout2 &&  exec $SHELL'
   

2. Use the following command to start a ssh and tmux session for each of the clients:

   ssh -Y -p 22 -t <username>@<radio_hostname> 'cd /local/repository/bin && tmux new-session -A -s shout &&  exec $SHELL'
   

Note: tmux allows multiple remote sessions to remain active even when the SSH connection gets disconncted.

Designing an IQ file

1. Use the signal generation Jupyter Notebook (https://github.com/npatwari/tx_rx_processing/blob/main/QPSK_signal_generationV3.ipynb).
2. Change the Info_to_TX variable to the message desired to be transmitted (using the same length at the placeholder one).
3. Use the file transfer script (https://github.com/npatwari/tx_rx_processing/blob/main/filetransfer.sh) to scp the iq file to all nodes. Make sure to update the HOSTS using the List View of your experiment, as well as the iq filename. The file will show up in the ~ directory on the nodes.
4. Use the following command (updating the iq file name) to move the iq file to the path where it is specified in the JSON file. This eliminates what needs to be edited in the JSON file on each node.

   mv ~/QPSK_signal_2023_01_18_neal.iq /local/repository/shout/signal_library/QPSK_signal_2023_01_18_neal.iq
   

Transmission and reception

1. Files to modify before running an experiment:

   (1) ./3.run_cmd.sh: make sure that the CMD in line 16 is save_iq_w_tx_file.

   (1.5) useexternalclock = True: edit meascli.py to enable the use of external clock white rabbit in nodes.

   Path: /local/repository/shout/meascli.py.

   (2) save_iq_w_tx_file.json:

   Path: /local/repository/etc/cmdfiles/save_iq_w_tx_file.json.

   Parameters:

   • txsamps: which file to transmit samples from. Note that the file should contain complex samples as float32 IQIQ...

   • txrate and rxrate: sampling rate at TX and RX.

   • txgain and rxgain: TX and RX gain.

   • txfreq and rxfreq: TX and RX carrier/center frequency.

   • txclients and rxclients: nodes for transmission and reception.

   • rxrepeat: number of repeated sample collection runs.

   • sync: whether to enable sync between TX and RX.

   • nsamps: number of samples to be collected.

   • wotxrepeat: number of repeated sample collection runs without TX.

2. Orchestrator-client connection

   (1) In one of your orch SSH sessions, run: ./1.start_orch.sh

   (2) In the SSH session for each of the clients, run: ./2.start_client.sh

3. Measurement collection In your other orch SSH session, run:

   ./3.run_cmd.sh
   

4. Collection Confirmation In one of the orch SSH sessions, check that the data folder was created by running the following command and checking for a directory called Shout_meas_datestr_timestr with three files: log, measurements.hdf5, save_iq_w_tx_file.json

   ls /local/data/
   

5. Transfer the measurement file back to the local host

   scp -r <username>@<orch_node_hostname>:/local/data/Shout_meas_datestr_timestr /<local_dir>
   

6. If you are testing UHD, run the following command on each node (other than orchestrator). Change filename to be an appropriate title such as probe_bes.txt if you are wanting to save the results. Otherwise, just run the uhd_usrp_probe without piping the output to a file.

   uhd_usrp_probe > filename.txt
   

   Then, run the following command on your local host to recover the created files.

   scp <username>@<radio_hostname>:/local/repository/bin/filename.txt /<local_dir>
   

QPSK Demodulation

SDR node pairs used for this session

Group Number	Link
1	cbrssdr1-ustar-comp --> cbrssdr1-hospital-comp
2	cbrssdr1-ustar-comp --> cbrssdr1-browning-comp
3	cbrssdr1-smt-comp --> cbrssdr1-honors-comp
4	cbrssdr1-honors-comp --> cbrssdr1-hospital-comp
5	cbrssdr1-bes-comp --> cbrssdr1-smt-comp
6	cbrssdr1-browning-comp --> cbrssdr1-fm-comp
7	cbrssdr1-browning-comp --> cbrssdr1-bes-comp
8	cbrssdr1-honors-comp --> cbrssdr1-browning-comp
9	cbrssdr1-browning-comp --> cbrssdr1-ustar-comp
10	cbrssdr1-fm-comp --> cbrssdr1-bes-comp
11	cbrssdr1-fm-comp --> cbrssdr1-browning-comp
12	cbrssdr1-fm-comp --> cbrssdr1-smt-comp
13	cbrssdr1-fm-comp --> cbrssdr1-ustar-comp
14	cbrssdr1-smt-comp --> cbrssdr1-bes-comp
15	cbrssdr1-smt-comp --> cbrssdr1-browning-comp
16	cbrssdr1-smt-comp --> cbrssdr1-fm-comp
17	cbrssdr1-smt-comp --> cbrssdr1-hospital-comp
18	cbrssdr1-hospital-comp --> cbrssdr1-smt-comp
19	cbrssdr1-hospital-comp --> cbrssdr1-ustar-comp
20	cbrssdr1-honors-comp --> cbrssdr1-bes-comp
21	cbrssdr1-honors-comp --> cbrssdr1-smt-comp
22	cbrssdr1-honors-comp --> cbrssdr1-ustar-comp
23	cbrssdr1-ustar-comp --> cbrssdr1-honors-comp
24	cbrssdr1-ustar-comp --> cbrssdr1-smt-comp
25	cbrssdr1-smt-comp --> cbrssdr1-ustar-comp
26	cbrssdr1-hospital-comp --> cbrssdr1-honors-comp
27	cbrssdr1-bes-comp --> cbrssdr1-browning-comp

Measurement analysis

For the demonstration, we will analyze the received signals on Google Colab as our python notebook. (You can also certainly run the python notebook locally on your own Jupyter Notebook if you have one installed on your computer.)

Compress the collected measuremnt folder using zip in order to upload all its files to the Colab notebook. Or if you want a previously collected dataset, there are some in this repo.

You will then load our python notebook on Google Colab. You'll follow all of the instructions on this notebook. That includes making a copy of the notebook (the linked file is read only); uploading the zipped measuremnt file; and picking the txloc and rxloc and repNum for the measurement you will analyze.

In the demo, we will attempt to organize so that each person / group looks at a different link.