5G NR PN23 payload generation

DCI/DLSCH Payload Data to PDCCH used by TM is PN23 of 3GPP standard.

However, the PN23 provided by matlab and the PN23 provided by Keysight are different.

Keysight: PN23 (0:1727)

If there is any way to make PN23(0:1727)?

Or is there a setting example for comm.PNSequence when making a PN23 in general?

Answer 1

[Nivedita]

Hi Jongmin!

I understand that you want to generate the PN23(0:1727) sequence as provided by the Keysight in MALTAB.

I do not have much knowledge in the PN23 payload generation. However, I can guide you on how you can achieve this.

To achieve this, you can follow the steps below:

% Define the length of the PN sequence 
pn_seq_Length = 1728; % Total length of the PN sequence, including the initial value 

% Create a PNSequence object 
pnSeq = comm.PNSequence('Polynomial', 'x^23 + x^18 + 1', 'SamplesPerFrame', pn_seq_Length); 
pnSeq.InitialConditionsSource = "Property"; 
pnSeq.InitialConditions = zeros(1,23); 

% Generate the PN sequence 
pnSequence = pnSeq(); 

% Extract the desired range of the PN23 sequence 
pn23 = pnSequence(1:1728); % Adjust the range as needed 

• In the code above, I have used a polynomial x^23 + x^18 + 1 as an example and also set the “InitialConditions” property to all zeroes, which are to be changed according to the requirement. You can adjust the range (pn23 = pnSequence(1:1728)) to match the specific range or length required by your application or the Keysight tool.
• Regarding the discrepancy between the PN23 sequences generated by MATLAB and Keysight, I would suggest you to review the documentation and specifications of each tool to understand how they generate and represent PN sequences. If you're getting different results, it might be caused due to differences in the initial conditions, polynomial coefficients, or other settings used by each tool.
• For Keysight's equipment, you might need to consult their documentation or support resources to understand the exact settings required to generate a PN23 sequence that matches your expectations.
• For more detailed information on how to generate various PN sequences using the “comm.PNSequence” object and other examples, you can refer to the following documentation link: Generate a pseudonoise (PN) sequence - MATLAB

I hope this helps!