How to build a for-loop for 3rd dimensional noise realizations

I am currently working on some research and was given a signal set of 1000x320x10 that I need to filter. The 3rd dimension is the number of noise realizations present. For a prior signal set, I used a for-loop to cycle through the data, line-by-line, and save the newly filtered data for later testing. I now need to include a seperate for-loop to also go through the 10 noise realization, but I am unsure how to properly make it go through the consecutive loops of that 3rd dimension. Do i just nest another for loop in there somewhere after filtering the original 1000 rows? Or do I need to filter them each row by row (1x320x1, 1x320x2, 1x320x3,...,1x320x10)?

Thank you!

clc;
clear;
close all;

load Wifi_Data_9dB_L5;


Fs = 20e6;                                                              %Establishing Variables
Fsamp = 20e6;
BW = 7.7e6;
Rp = 0.01;
Order = 4;
ImpPlot = 0;
PrntPlots = 0;
Rp = 0.01;
%%--------------------------------------------------------------------------
Tsamp = 1/Fsamp;                                                        %Filter variables
SNR = 9;
NumMC = 10;
FiltType ='Cheby';
N = 6;

for i = 1:1000
    New_Sig = SigPlusNoise(i,:);                                        %Drawing signal from given matrix
    
    SigIn = New_Sig;                                                    %Establihing input signal    
                                                                       
    cheby = LPF_ChebyI_V1(SigIn,Fsamp,Order,BW,Rp,ImpPlot,PrntPlots);   %Filter function
    
    New_data(i,:) = (cheby);                                            %Making new matrix
    
end 

save('New_data')                                                        %Saving filtered signal in file New_Data

[Jordan Willis]

For anybody that reads this in the future, the issue is that I was being given a cell with a huge matrix crammed into it. So, using Tarunbir's answer, all I had to change was to use SigPlusNoise{1} in combination with the (i, :, j).

My code is now listed below and runs fine.

for i = 1:1000
    for j = 1:10
        New_Sig = SigPlusNoise{1}(i,:,j);                                      %Drawing signal from given matrix
    
        SigIn = New_Sig;                                                    %Establihing input signal    
                                                                           
        cheby = LPF_ChebyI_V1(SigIn,Fsamp,Order,BW,Rp,ImpPlot,PrntPlots);   %Filter function
        
        New_data(i,:,j) = (cheby);                                          %Making new matrix
    end
end 

Answer 1

[Tarunbir Gambhir]

Based on the information you have shared, I assume that you have 1000 samples of signals which are of length 320, and have 10 different noise realizations each.

I suggest you use a nested for loop to go through the third dimension, filtering among different noise levels for each signal. Something like this should work.

for i = 1:1000
    for j = 1:10
        New_Sig = SigPlusNoise(i,:,j);                                      %Drawing signal from given matrix
    
        SigIn = New_Sig;                                                    %Establihing input signal    
                                                                           
        cheby = LPF_ChebyI_V1(SigIn,Fsamp,Order,BW,Rp,ImpPlot,PrntPlots);   %Filter function
        
        New_data(i,:,j) = (cheby);                                          %Making new matrix
    end
end 

On a side note, I advise you to initialise 'New_data' variable with the correct size before entering the for loop.