tavildar / ldpc Goto Github PK

As a hardware engineer, I am working on developing an FPGA hardware design for LDPC. I have a MATLAB code that is similar to the
this code. However, I am facing an issue with the processing of the Rx data. Currently, the data is coming in one by one into the array "updated_llr_vec". According to the code, the variable "l1" is calculated using the value of "updated_llr_vec(n2)- lasteta(i_m, n2)))",

                            n2 = obj.row_mat(i_m, i_n2);
                            l1 = (updated_llr_vec(n2) - lasteta(i_m, n2));

which means that if "n2" is equal to 136, I will have to wait until 136 data points are filled in the "updated_llr_vec" array before the next process can start. This will result in latency issues.

I am wondering if there is a way to avoid this latency issue and optimize the processing of the data. Is there anything that I am missing in my understanding of the code, or is there a better way to implement this process? Any insights or suggestions would be greatly appreciated.

Hi! Nice library, thank you for this!

Would it be interesting for you to implement one LDPC/QAM simulation for image transmission?

I'm doing a comparison work between Artificial Intelligence and Conventional/Classic methods for coding/decoding and modulation/demodulation.
Having a reliable and fair simulation of LDPC/QAM like yours but with images would be even more excellent.

I'm in doubt because in your current work the information bits must have the K dimension (row dimension of H). But how can we adapt an image for this case, once an image have multiple and different dimensions (pixels)?

Hello, how are the images in the readme generated? I did not find a way to generate