I am currently trying to understand the Chirp Z Transform, and compute an FFT for a vector that has size which is not necessarily a power of 2. The key step in the Chirp Z transform to recognize that the boils down to computing a circular convolution of two vectors of length $n$.
My question is: How does one compute the circular convolution of two vectors say ($x,x,...,x[n]$) and ($y,y,...,y[n]$) using DFTs only sizes that are a power of 2? I know that by the convolution theorem, I can find the circular convolutions of two vectors applying the DFT (and it's inverse) a few times, but I only have power of 2 sized DFTs at my disposal to compute this for arbitrary $n$. I considered padding the vectors to increase their size to the nearest power of 2, but it seems as if one must carefully construct such a padding to get the right result (since we need to compute modulo $n$ and not $2^k$).
For more context: I was going through Dilip Sarwate's answer on this topic at this link: https://math.stackexchange.com/questions/104148/chirp-transform-and-convolution[on math stackexchange]1 and was unable to figure out how one can compute a circular convolution efficiently.