Image Restoration by Solving Constrained Least squares in Frequency Domain (Frequency Domain Filtering)
When dealing with applying a 2D convolution in frequency domain we have to take into account 2 things:

Extending the kernel to the dimension of the input data.
Dealing with the implicit periodic extension of the frequency domain element wise multiplication.

As you wrote in the comments, one way to do it is simple zero padding and fftshift(). Yet this might cause some artifacts.
Better way to deal with it is the Periodic Extension as I wrote in my answer to Applying 2D Image Convolution in Frequency Domain with Replicate Border Conditions in MATLAB. I added there some code to apply the extension in MATLAB.
More sources would be Applying Image Filtering (Circular Convolution) in Frequency Domain and my answer to How to Zero Pad in Order to Perform Filtering in the Fourier (Frequency) Domain? and 2D Frequency Domain Convolution Using FFT (Convolution Theorem).