用bsxfun卷积而不是Matlab中的循环

Question

I want to replace the for loops with bsxfun to calculate convolution in Matlab. Following is the script:

for Rx = 1:Num_Rx
    for Tx= 1:Num_Tx
        Received(Rx,:)=Received(Rx,:)+conv(squeeze(channel(Rx,Tx,:))', Transmitted(Tx,:));
    end
end

% Received is a Num_Rx by N matrix, Transmitted is a Num_Tx by N matrix and channel is a 3D matrix with dimension Num_Rx, Num_Tx, N.

When I changed code as:

Received = bsxfun(@plus, Received, bsxfun(@conv, permute(squeeze(channel), [3 1 2]), Transmitted));

Error came out, which said "two non-single-dimension of input arrays must be matched".

How could I correct this line? Thanks a lot!

Answer 1

Why do you want to replace the loops with bsxfun ? If the sizes involved in the convolution aren't particularly small, then the convolution is going to take up most of your overhead and the difference between loops and some vectorized version of this call is going to be minimal.

One option you have, if you can afford the temporary storage and it doesn't mess with your numerics too much, is to use the FFT to do this convolution instead. That would look something like

 Transmitted = reshape(Transmitted, [1 Num_Tx size(Transmitted, 2)]);
 N = size(Transmitted, 3) + size(channel, 3) - 1;
 Received = ifft(fft(channel, N, 3).*fft(Transmitted, N, 3), N, 3);
 Received = squeeze(sum(Received, 2));