Circular convolution of real signal N by N/2 sized complex IFFT
This is the general solution to recover N real samples using an N/2 Length IFFT. N/2+1 samples of the FFT are required for an even sequence N.  

First generating a sample sequence of the N/2+1 samples of an FFT of a real signal:

x = [1 2 3 4 5 6 7 8];
N = length(x);
N2 = N/2;
fx = fft(x);
X = fx(1:N2+1);             % starting result: positive spectrum of real sequence


So above is the same result as can be alternatively computed with an N/2 FFT as already demonstrated.

Given such an result, below shows how to get the original sequence x using an N/2 IFFT. The code is self-explantory:

W = @(k,N) exp(-j*2*pi/N*[0:k-1]);                   % FFT Twiddle factors
Xe =  (X(1:N2) + conj(X(N2+1:-1:2)))/2;              % FFT of even samples
Xo = (X(1:N2) - conj(X(N2+1:-1:2)))./(2*W(N2,N));    % FFT of odd samples

newX = Xe + j*Xo;                      

xr = ifft(newX);                      % N/2 IFFT 
newxo =  real(xr)                     % recovered odd x samples
newxe =  imag(xr)                     % recovered even x samples


Since each FFT in your formula for cross correlation is the FFT of a real signal, the product will also be the FFT of a real signal, hence the technique outlined above can be used.