I have some frequency response data from 802.11a OFDM communication in channel 8 of the 5 GHz band, and I would like to inverse transform this to produce the corresponding time domain response. That is, I have $N$ equally spaced samples $H(f_1), H(f_2), ..., H(f_N)$ (except the middle sample is missing, see below) of the radio channel transfer function, and I wish to obtain the time domain impulse response $h(t)$, or in practice a discrete approximation $\hat{h}[n] \approx h[n] = h(nT_s)$.
Now, if I inverse FFT the samples I get a sequence $g[n]$, but I do not know what time values the elements of the sequence represent. The ways I know of to obtain the time resolution are all based around knowing the sampling frequency $f_s = 1 / T_s$ that was used to produce the original FFT, but that is unknown here. I do however know the frequencies $f_1, f_2, ..., f_N$, and intuition tells me that it should be possible to infer the time resolution from this knowledge. I am not very familiar with discrete transforms however, so I haven't been able to figure it out myself.
To be specific, the $N = 52$ frequencies in question are centered around $5040 \; MHz$ and spaced $312.5 \; kHz$ apart. The center frequency is missing (unused), so there are 26 below center and 26 above, making the full range $f_1 = 5031.875 \; MHz$ to $f_{52} = 5048.125 \; MHz$.