Hi arunirc,
(I’m not sure I understand what you want to do.   Are you planning to do a Next Sentence Prediction type of task, where you input pairs of texts having up to 512 tokens each?   Or, when you say “same sentence” do you mean a set of words separated by full stops?)
Within each layer, after the attention heads, the output from each head needs to be concatenated before the feed-forward network.   For that concatenation to work, I suspect that the matrices need to be the same size.   If so, then I don’t think you could have one head only attending to a few tokens, because its matrix would be smaller.
Have you considered using two completely separate BERT models, one of which has only 1 head per layer and takes as input only the first text,  and the other of which has 15 heads per layer and takes as input the pairs of texts, and combining the outputs later.