How to use ndcg metric for binary relevance
The nDCG depends on the relevance of each document as you can see on the Wikipedia definition. I guess you could use 0 and 1 as relevance scores, but then all relevant documents would have the same score of 1, and then it wouldn't make much sense to apply the nDCG penalty discounts.
A similar measure often used with binary relevance scores is the mean average precision defined as:
$\text{MAP}=\frac{\sum_{q=1}^Q\text{AveP}(q)}{Q}$,
where $Q$ is the number of queries.
A comprehensive explanation of both nDCG and MAP is available here