How to find the following bias equation? While reading up for a question on Cryptography.SE I stumbled across quite a complex equation approximating the bias of a "down-sampling" function. The original paper is "The Security of DSA and ECDSA Bypassing the Standard Elliptic Curve Certification Scheme" by Vaudenay (PS).
The question on Crypto.SE has a full quote of the relevant section, but I will re-state things here.
Suppose we have a prime $q\in\mathbb P$ from the interval $[2^{N-1},2^{N})$. Suppose further we have an integer $k\in\mathbb N$, that is uniformly, randomly sampled from the range $[0,2^N)$. Now suppose we construct $\mathbb N\ni k'=k\bmod q$, obviously "all the numbers larger than $q$ get wrapped around" which means that the probability that $k'\in[0,N-q]$ is double as high as for the rest of the interval $[0,q)$.
Now the paper states that this leads to the bias 
$$E\left(e^{\frac{2i\pi k}q}\right)\approx \frac{q
 e^{i\pi\frac{N-1}q}}{\pi N} \times \sin\left(\frac{\pi N}q\right)$$
My question is "simple":
From the above definitions, how do we arrive at this approximation?
 A: (Sorry for the late answer. I stumbled across this question while searching for a different paper)
This is a straightforward application of the sum of complex exponentials. E.g. here
Suppose $N > q$ and $k$ is uniformly distributed on $[0, N)$, i.e. $P(k=j) = \frac{1}{N} \forall j \in [0,N)$. Then the bias term 
\begin{align} 
E\left(e^{\frac{i2\pi k}{q}}\right) & = \sum_{j=0}^{N-1}P(k) e^{\frac{i2\pi k}{q}} \\
& = \frac{1}{N}\sum_{j=0}^{N-1}e^{\frac{i2\pi k}{q}} \\
& = \frac{1}{N} \frac{1-e^{\frac{i2\pi N}{q}}}{1-e^{\frac{i2\pi}{q}}} \\
& = \frac{1}{N} \frac{ e^{\frac{i\pi N}{q}}(e^{-\frac{i\pi N}{q}}-e^{\frac{i\pi N}{q}})}{e^{\frac{i\pi}{q}}(e^{-\frac{i\pi}{q}}-e^{\frac{i\pi}{q}})} \\
& = \frac{1}{N} \times e^{ i\pi \frac{N-1}{q}} \times \frac{\sin(\frac{\pi N}{q})}{\sin(\frac{\pi}{q})}\\
& \approx \frac{q e^{i\pi\frac{N-1}q}}{\pi N} \times \sin\left(\frac{\pi N}q\right)
\end{align}
where the last approximation uses $\sin x \approx x$ for $x \rightarrow 0$. This will  be the case if $q$ is large, as is typical for most cryptosystems.
Note that the wraparound is implicitly handled in the summation from $0$ to $N-1$, since for $j \geq q$, the complex exponential term wraps around as well.
