Suppose there are $n=2k+1$ independent and identically distributed exponential random variables with rate parameter $\lambda.$ Find $\mathbb{E}[median(X_1,\cdots,X_n)]?$
To do so, I found the density of $median(X_1,\cdots,X_n) = X_{(k+1)},$ where $X_{(j)}$ denotes the jth order statistic. Namely, $$f_{X_{(j)}}(a) = n \lambda e^{-\lambda a} \binom{n-1}{j-1}(1-e^{-\lambda a})^{(j-1)}(e^{-\lambda a})^{((n-1) -(j-1))} = n \lambda e^{-\lambda a} P(Y=j-1), $$ where $Y$ is a binomial random variable with number of trials and probability of success equal to $n-1$ and $1-e^{-\lambda a},$ respectively. Hence, $$f_{X_{(k+1)}}(a) = n \lambda e^{-\lambda a} \binom{n-1}{k}(1-e^{-\lambda a})^{k}(e^{-\lambda a})^{((n-1)-k)} = n \lambda e^{-\lambda a} P(Y=k). $$ This leads to $$ \mathbb{E}[median(X_1,\cdots,X_n)] = \mathbb{E}[X_{(k+1)}] = \int_{0}^{\infty} x f_{X_{(k+1)}}(x) dx, $$ but I'm stuck on the integral-- I'm not sure if there is a closed form solution.
Alternatively, is there a simpler way to find the solution?