  Consider a $N\times n$ random matrix $Y_n=(Y_{ij}^{n})$ where the entries are
given by $$ Y_{ij}^{n}=\frac{\sigma_{ij}(n)}{\sqrt{n}} X_{ij}^{n} $$ the
$X_{ij}^{n}$ being centered, independent and identically distributed random
variables with unit variance and $(\sigma_{ij}(n); 1\le i\le N, 1\le j\le n)$
being an array of numbers we shall refer to as a variance profile. We study in
this article the fluctuations of the random variable $$ \log\det(Y_n Y_n^* +
\rho I_N) $$ where $Y^*$ is the Hermitian adjoint of $Y$ and $\rho > 0$ is an
additional parameter. We prove that when centered and properly rescaled, this
random variable satisfies a Central Limit Theorem (CLT) and has a Gaussian
limit whose parameters are identified. A complete description of the scaling
parameter is given; in particular it is shown that an additional term appears
in this parameter in the case where the 4$^\textrm{th}$ moment of the
$X_{ij}$'s differs from the 4$^{\textrm{th}}$ moment of a Gaussian random
variable. Such a CLT is of interest in the field of wireless communications.
