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MIMO Channel Models
In this webdemo we evaluate the capacity limits of Multiple Input Multiple Output (MIMO) channels. Generally, a MIMO system consisting of $N_{\rm{t}}$ transmit antennas and $N_{\rm{r}}$ receive antennas can be represented by the following vector/matrix equation $$ \mathbf{y}=\mathbf{H}\mathbf{x}+\mathbf{n} $$ where $\mathbf{x}$ is the transmit symbol vector with the dimension $N_{\rm{t}}\times 1$, $\mathbf{y}$ is the $N_{\rm{r}}\times 1$ receive vector, $\mathbf{n}$ represents the $N_{\rm{r}}\times 1$ additive white Gaussian noise (AWGN) vector and usually the noise is assumed to be spatially independent, i.e., $\rm{E}\left\{\mathbf{n}\mathbf{n}^{H}\right\}=\sigma_{n}^{2}\mathbf{I}_{N_{r}}$. Furthermore, the flat fading MIMO channel is modeled by the matrix $\mathbf{H}$ with the dimension $(N_{\rm{t}}\times N_{\rm{r}})$. Explicitly, the channel matrix is given by $$ \mathbf{H}=\begin{bmatrix} h_{11} & \cdots & h_{1N_t}\\ h_{21}& \cdots & h_{2N_t}\\ \vdots & \vdots & \vdots \\ h_{N_{r}1}& \cdots & h_{N_{r}N_{t}} \end{bmatrix} $$ where the elements $h_{ij} \, \forall i, j$ typically follow circularly symmetric complex Gaussian distribution with zero mean and unit variance in Non-Light-of-Sight (NLOS) scenarios.