On the Capacity of Multiple-Antenna Systems and Parallel Gaussian Channels With Amplitude-Limited Inputs

We propose upper and lower bounds on the capacity of multiple-input multiple-output (MIMO) systems with amplitude-limited inputs. The results are derived by considering an equivalent channel via singular value decomposition, and by enlarging and reducing the corresponding feasible region of the channel input vector, for the upper and lower bounds, respectively. We analytically characterize the asymptotic behavior of the derived bounds for high and low noise levels, and study the gap between them. We also consider parallel Gaussian channels with peak and average power-constrained inputs. For such channels, the capacity-achieving distribution has been reported in the literature to be discrete, which can be computed using numerical optimization techniques. However, there is no closed-form expression and finding the capacity-achieving distribution is computationally tedious. With this motivation, we derive approximate expressions for the capacity at low and high noise variance levels. We illustrate our findings on both MIMO channels and parallel Gaussian channels via several numerical examples.