Browsing by Subject "Amplitude-limited inputs"

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Open Access
On the capacity of multiple-antenna systems and parallel Gaussian channels with amplitude-limited inputs
(Institute of Electrical and Electronics Engineers Inc., 2016) Elmoslimany A.; Duman, T. M.
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. © 1972-2012 IEEE.
Open Access
On the discreteness of capacity-achieving distributions for fading and signal-dependent noise channels with amplitude-limited inputs
(Institute of Electrical and Electronics Engineers, 2018) Elmoslimany A.; Duman, Tolga
We address the problem of finding the capacity of two classes of channels with amplitude-limited inputs. The first class is frequency flat fading channels with an arbitrary (but finite support) channel gain with the channel state information available only at the receiver side; while the second one we consider is the class of additive noise channels with signal-dependent Gaussian noise. We show that for both channel models and under some regularity conditions, the capacity-achieving distribution is discrete with a finite number of mass points. Furthermore, finding the capacity-achieving distribution turns out to be a finite-dimensional optimization problem, and efficient numerical algorithms can be developed using standard optimization techniques to compute the channel capacity. We demonstrate our findings via several examples. In particular, we present an example for a block fading channel where the channel gain follows a truncated Rayleigh distribution, and two instances of signal-dependent noise that are used in the literature of magnetic recording and optical communication channels.