Capacity Achieving Probability Measure of an Input-bounded Vector Gaussian Channel

A discrete-time memoryless additive vector Gaussian noise channel subject to average cost constraints and an input-bounded constraint is considered. The necessary and sufficient condition for an input distribution to be capacity achieving is derived, and the capacity achieving distribution is shown to be “discrete” in nature.