Capacity-Distortion Tradeoff of Noisy Gaussian State Amplification

Yinfei Xu, Tao Guo, Daming Cao, Wei Xu

Abstract: The problem of joint information and noisy Gaussian state amplification is investigated in this paper. The optimal capacity-distortion tradeoff is characterized. For the achievability part, the Gelfand-Pinsker scheme is evaluated using minimum mean squared error of Gaussian random variables. For the converse part, Cauchy-Schwartz inequality is invoked to transform the optimal linear estimation into a canonical form.