Channel capacity and state estimaiton for state-dependent gaussian channels

• Published in: IEEE transactions on information theory Vol. 51; no. 4; p. 1486
• Main Authors: Sutivong, Arak, Chiang, Mung, Cover, Thomas M, Young-Han, Kim
• Format: Journal Article
• Language: English
• Published: New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.04.2005
• Subjects: Communication channels; Data transmission; Normal distribution
• ISSN: 0018-9448; 1557-9654

We formulate a problem of state information transmission over a state-dependent channel with states known at the transmitter. In particular, we solve a problem of minimizing the mean-squared channel state estimation error E parallel Sn - Sn parallel for a state-dependent additive Gaussian channel Yn = Xn + Sn + Zn with an independent and identically distributed (i.i.d.) Gaussian state sequence Sn = (S1,..., Sn) known at the transmitter and an unknown i.i.d. additive Gaussian noise Zn. We show that a simple technique of direct state amplification (i.e.,Xn = alpha Sn), where the transmitter uses its entire power budget to amplify the channel state, yields the minimum mean-squared state estimation error. This same channel can also be used to send additional independent information at the expense of a higher channel state estimation error. We characterize the optimal tradeoff between the rate R of the independent information that can be reliably transmitted and the mean-squared state estimation error D. We show that any optimal (R,D) tradeoff pair can be achieved via a simple power-sharing technique, whereby the transmitter power is appropriately allocated between pure information transmission and state amplification. [PUBLICATION ABSTRACT]