Young-Han Kim

*IEEE Transactions on Information Theory,*vol. 52, no. 7, pp. 3063–3079, July 2006.Preliminary results appeared in

*Proceedings of IEEE International Symposium on Information Theory,*pp. 416–420, Adelaide, Australia, September 2005.

Despite numerous bounds and partial results, the feedback capacity of
the stationary nonwhite Gaussian additive noise channel has been open,
even for the simplest cases such as the first-order *autoregressive*
Gaussian channel studied by Butman, Tiernan and Schalkwijk, Wolfowitz,
Ozarow, and more recently, Yang, Kavcic, and Tatikonda. Here we
consider another simple special case of the stationary first-order
*moving average* additive Gaussian noise channel and find the feedback
capacity in closed form. Specifically, the channel is given by where the input satisfies a
power constraint and the noise is a first-order moving
average Gaussian process defined by with white Gaussian innovations

We show that the feedback capacity of this channel is

where is the unique positive root of the equation

and is the ratio of the average input power per transmission to the variance of the noise innovation . The optimal coding scheme parallels the simple linear signaling scheme by Schalkwijk and Kailath for the additive white Gaussian noise channel — the transmitter sends a real-valued information-bearing signal at the beginning of communication and subsequently refines the receiver's knowledge by processing the feedback noise signal through a linear stationary first-order autoregressive filter. The resulting error probability of the maximum likelihood decoding decays doubly-exponentially in the duration of the communication. Refreshingly, this feedback capacity of the first-order moving average Gaussian channel is very similar in form to the best known achievable rate for the first-order {autoregressive} Gaussian noise channel given by Butman.