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Young-Han Kim

Publications and source records attributed to Young-Han Kim.

59 records · Page 4Linked to original sources

On the Feedback Capacity of Stationary Gaussian Channels

The capacity of stationary additive Gaussian noise channels with feedback is characterized as the solution to a variational problem. Toward this end, it is proved that the optimal feedback coding scheme is stationary. When specialized to the first-order autoregressive moving-average noise spectrum, this variational characterization yields a closed-form expression for the feedback capacity. In particular, this result shows that the celebrated Schalkwijk--Kailath coding scheme achieves the feedback capacity for the first-order autoregressive moving-average Gaussian channel, resolving a long-standing open problem studied by Butman, Schalkwijk--Tiernan, Wolfowitz, Ozarow, Ordentlich, Yang--Kavcic--Tatikonda, and others.

cs.IT↗

A Counterexample to Cover's 2P Conjecture on Gaussian Feedback Capacity

We provide a counterexample to Cover's conjecture that the feedback capacity $C_\textrm{FB}$ of an additive Gaussian noise channel under power constraint $P$ be no greater than the nonfeedback capacity $C$ of the same channel under power constraint $2P$, i.e., $C_\textrm{FB}(P) \le C(2P)$.

cs.IT↗

Feedback Capacity of the First-Order Moving Average Gaussian Channel

The feedback capacity of the stationary Gaussian additive noise channel has been open, except for the case where the noise is white. Here we find the feedback capacity of the stationary first-order moving average additive Gaussian noise channel in closed form. Specifically, the channel is given by $Y_i = X_i + Z_i,$ $i = 1, 2, ...,$ where the input $\{X_i\}$ satisfies a power constraint and the noise $\{Z_i\}$ is a first-order moving average Gaussian process defined by $Z_i = αU_{i-1} + U_i,$ $|α| \le 1,$ with white Gaussian innovations $U_i,$ $i = 0,1,....$ We show that the feedback capacity of this channel is $-\log x_0,$ where $x_0$ is the unique positive root of the equation $ ρx^2 = (1-x^2) (1 - |α|x)^2,$ and $ρ$ is the ratio of the average input power per transmission to the variance of the noise innovation $U_i$. The optimal coding scheme parallels the simple linear signalling 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 error 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. 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 \emph{autoregressive} Gaussian noise channel studied by Butman, Wolfowitz, and Tiernan, although the optimality of the latter is yet to be established.

cs.IT↗

On Multiple User Channels with Causal State Information at the Transmitters

We extend Shannon's result on the capacity of channels with state information to multiple user channels. More specifically, we characterize the capacity (region) of degraded broadcast channels and physically degraded relay channels where the channel state information is causally available at the transmitters. We also obtain inner and outer bounds on the capacity region for multiple access channels with causal state information at the transmitters.

cs.IT↗

Monotonicity Results for Coherent MIMO Rician Channels

The dependence of the Gaussian input information rate on the line-of-sight (LOS) matrix in multiple-input multiple-output coherent Rician fading channels is explored. It is proved that the outage probability and the mutual information induced by a multivariate circularly symmetric Gaussian input with any covariance matrix are monotonic in the LOS matrix D, or more precisely, monotonic in D'D in the sense of the Loewner partial order. Conversely, it is also demonstrated that this ordering on the LOS matrices is a necessary condition for the uniform monotonicity over all input covariance matrices. This result is subsequently applied to prove the monotonicity of the isotropic Gaussian input information rate and channel capacity in the singular values of the LOS matrix. Extensions to multiple-access channels are also discussed.

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