The compound channel capacity of a class of finite-state channels

A transmitter and receiver need to be designed to guarantee reliable communication on any channel belonging to a given family of finite-state channels defined over common finite input, output, and state alphabets. Both the transmitter and receiver are assumed to be ignorant of the channel over which transmission is carried out and also ignorant of its initial state. For this scenario we derive an expression for the highest achievable rate. As a special case we derive the compound channel capacity of a class of Gilbert-Elliott channels

On the use of training sequences for channel estimation

Suppose Q is a family of discrete memoryless channels. An unknown member of Q will be available, with perfect, causal output feedback for communication. We study a scenario where communication is carried by first testing the channel by means of a training sequence, then coding according to the channel estimate. We provide an upper bound on the maximum achievable error exponent of any such coding scheme. If we consider the Binary Symmetric and the Z families of channels this bound is much lower than Burnashev's exponent. For example, in the case of Binary Symmetric Channels this bound has a slope that vanishes at capacity. This is to be compared with our previous result that demonstrates the existence of coding schemes that achieve Burnashev's exponent (that has a nonzero slope at capacity) even though the channel is revealed neither to the transmitter nor to the receiver. Hence, the present result suggests that, in terms of error exponent, a good universal feedback scheme entangles channel estimation with information delivery, rather than separating them

Large Deviations of the Maximum Eigenvalue in Wishart Random Matrices

We compute analytically the probability of large fluctuations to the left of the mean of the largest eigenvalue in the Wishart (Laguerre) ensemble of positive definite random matrices. We show that the probability that all the eigenvalues of a (N x N) Wishart matrix W=X^T X (where X is a rectangular M x N matrix with independent Gaussian entries) are smaller than the mean value =N/c decreases for large N as $\sim \exp[-\frac{\beta}{2}N^2 \Phi_{-}(\frac{2}{\sqrt{c}}+1;c)]$, where \beta=1,2 correspond respectively to real and complex Wishart matrices, c=N/M < 1 and \Phi_{-}(x;c) is a large deviation function that we compute explicitly. The result for the Anti-Wishart case (M < N) simply follows by exchanging M and N. We also analytically determine the average spectral density of an ensemble of constrained Wishart matrices whose eigenvalues are forced to be smaller than a fixed barrier. The numerical simulations are in excellent agreement with the analytical predictions.Comment: Published version. References and appendix adde

Secret Sharing over Fast-Fading MIMO Wiretap Channels

Secret sharing over the fast-fading MIMO wiretap channel is considered. A source and a destination try to share secret information over a fast-fading MIMO channel in the presence of a wiretapper who also makes channel observations that are different from but correlated to those made by the destination. An interactive authenticated unrestricted public channel is also available for use by the source and destination in the secret sharing process. This falls under the "channel-type model with wiretapper" considered by Ahlswede and Csiszar. A minor extension of their result (to continuous channel alphabets) is employed to evaluate the key capacity of the fast-fading MIMO wiretap channel. The effects of spatial dimensionality provided by the use of multiple antennas at the source, destination, and wiretapper are then investigated.Comment: Revision submitted to EURASIP Journal on Wireless Communications and Networking, Special Issue on Wireless Physical Layer Security, Sept. 2009. v.3: Fixes to proofs. Matthieu Bloch added as co-author for contributions to proof