Universal delay estimation for discrete channels

The use of information theory concepts for universal estimation of delay for classes of discrete channels is discussed. The problem is presented as one of hypothesis testing. Although the channel statistics are not known, for large enough signal duration, the exponent of the average error probability is equal to that associated with the optimal maximum-likelihood (ML) decision procedure which utilizes full knowledge of the channel parameters. Two categories of problems are discussed: the single-channel problem, where the random transmitted signal is known to the receiver, and the two-sensor problem, where the random signal is unknown.

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