, "The capacity of a channel with arbitrarily varying channel probability functions and binary output alphabet," Z. Wahrscheinlichkeitstheorie Verw. Gebiete, vol. 15, pp. 186--194, 1970.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... and state constraint , for the average probability of error, is given by if if (119) Furthermore, if , a strong converse holds so that (120) Although exhibits a dichotomy similar to the capacity of the AVC (5) cf. 57) a proof of Theorem 15 using Ahlswede s elimination technique [7] is not apparent. Its proof in [50] is based on a straightforward albeit more computational approach akin to that in [48] The direct part uses a code with codewords chosen at random from an dimensional spheres of radius and selectively identified as in [48] Interestingly, simple minimum ....

, "Elimination of correlation in random codes for arbitrarily varying channels," Z. Wahrscheinlichkeitstheorie Verw. Gebiete, vol. 44, pp. 159--175, 1978.

....and decoder. For instance, such a resource allows the use of spread spectrum techniques in combating jammer interference [117] In fact, access to such a source of common randomness can sometimes enable reliable communication at rates that are strictly larger than those achievable without it [6], 48] The capacity, reliability function, and error exponent for a given model will also depend on the precise notion of reliable communication adopted by the system designer with regard to the decoding error probability. For a given system the error probability will, in general, depend on the ....

....to both transmitter and receiver, will be assumed to be also finite unless otherwise stated. The probability of receiving , when is transmitted and is the channel state sequence, is given by (5) The standard AVC model introduced in [31] and subsequently studied by several authors (e.g. 2] [6], 10] 20] 45] assumes that the transmitter and receiver are unaware of the actual state sequence which governs a transmission. In the same vein, the selector of the state sequence , is ignorant of the actual message transmitted. However, the state selector is assumed to know the code ....

[Article contains additional citation context not shown here]

, "Elimination of correlation in random codes for arbitrarily varying channels," Z. Wahrscheinlichkeitstheorie Verw. Gebiete, vol. 44, pp. 159--175, 1978.

....An exponential cost function can be more appropriate than a linear function if the processing cost for decoding is signi cant or if bu er over ow caused by long codewords is important. For further discussion of exponential cost functions, see Humblet [7] Blumer and McEliece [2] the author [4], and references in these papers. A uni ed and extended treatment of the material in [3] and [4] is given by Acz el and Dar oczy [1, pp.156 172] For exponential costs, the R enyi entropy plays a role in the coding theorem that is similar to the role of the Shannon entropy for a linear cost ....

....cost for decoding is signi cant or if bu er over ow caused by long codewords is important. For further discussion of exponential cost functions, see Humblet [7] Blumer and McEliece [2] the author [4] and references in these papers. A uni ed and extended treatment of the material in [3] and [4] is given by Acz el and Dar oczy [1, pp.156 172] For exponential costs, the R enyi entropy plays a role in the coding theorem that is similar to the role of the Shannon entropy for a linear cost function. In an interesting recent paper, Csisz ar [6] examines a di erent kind of coding problem for ....

[Article contains additional citation context not shown here]

, Denition of entropy by means of a coding problem, Z. Wahrscheinlichkeitstheorie verw. Geb. 6 (1966), 113-118.

....and for all messages; a less stringent requirement is that the error probability be small only as an (arithmetic) average over the message set. While these two different performance criteria yield the same capacity for a known channel, in the presence of a jammer the capacities may be different [20]. Rather than requiring the error probability to be small for every jammer strategy, we may average it over the set of all strategies with respect to a given prior. This Bayesian approach gives another notion of reliable communication, with yet another definition of capacity. The notions of ....

....of error will lead to a more stringent performance criterion than the average probability of error. In the case of known channels, both criteria result in the same capacity values. For certain unknown channels, however, these two criteria can yield different capacity results, as will be seen below [20]. For certain unknown channels, an improvement in performance can be obtained by using a randomized code. A randomized code constitutes a communication technique, the implementation of which requires the availability of a common source of randomness at the transmitter and receiver; the encoder ....

[Article contains additional citation context not shown here]

, "The capacity of a channel with arbitrarily varying channel probability functions and binary output alphabet," Z. Wahrscheinlichkeitstheorie Verw. Gebiete, vol. 15, pp. 186--194, 1970.

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