Y.-S. Liu and B. L. Hughes, "A new universal random coding bound for the multiple-access channel," IEEE Trans. Inform. Theory, vol. 42, pp. 376--386, Mar. 1996.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....reliability function, randomized code reliability function, and random coding error exponent of a channel. Our survey does not address these important notions LAPIDOTH AND NARAYAN: RELIABLE COMMUNICATION UNDER CHANNEL UNCERTAINTY 2153 for which we direct the reader to [43] 44] 46] 64] 65] [95], 115] 116] and references therein. In the situations considered above, quite often the selection of codes is restricted in that the transmitted codewords must satisfy appropriate input constraints. Let be a nonnegativevalued function on , and let (20) where, for convenience, we assume that ....

.... Decoding: Loosely speaking, a sequence of codes is universal for a family of channels if it achieves the same random coding error exponent as the maximumlikelihood decoder without requiring knowledge of the specific channel in the family over which transmission takes place [44] 60] 92] [95], 98] 103] 129] We now make this notion precise. Let denote a sequence of sets, with . Consider a randomized encoder whose codewords are drawn independently and uniformly from as in (77) Let denote a maximum likelihood receiver for the encoder and the channel as in (86) and (91) As in ....

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Y.-S. Liu and B. L. Hughes, "A new universal random coding bound for the multiple-access channel," IEEE Trans. Inform. Theory, vol. 42, pp. 376--386, Mar. 1996.

....depending on , and ; that exponent is positive for each with the property that for determined by (VI.16) with the given and , VI.17) is satisfied with strict inequalities. Pokorny and Wallmeier [71] used the proof technique of Theorem IV.1 with a decoder maximizing . Recently, Liu and Hughes [62] improved upon the exponent of [71] using a similar technique but with decoder minimizing . The maximum mutual information and minimum conditional entropy decoding rules are equivalent for DMC s with codewords of the same type but not in the MAC context; by the result of [62] minimum ....

....Liu and Hughes [62] improved upon the exponent of [71] using a similar technique but with decoder minimizing . The maximum mutual information and minimum conditional entropy decoding rules are equivalent for DMC s with codewords of the same type but not in the MAC context; by the result of [62], minimum conditional entropy appears the better one. VII. EXTENSIONS While the type concept is originally tailored to memoryless models, it has extensions suitable for more complex models, as well. So far, such extensions proved useful mainly in the context of source coding and hypothesis ....

Y. S. Liu and B. L. Hughes, "A new universal random coding bound for the multiple-access channel," IEEE Trans. Inform. Theory, vol. 42, pp. 376--386, 1996.

....[13, pg. 25] 2 19 V. Examples In this section, we calculate the exponents of Section III for two multiple access channels. These two examples show that strict inequality can hold in (18) and (20) The method by which these exponents are calculated is described in detail in Appendix A of [11]. A. Example 1 Consider a discrete memoryless MAC with X = Y = Z = f0; 1g and the transition probability given in Table I. As shown in [4, pg. 287] the capacity region of this channel is C = f(RX ; R Y ) RX R Y 1; RX ; R Y 0g : Time sharing is needed to attain certain points in C, as these ....

Y. S. Liu and B. L. Hughes, "A new universal random coding bound for the multiple-access channel," Dept. of Elec. Comp. Eng., The Johns Hopkins University, Tech. Rep. 95-02, Jan. 1995.

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