The discrete memoryless multiple-access channel with cribbing encoders

Willems, F.M.J.; Meulen, E. van der

doi:10.1109/tit.1985.1057042

Cited by 205 publications

(205 citation statements)

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“…and van der Meulen also considered a limiting case of cooperation where the encoders "crib" from each other, that is, they learn each others' codewords before the next transmission [4]. Several scenarios regarding which encoder(s) crib, and how much of the codewords the encoders learn, are treated and the capacity region for each case is obtained in [4].…”

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confidence: 99%

“…Several scenarios regarding which encoder(s) crib, and how much of the codewords the encoders learn, are treated and the capacity region for each case is obtained in [4]. The capacity of such channels are an upper bound to the rates achievable by cooperative schemes, since in the case of cribbing encoders, the sharing of information comes for free, i.e., the transmitters do not allocate any resources such as powers, to establish common information.…”

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Power Control for Fading Cooperative Multiple Access Channels

Kaya

Ulukuş

2007

IEEE Trans. Wireless Commun.

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Abstract-For a fading Gaussian multiple access channel with user cooperation, we obtain the power allocation policies that maximize the average rates achievable by block Markov superposition coding, subject to average power constraints. The optimal policies result in a coding scheme that is simpler than the one for a general multiple access channel with generalized feedback. This simpler coding scheme also leads to the possibility of formulating an otherwise non-concave optimization problem as a concave one. Using the perfect channel state information available at the transmitters to adapt the powers, we demonstrate gains over the achievable rates for existing cooperative systems.

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confidence: 99%

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Power Control for Fading Cooperative Multiple Access Channels

Kaya

Ulukuş

2007

IEEE Trans. Wireless Commun.

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“…In the n th block, we simply encode X {4} [n − 1] and directly communicate it with receiver 4 and the private receivers. Upon receiving all the n blocks at the receivers, we perform backward decoding [11].…”

Section: A Block Markov Encoding Schemementioning

confidence: 99%

A block Markov encoding scheme for broadcasting nested message sets

Bidokhti¹,

Prabhakaran²,

Diggavi

2013

2013 IEEE International Symposium on Information Theory

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Abstract-Encoding schemes for broadcasting two nested message sets are studied. We start with a simple class of deterministic broadcast channels for which (variants of) linear superposition coding are optimal in several cases [1], [2]. Such schemes are sub-optimal in general, and we propose a block Markov encoding scheme which achieves (for some deterministic channels) rates not achievable by the previous schemes in [1], [2]. We adapt this block Markov encoding scheme to general broadcast channels, and show that it achieves a rate-region which includes the previously known rate-regions 1 .

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“…It is worth mentioning that Lemma 1 is not completely new. Indeed, its variants can be found in [9], [23], and even in 1 The notion of successive refinement is sometimes used in the more restrictive no rate loss scenario.…”

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On the Role of the Refinement Layer in Multiple Description Coding and Scalable Coding

Wang

Zhao

Cuff

et al. 2011

IEEE Trans. Inform. Theory

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Abstract-We clarify the relationship among several existing achievable multiple description rate-distortion regions by investigating the role of refinement layer in multiple description coding. Specifically, we show that the refinement layer in the El Gamal-Cover (EGC) scheme and the Venkataramani-Kramer-Goyal (VKG) scheme can be removed; as a consequence, the EGC region is equivalent to the EGC* region (an antecedent version of the EGC region) while the VKG region (when specialized to the 2-description case) is equivalent to the Zhang-Berger (ZB) region. Moreover, we prove that for multiple description coding with individual and hierarchical distortion constraints, the number of layers in the VKG scheme can be significantly reduced when only certain weighted sum rates are concerned. The role of refinement layer in scalable coding (a special case of multiple description coding) is also studied.

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The discrete memoryless multiple-access channel with cribbing encoders

Cited by 205 publications

References 13 publications

Power Control for Fading Cooperative Multiple Access Channels

Power Control for Fading Cooperative Multiple Access Channels

A block Markov encoding scheme for broadcasting nested message sets

On the Role of the Refinement Layer in Multiple Description Coding and Scalable Coding

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