Presupposition, perceptional relativity and translation theory

The intertwining of assertions and presuppositions in utterances affects the way a text is perceived in the source language (SL) and the target language (TL). Presuppositions can be thought of as shared assumptions that form the background of the asserted meaning. To translate presuppositions as assertions, or vice versa, can distort the thematic meaning of the SL text and produce a text with a different information structure. Since a good translation is not simply concerned with transferring the propositional content of the SL text, but also its other semantic and pragmatic components, including thematic meaning, a special attention should be accorded to the translation of presupposition. This article examines the intrinsic relation between presupposition and thematic meaning, why the concept is relevant to translation theory, and how presupposition can affect the structure and understanding of discourse. Unshared presuppositions are major obstacles in translation, as cultural concepts may be conveyed through expressions that yield presuppositions. To attain an optimal proximity to the SL text, presupposition needs to be singled out as a distinct aspect of meaning, and distinctions need to be made between definite and indefinite meaning, topic and comment, topic and focus, presupposition and entailment, and presupposition and implicature

Capacity Region of the Broadcast Channel with Two Deterministic Channel State Components

This paper establishes the capacity region of a class of broadcast channels with random state in which each channel component is selected from two possible functions and each receiver knows its state sequence. This channel model does not fit into any class of broadcast channels for which the capacity region was previously known and is useful in studying wireless communication channels when the fading state is known only at the receivers. The capacity region is shown to coincide with the UV outer bound and is achieved via Marton coding.Comment: 5 pages, 3 figures. Submitted to ISIT 201

The Relay-Eavesdropper Channel: Cooperation for Secrecy

This paper establishes the utility of user cooperation in facilitating secure wireless communications. In particular, the four-terminal relay-eavesdropper channel is introduced and an outer-bound on the optimal rate-equivocation region is derived. Several cooperation strategies are then devised and the corresponding achievable rate-equivocation region are characterized. Of particular interest is the novel Noise-Forwarding (NF) strategy, where the relay node sends codewords independent of the source message to confuse the eavesdropper. This strategy is used to illustrate the deaf helper phenomenon, where the relay is able to facilitate secure communications while being totally ignorant of the transmitted messages. Furthermore, NF is shown to increase the secrecy capacity in the reversely degraded scenario, where the relay node fails to offer performance gains in the classical setting. The gain offered by the proposed cooperation strategies is then proved theoretically and validated numerically in the additive White Gaussian Noise (AWGN) channel.Comment: 33 pages, submitted to IEEE Transactions on Information Theor

Are Slepian-Wolf Rates Necessary for Distributed Parameter Estimation?

We consider a distributed parameter estimation problem, in which multiple terminals send messages related to their local observations using limited rates to a fusion center who will obtain an estimate of a parameter related to observations of all terminals. It is well known that if the transmission rates are in the Slepian-Wolf region, the fusion center can fully recover all observations and hence can construct an estimator having the same performance as that of the centralized case. One natural question is whether Slepian-Wolf rates are necessary to achieve the same estimation performance as that of the centralized case. In this paper, we show that the answer to this question is negative. We establish our result by explicitly constructing an asymptotically minimum variance unbiased estimator (MVUE) that has the same performance as that of the optimal estimator in the centralized case while requiring information rates less than the conditions required in the Slepian-Wolf rate region.Comment: Accepted in Allerton 201