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Dirty paper coding

About: Dirty paper coding is a research topic. Over the lifetime, 814 publications have been published within this topic receiving 37097 citations.


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Journal ArticleDOI
TL;DR: This correspondence shows that solutions to themultiple description coding problem and the broadcast channel coding problem share a common encoding procedure: successive source encoding, and shows that Marton's encoding scheme can be viewed as a multiple description coding procedure.
Abstract: In this correspondence, we show that solutions to the multiple description coding problem and the broadcast channel coding problem share a common encoding procedure: successive source encoding. We use this connection as the basis for establishing connections between the achievable multiple description rate region and Marton's region for broadcast channels. Specifically, we show that Marton's encoding scheme can be viewed as a multiple description coding procedure. We also explore the dual problem, namely, the relationship between successive channel decoding in multiple access communication and distributed source coding. By illuminating these connections to multiple description, we hope to motivate a solution to what remains a mostly unsolved problem

44 citations

Journal ArticleDOI
TL;DR: This paper examines near-capacity dirty-paper code designs based on source-channel coding and synergistically combines trellis-coded quantization (TCQ) with both systematic and nonsystematic irregular repeat-accumulate (IRA) codes so that they work together as well as they do individually.
Abstract: This paper examines near-capacity dirty-paper code designs based on source-channel coding. We first point out that the performance loss in signal-to-noise ratio (SNR) in our code designs can be broken into the sum of the packing loss from channel coding and a modulo loss, which is a function of the granular loss from source coding and the target dirty-paper coding rate (or SNR). We then examine practical designs by combining trellis-coded quantization (TCQ) with both systematic and nonsystematic irregular repeat-accumulate (IRA) codes. Like previous approaches, we exploit the extrinsic information transfer (EXIT) chart technique for capacity-approaching IRA code design; but unlike previous approaches, we emphasize the role of strong source coding to achieve as much granular gain as possible using TCQ. Instead of systematic doping, we employ two relatively shifted TCQ codebooks, where the shift is optimized (via tuning the EXIT charts) to facilitate the IRA code design. Our designs synergistically combine TCQ with IRA codes so that they work together as well as they do individually. By bringing together TCQ (the best quantizer from the source coding community) and EXIT chart-based IRA code designs (the best from the channel coding community), we are able to approach the theoretical limit of dirty-paper coding. For example, at 0.25 bit per symbol (b/s), our best code design (with 2048-state TCQ) performs only 0.630 dB away from the Shannon capacity.

44 citations

Journal ArticleDOI
TL;DR: Dirty-paper coding makes an analogy to the problem of writing on dirty paper, where the reader cannot nominally distinguish dirt from ink, and in the field of information hiding, theoretical bounds as well as practical watermarking schemes have been found.
Abstract: Dirty-paper coding makes an analogy to the problem of writing on dirty paper, where the reader cannot nominally distinguish dirt from ink. There are many scenarios where this result may be applied. In the field of information hiding (or watermarking), theoretical bounds as well as practical watermarking schemes have been found. Another important application of dirty-paper coding is for a multiuser channel wherein a multiple-antenna transmitter is communicating with multiple users.

43 citations

Journal ArticleDOI
TL;DR: In this paper, the authors consider transmission over the ergodic fading multiple-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full information at receiver and show that a gain is easily achieved by appropriately exploiting the information.
Abstract: We consider transmission over the ergodic fading multiple-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full information at the receiver. Over the equivalent non-fading channel, capacity has recently been shown to be achievable using transmission schemes that were designed for the "dirty paper" channel. We focus on a similar "fading paper" model. The evaluation of the fading paper capacity is difficult to obtain. We confine ourselves to the linear-assignment capacity, which we define, and use convex analysis methods to prove that its maximizing distribution is Gaussian. We compare our fading-paper transmission to an application of dirty paper coding that ignores the partial state information and assumes the channel is fixed at the average fade. We show that a gain is easily achieved by appropriately exploiting the information. We also consider a cooperative upper bound on the sum-rate capacity as suggested by Sato. We present a numeric example that indicates that our scheme is capable of realizing much of this upper bound.

43 citations

Posted Content
TL;DR: This work considers transmission over the ergodic fading multiple-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full Information at the receiver and uses convex analysis methods to prove that its maximizing distribution is Gaussian.
Abstract: We consider transmission over the ergodic fading multi-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full information at the receiver. Over the equivalent {\it non}-fading channel, capacity has recently been shown to be achievable using transmission schemes that were designed for the ``dirty paper'' channel. We focus on a similar ``fading paper'' model. The evaluation of the fading paper capacity is difficult to obtain. We confine ourselves to the {\it linear-assignment} capacity, which we define, and use convex analysis methods to prove that its maximizing distribution is Gaussian. We compare our fading-paper transmission to an application of dirty paper coding that ignores the partial state information and assumes the channel is fixed at the average fade. We show that a gain is easily achieved by appropriately exploiting the information. We also consider a cooperative upper bound on the sum-rate capacity as suggested by Sato. We present a numeric example that indicates that our scheme is capable of realizing much of this upper bound.

42 citations

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202217
202121
202013
201926
201823