Noisy DPC and Application to a Cognitive Channel

dc.creatorPeng, Yong
dc.creatorRajan, Dinesh
dc.date2009-01-19
dc.date.accessioned2026-07-07T12:32:04Z
dc.date.available2026-07-07T12:32:04Z
dc.descriptionIn this paper, we first consider a channel that is contaminated by two independent Gaussian noises $S ~ N(0,Q)$ and $Z_0 ~ N(0,N_0)$. The capacity of this channel is computed when independent noisy versions of $S$ are known to the transmitter and/or receiver. It is shown that the channel capacity is greater then the capacity when $S$ is completely unknown, but is less then the capacity when $S$ is perfectly known at the transmitter or receiver. For example, if there is one noisy version of $S$ known at the transmitter only, the capacity is $0.5log(1+P/(Q(N_1/(Q+N_1))+N_0))$, where $P$ is the input power constraint and $N_1$ is the power of the noise corrupting $S$. We then consider a Gaussian cognitive interference channel (IC) and propose a causal noisy dirty paper coding (DPC) strategy. We compute the achievable region using this noisy DPC strategy and quantify the regions when it achieves the upper bound on the rate.
dc.description5 pages, 5 figures, submitted to IEEE ISIT 2009
dc.identifierhttps://arxiv.org/abs/0901.2934
dc.identifierhttp://arxiv.org/abs/0901.2934
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/216662
dc.subjectInformation Theory
dc.titleNoisy DPC and Application to a Cognitive Channel
dc.typetext

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