A relay channel with orthogonal components in which the destination is affected by an interference signal that is non-causally available only at the source is studied. The interference signal has structure in that it is produced by another transmitter communicating with its own destination. Moreover, the interferer is not willing to adjust its communication strategy to minimize the interference. Knowledge of the interferer's signal may be acquired by the source, for instance, by exploiting HARQ retransmissions on the interferer's link. The source can then utilize the relay not only for communicating its own message, but also for cooperative interference mitigation at the destination by informing the relay about the interference signal. Proposed transmission strategies are based on partial decode-and-forward (PDF) relaying and leverage the interference structure. Achievable schemes are derived for discrete memoryless models, Gaussian and Ricean fading channels. Furthermore, optimal strategies are identified in some special cases. Finally, numerical results bring insight into the advantages of utilizing the interference structure at the source, relay or destination.
We consider a state-dependent three-terminal full-duplex relay channel with the channel states noncausally available at only the source, that is, neither at the relay nor at the destination. This model has application to cooperation over certain wireless channels with asymmetric cognition capabilities and cognitive interference relay channels. We establish lower bounds on the channel capacity for both discrete memoryless (DM) and Gaussian cases. For the DM case, the coding scheme for the lower bound uses techniques of rate-splitting at the source, decode-and-forward (DF) relaying, and a Gel'fand-Pinsker-like binning scheme. In this coding scheme, the relay decodes only partially the information sent by the source. Due to the rate-splitting, this lower bound is better than the one obtained by assuming that the relay decodes all the information from the source, that is, full-DF. For the Gaussian case, we consider channel models in which each of the relay node and the destination node experiences on its link an additive Gaussian outside interference. We first focus on the case in which the links to the relay and to the destination are corrupted by the same interference; and then we focus on the case of independent interferences. We also discuss a model with correlated interferences. For each of the first two models, we establish a lower bound on the channel capacity. The coding schemes for the lower bounds use techniques of dirty paper coding or carbon copying onto dirty paper, interference reduction at the source and decode-and-forward relaying. The results reveal that, by opposition to carbon copying onto dirty paper and its root Costa's initial dirty paper coding (DPC), it may be beneficial in our setup that the informed source uses a part of its power to partially cancel the effect of the interference so that the uninformed relay benefits from this cancellation, and so the source benefits in turn.  Writing on dirty paper, a variation of the standard additive white Gaussian noise (AWGN) channel with the channel output is considered. The Gaussian noise noncausally known at the transmitter does not affect the capacity of the AWGN channel. This is known as WDP property. The WDP property for three Gaussian multiple user channels with known capacity region is established. The achievable rate regions of corresponding discrete channels is proved. Although those regions may be suboptimal in general, they turn out to be optimal for these Gaussian channels. Alternative proofs can be obtained by successive uses of Costa's WDP coding scheme, from which the WDP property can be established for more general noise and state distributions. We study the capacity of a class of state-controlled relay channels with orthogonal channels from the source to the relay and from the source and relay to the destination. The channel states are assumed to be known, non-causally, to only the source. This model is useful for relaying in the context of cognition and certain interference-aware networks. For the discrete memoryless case, we establish lower bounds on the channel capacity. For the memoryless Gaussian case, we establish lower and upper bounds on the channel capacity. The upper bound is strictly better than the cut-set upper bound, and is tight for certain special cases. We consider a relay channel in the presence of interference which is non-causally available only at the source. The interference signal may have structure, for example it could come from another source communicating with its own destination. However, the external interferer is not willing to adjust its communication strategy to minimize the interference and is considered to be fixed. Two approaches are possible to mitigate the interference: exploiting the structure or treating the interference as unstructured. Using these approaches, we establish bounds for the Gaussian relay channel with orthogonal components and discuss to the importance of exploiting the interference structure in multi-terminal scenarios.  We consider a three-terminal state-dependent relay channel with the channel state available non-causally at only the source. Such a model may be of interest for node cooperation in the framework of cognition, i.e., collaborative signal transmission involving cognitive and non-cognitive radios. We study the capacity of this communication model. One principal problem in this setup is caused by the relay's not knowing the channel state. In the discrete memoryless (DM) case, we establish lower bounds on channel capacity. For the Gaussian case, we derive lower and upper bounds on the channel capacity. The upper bound is strictly better than the cut-set upper bound. We show that one of the developed lower bounds comes close to the upper bound, asymptotically, for certain ranges of rates. We generalize the Gel'fand-Pinsker model to encompass the setup of a memoryless multiple-access channel (MAC). According to this setup, only one of the encoders knows the state of the channel (noncausally), which is also unknown to the receiver. Two independent messages are transmitted: a common message and a message transmitted by the informed encoder. We find explicit characterizations of the capacity region with both noncausal and causal state information. Further, we study the noise-free binary case, and we also apply the general formula to the Gaussian case with noncausal channel state information, under an individual power constraint as well as a sum power constraint. In this case, the capacity region is achievable by a generalized writing-on-dirty-paper scheme.