We consider the problem of channel coding over multiterminal state-dependent channels in which neither transmitters nor receivers but only a helper node has a non-causal knowledge of the state. Such channel models arise in many emerging communication schemes. We start by investigating the parallel state-dependent channel with the same but differently scaled state corrupting the receivers. A cognitive helper knows the state in a non-causal manner and wishes to mitigate the interference that impacts the transmission between two transmit–receive pairs. Outer and inner bounds are derived. In our analysis, the channel parameters are partitioned into various cases, and segments on the capacity region boundary are characterized for each case. Furthermore, we show that for a particular set of channel parameters, the capacity region is entirely characterized. In the second part of this work, we address a similar scenario, but now each channel is corrupted by an independent state. We derive an inner bound using a coding scheme that integrates single-bin Gel’fand–Pinsker coding and Marton’s coding for the broadcast channel. We also derive an outer bound and further partition the channel parameters into several cases for which parts of the capacity region boundary are characterized.

A double-sided variant of the information bottleneck method is considered. Let $(\mathsf{X},\mathsf{Y})$ be a bivariate source characterized by a joint pmf ${\mathsf{P}}_{\mathsf{X}\mathsf{Y}}$. The problem is to find two independent channels ${\mathsf{P}}_{\mathsf{U}|\mathsf{X}}$ and ${\mathsf{P}}_{\mathsf{V}|\mathsf{Y}}$ (setting the Markovian structure $\mathsf{U}\to \mathsf{X}\to \mathsf{Y}\to \mathsf{V}$), that maximize $I(\mathsf{U};\mathsf{V})$ subject to constraints on the relevant mutual information expressions: $I(\mathsf{U};\mathsf{X})$ and $I(\mathsf{V};\mathsf{Y})$. For jointly Gaussian $\mathsf{X}$ and $\mathsf{Y}$, we show that Gaussian channels are optimal in the low-SNR regime but not for general SNR. Similarly, it is shown that for a doubly symmetric binary source, binary symmetric channels are optimal when the correlation is low and are suboptimal for high correlations. We conjecture that Z and S channels are optimal when the correlation is 1 (i.e., $\mathsf{X}=\mathsf{Y}$) and provide supporting numerical evidence. Furthermore, we present a Blahut–Arimoto type alternating maximization algorithm and demonstrate its performance for a representative setting. This problem is closely related to the domain of biclustering.

A diamond network is considered in which the central processor is connected, via backhaul noiseless links, to multiple conferencing base stations, which communicate with a single user over a multiple access channel. We propose coding techniques along with lower and upper bounds on the capacity. Our achievability scheme uses a common cloud coding strategy based on the technique proposed by Wand, Wigger, and Zaidi (2018) and extends it beyond two relays. Our upper bounds generalize the method proposed by Bidokhti and Kramer for the two relay diamond network without cooperation (2016) and lead to new bounds for the multiple relay setting. Specializing our upper bounds for the two relay scenario (with cooperation), we provide new bounds and improve state-of-the-art.

We study the problem of coding over a general discrete memoryless broadcast channel controlled by random parameters. The parameters are available at the transmitter in a non-causal manner and are subject to a state masking constraint on the receivers. We derive inner and outer bounds on the achievable region and show that for the special case of Gaussian broadcast channel with private messages, these bounds are tight.

We consider a state-dependent parallel Gaussian channel with independent states and a common cognitive helper, in which two transmitters wish to send independent information to their corresponding receivers over two parallel subchannels. Each channel is corrupted by independent additive Gaussian state. The states are not known to the transmitters nor to the receivers, but known to a helper in a noncausal manner. The helper's goal is to assist a reliable communication by mitigating the state. Outer and inner bounds are derived and segments of the capacity region is characterized for various channel parameters.