Abstract-A new inner bound on the capacity region of the general index coding problem is established. Unlike most existing bounds that are based on graph theoretic or algebraic tools, the bound relies on a random coding scheme and optimal decoding, and has a simple polymatroidal single-letter expression. The utility of the inner bound is demonstrated by examples that include the capacity region for all index coding problems with up to five messages (there are 9846 nonisomorphic ones).

Abstract-We propose and parameterize an empirical model of the outdoor-to-indoor and indoor-to-indoor distributed (cooperative) radio channel, using experimental data in the 2.4 GHz band. In addition to the well-known physical effects of path loss, shadowing, and fading, we include several new aspects in our model that are specific to multi-user distributed channels: (i) correlated shadowing between different point to point links which has a strong impact on cooperative system performance, (ii) different types of indoor node mobility with respect to the transmitter and/or receiver nodes, implying a distinction between static and dynamic shadowing motivated by the measurement data, and (iii) a small-scale fading distribution that captures more severe fading than given by the Rayleigh distribution.

Abstract-It is shown that simultaneous nonunique decoding is rate-optimal for the general K-sender, L-receiver discrete memoryless interference channel when encoding is restricted to randomly generated codebooks, superposition coding, and time sharing. This result implies that the Han-Kobayashi inner bound for the two-user-pair interference channel cannot be improved simply by using a better decoder such as the maximum likelihood decoder. It also generalizes and extends previous results by Baccelli, El Gamal, and Tse on Gaussian interference channels with point-to-point Gaussian random codebooks and shows that the Cover-van der Meulen inner bound with no common auxiliary random variable on the capacity region of the broadcast channel can be improved to include the superposition coding inner bound simply by using simultaneous nonunique decoding. The key to proving the main result is to show that after a maximal set of messages has been recovered, the remaining signal at each receiver is distributed essentially independently and identically.

The optimal rate region for interference networks is characterized when encoding is restricted to random code ensembles with superposition coding and time sharing. A simple simultaneous nonunique decoding rule, under which each receiver decodes for the intended message as well as the interfering messages, is shown to achieve this optimal rate region regardless of the relative strengths of signal, interference, and noise. This result implies that the Han-Kobayashi bound, the best known inner bound on the capacity region of the two-user-pair interference channel, cannot be improved merely by using the optimal maximum likelihood decoder. Index Termsnetwork information theory, interference network, superposition coding, maximum likelihood decoding, simultaneous decoding, Han-Kobayashi bound.

Abstract-An inner bound to the capacity region of a class of deterministic interference channels with three user pairs is presented. The key idea is to simultaneously decode the combined interference signal and the intended message at each receiver. It is shown that this interference-decoding inner bound is tight under certain strong interference conditions. The inner bound is also shown to strictly contain the inner bound obtained by treating interference as noise, which includes interference alignment for deterministic channels. The gain comes from judicious analysis of the number of combined interference sequences in different regimes of input distributions and message rates. Finally, the inner bound is generalized to the case where each channel output is observed through a noisy channel.Index Terms-Capacity region, deterministic model, interference alignment, interference channel, multiuser information theory, network information theory, simultaneous non-unique decoding.