A New Random Coding Technique that Generalizes Superposition Coding and Binning

Proving capacity for networks without feedback or cooperation usually involves two fundamental random coding techniques: superposition coding and binning. Although conceptually very different, these two techniques often achieve the same performance, suggesting an underlying similarity. In this correspondence we propose a new random coding technique that generalizes superposition coding and binning and provides new insight on relationship among the two With this new theoretical tool, we derive new achievable regions for three classical information theoretical models: multi-access channel, broadcast channel, the interference channel, and show that, unfortunately, it does not improve over the largest known achievable regions for these cases.

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