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Proving capacity for networks without feedback or cooperation usuallyinvolves two fundamental random coding techniques: superposition coding andbinning. Although conceptually very different, these two techniques oftenachieve the same performance, suggesting an underlying similarity. In thiscorrespondence we propose a new random coding technique that generalizessuperposition coding and binning and provides new insight on relationship amongthe two With this new theoretical tool, we derive new achievable regions forthree classical information theoretical models: multi-access channel, broadcastchannel, the interference channel, and show that, unfortunately, it does notimprove over the largest known achievable regions for these cases.

A New Random Coding Technique that Generalizes Superposition Coding and Binning