  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.
