In many wireless networks, link strengths are affected by many topological
factors such as different distances, shadowing and inter-cell interference,
thus resulting in some links being generally stronger than other links. From an
information theoretic point of view, accounting for such topological aspects
has remained largely unexplored, despite strong indications that such aspects
can crucially affect transceiver and feedback design, as well as the overall
performance.
The work here takes a step in exploring this interplay between topology,
feedback and performance. This is done for the two user broadcast channel with
random fading, in the presence of a simple two-state topological setting of
statistically strong vs. weaker links, and in the presence of a practical
ternary feedback setting of alternating channel state information at the
transmitter (alternating CSIT) where for each channel realization, this CSIT
can be perfect, delayed, or not available.
In this setting, the work derives generalized degrees-of-freedom bounds and
exact expressions, that capture performance as a function of feedback
statistics and topology statistics. The results are based on novel topological
signal management (TSM) schemes that account for topology in order to fully
utilize feedback. This is achieved for different classes of feedback mechanisms
of practical importance, from which we identify specific feedback mechanisms
that are best suited for different topologies. This approach offers further
insight on how to split the effort --- of channel learning and feeding back
CSIT --- for the strong versus for the weaker link. Further intuition is
provided on the possible gains from topological spatio-temporal diversity,
where topology changes in time and across users.Comment: Shorter version will be presented at ISIT 201