Abstract:
We analyze a network of nodes in which pairs communicate over a shared wireless
medium. We are interested in the maximum total aggregate traffic flow
possible as given by the number of users multiplied by their data rate. Our
model differs substantially from the many existing approaches in that the
channel connections in our network are entirely random: we assume that, rather
than being governed by geometry and a decay-versus-distance law, the
strengths of the connections between nodes are drawn independently from a common
distribution. Such a model is appropriate for environments where the first
order effect that governs the signal strength at a receiving node is a random
event (such as the existence of an obstacle), rather than the distance from the
transmitter.
We show that the aggregate traffic flow as a function of the number of nodes
"n" is a strong function of the channel distribution. In particular,
for certain distributions the aggregate traffic flow is at least
n/(\log n)^d for some d>0, which is significantly larger
than the n^{1/2} results obtained for many geometric models. Our
results provide guidelines for the connectivity that is needed for large
aggregate traffic. We show how our model and distance-based models can
be related in some cases.
Status:
Submitted to IEEE Transactions on Information Theory, June 2005.
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