1,371 research outputs found
Monotone properties of random geometric graphs have sharp thresholds
Random geometric graphs result from taking uniformly distributed points
in the unit cube, , and connecting two points if their Euclidean
distance is at most , for some prescribed . We show that monotone
properties for this class of graphs have sharp thresholds by reducing the
problem to bounding the bottleneck matching on two sets of points
distributed uniformly in . We present upper bounds on the threshold
width, and show that our bound is sharp for and at most a sublogarithmic
factor away for . Interestingly, the threshold width is much sharper for
random geometric graphs than for Bernoulli random graphs. Further, a random
geometric graph is shown to be a subgraph, with high probability, of another
independently drawn random geometric graph with a slightly larger radius; this
property is shown to have no analogue for Bernoulli random graphs.Comment: Published at http://dx.doi.org/10.1214/105051605000000575 in the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
Optimal Power Allocation over Multiple Identical Gilbert-Elliott Channels
We study the fundamental problem of power allocation over multiple
Gilbert-Elliott communication channels. In a communication system with time
varying channel qualities, it is important to allocate the limited transmission
power to channels that will be in good state. However, it is very challenging
to do so because channel states are usually unknown when the power allocation
decision is made. In this paper, we derive an optimal power allocation policy
that can maximize the expected discounted number of bits transmitted over an
infinite time span by allocating the transmission power only to those channels
that are believed to be good in the coming time slot. We use the concept belief
to represent the probability that a channel will be good and derive an optimal
power allocation policy that establishes a mapping from the channel belief to
an allocation decision.
Specifically, we first model this problem as a partially observable Markov
decision processes (POMDP), and analytically investigate the structure of the
optimal policy. Then a simple threshold-based policy is derived for a
three-channel communication system. By formulating and solving a linear
programming formulation of this power allocation problem, we further verified
the derived structure of the optimal policy.Comment: 10 pages, 7 figure
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