Abstract:
In recent years, access-points have been densely
placed at public spaces. Users can each select an access-point
from among such access-points so as to enhance communication
quality. Access-point selection methods have thus become an
important technical issue. This paper proposes a joint accesspoint
and channel selection method using Markov approximation,
which adapt to dynamic changes in network conditions. Markov
approximation is a distributed optimization framework, where
a network is optimized by individual behavior of users forming
a time-reversible continuous-time Markov chain. Our method
provides an optimal access-point and channel selection strategy
according to a time-reversible continuous-time Markov chain,
aiming at maximizing the total throughput of users. Simulation
experiments demonstrate the effectiveness of the proposed
method.
