Topics: 5G communications and architectures; Radio resource allocation/management; Spectrum auctions/management
Authors: Abishek Sankararaman (The University of Texas at Austin, USA); Jeong-woo Cho (KTH Royal Institute of Technology, Sweden); Francois Baccelli (UT Austin & The University of Texas at Austin, USA)
Presenter Bio: Abishek is currently a PhD student in the Department of Electrical and
Computer Engineering at the University of Texas at Austin. His interests
are in Stochastic Geometry and Dynamics with applications in wireless
and social networks. Prior to starting at UT Austin, he received a
Bachelors and Masters degree in Electrical Engineering from Indian
Institute of Technology Madras.
Abstract: The development of mobile virtual network operators, where multiple
wireless technologies (e.g. 3G and 4G) or operators with non-overlapping
bandwidths are pooled and shared is expected to provide enhanced
service with broader coverage, without incurring additional
infrastructure cost. However, their emergence poses an unsolved question
on how to harness such a technology and bandwidth diversity. This paper
addresses one of the simplest questions in this class, namely, the
issue of associating each mobile to one of those bandwidths.
Intriguingly, this association issue is intrinsically distinct from
those in traditional networks. We first propose a generic stochastic
geometry model lending itself to analyzing a wide class of association
policies exploiting various information on the network topology, e.g.
received pilot powers and fading values. This model firstly paves the
way for tailoring and designing an optimal association scheme to
maximize any performance metric of interest (such as the probability of
coverage) subject to the information known about the network. In this
class of optimal association, we prove a result that the performance
improves as the information known about the network increases. Secondly,
this model is used to quantify the performance of any arbitrary
association policy and not just the optimal association policy. We
propose a simple policy called the Max-Ratio which is not-parametric,
i.e. it dispenses with the statistical knowledge of base station
deployments commonly used in stochastic geometry models. We also prove
that this simple policy is optimal in a certain limiting regime of the
wireless environment. Our analytical results are combined with
simulations to compare these policies with basic schemes, which provide
insights into (i) a practical compromise between performance gain and
cost of estimating information and; (ii) the selection of association
schemes under environments with different propagation models, i.e.
path-loss exponents.
