1,585 research outputs found
Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks
The problem of distributed rate maximization in multi-channel ALOHA networks
is considered. First, we study the problem of constrained distributed rate
maximization, where user rates are subject to total transmission probability
constraints. We propose a best-response algorithm, where each user updates its
strategy to increase its rate according to the channel state information and
the current channel utilization. We prove the convergence of the algorithm to a
Nash equilibrium in both homogeneous and heterogeneous networks using the
theory of potential games. The performance of the best-response dynamic is
analyzed and compared to a simple transmission scheme, where users transmit
over the channel with the highest collision-free utility. Then, we consider the
case where users are not restricted by transmission probability constraints.
Distributed rate maximization under uncertainty is considered to achieve both
efficiency and fairness among users. We propose a distributed scheme where
users adjust their transmission probability to maximize their rates according
to the current network state, while maintaining the desired load on the
channels. We show that our approach plays an important role in achieving the
Nash bargaining solution among users. Sequential and parallel algorithms are
proposed to achieve the target solution in a distributed manner. The
efficiencies of the algorithms are demonstrated through both theoretical and
simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM
Transactions on Networking, part of this work was presented at IEEE CAMSAP
201
A Comprehensive Survey of Potential Game Approaches to Wireless Networks
Potential games form a class of non-cooperative games where unilateral
improvement dynamics are guaranteed to converge in many practical cases. The
potential game approach has been applied to a wide range of wireless network
problems, particularly to a variety of channel assignment problems. In this
paper, the properties of potential games are introduced, and games in wireless
networks that have been proven to be potential games are comprehensively
discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on
Communications, vol. E98-B, no. 9, Sept. 201
Matching Theory for Future Wireless Networks: Fundamentals and Applications
The emergence of novel wireless networking paradigms such as small cell and
cognitive radio networks has forever transformed the way in which wireless
systems are operated. In particular, the need for self-organizing solutions to
manage the scarce spectral resources has become a prevalent theme in many
emerging wireless systems. In this paper, the first comprehensive tutorial on
the use of matching theory, a Nobelprize winning framework, for resource
management in wireless networks is developed. To cater for the unique features
of emerging wireless networks, a novel, wireless-oriented classification of
matching theory is proposed. Then, the key solution concepts and algorithmic
implementations of this framework are exposed. Then, the developed concepts are
applied in three important wireless networking areas in order to demonstrate
the usefulness of this analytical tool. Results show how matching theory can
effectively improve the performance of resource allocation in all three
applications discussed
Many-to-Many Matching Games for Proactive Social-Caching in Wireless Small Cell Networks
In this paper, we address the caching problem in small cell networks from a
game theoretic point of view. In particular, we formulate the caching problem
as a many-to-many matching game between small base stations and service
providers' servers. The servers store a set of videos and aim to cache these
videos at the small base stations in order to reduce the experienced delay by
the end-users. On the other hand, small base stations cache the videos
according to their local popularity, so as to reduce the load on the backhaul
links. We propose a new matching algorithm for the many-to-many problem and
prove that it reaches a pairwise stable outcome. Simulation results show that
the number of satisfied requests by the small base stations in the proposed
caching algorithm can reach up to three times the satisfaction of a random
caching policy. Moreover, the expected download time of all the videos can be
reduced significantly
Joint Access Point Selection and Power Allocation for Uplink Wireless Networks
We consider the distributed uplink resource allocation problem in a
multi-carrier wireless network with multiple access points (APs). Each mobile
user can optimize its own transmission rate by selecting a suitable AP and by
controlling its transmit power. Our objective is to devise suitable algorithms
by which mobile users can jointly perform these tasks in a distributed manner.
Our approach relies on a game theoretic formulation of the joint power control
and AP selection problem. In the proposed game, each user is a player with an
associated strategy containing a discrete variable (the AP selection decision)
and a continuous vector (the power allocation among multiple channels). We
provide characterizations of the Nash Equilibrium of the proposed game, and
present a set of novel algorithms that allow the users to efficiently optimize
their rates. Finally, we study the properties of the proposed algorithms as
well as their performance via extensive simulations.Comment: Revised and Resubmitted to IEEE Transactions on Signal Processin
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