9,228 research outputs found
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201
Understanding Game Theory via Wireless Power Control
In this lecture note, we introduce the basic concepts of game theory (GT), a
branch of mathematics traditionally studied and applied in the areas of
economics, political science, and biology, which has emerged in the last
fifteen years as an effective framework for communications, networking, and
signal processing (SP). The real catalyzer has been the blooming of all issues
related to distributed networks, in which the nodes can be modeled as players
in a game competing for system resources. Some relevant notions of GT are
introduced by elaborating on a simple application in the context of wireless
communications, notably the power control in an interference channel (IC) with
two transmitters and two receivers.Comment: Accepted for publication as lecture note in IEEE Signal Processing
Magazine, 13 pages, 4 figures. The results can be reproduced using the
following Matlab code: https://github.com/lucasanguinetti/ ln-game-theor
Distributed Channel Assignment in Cognitive Radio Networks: Stable Matching and Walrasian Equilibrium
We consider a set of secondary transmitter-receiver pairs in a cognitive
radio setting. Based on channel sensing and access performances, we consider
the problem of assigning channels orthogonally to secondary users through
distributed coordination and cooperation algorithms. Two economic models are
applied for this purpose: matching markets and competitive markets. In the
matching market model, secondary users and channels build two agent sets. We
implement a stable matching algorithm in which each secondary user, based on
his achievable rate, proposes to the coordinator to be matched with desirable
channels. The coordinator accepts or rejects the proposals based on the channel
preferences which depend on interference from the secondary user. The
coordination algorithm is of low complexity and can adapt to network dynamics.
In the competitive market model, channels are associated with prices and
secondary users are endowed with monetary budget. Each secondary user, based on
his utility function and current channel prices, demands a set of channels. A
Walrasian equilibrium maximizes the sum utility and equates the channel demand
to their supply. We prove the existence of Walrasian equilibrium and propose a
cooperative mechanism to reach it. The performance and complexity of the
proposed solutions are illustrated by numerical simulations.Comment: submitted to IEEE Transactions on Wireless Communicaitons, 13 pages,
10 figures, 4 table
Self-Evaluation Applied Mathematics 2003-2008 University of Twente
This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008
The 5G Cellular Backhaul Management Dilemma: To Cache or to Serve
With the introduction of caching capabilities into small cell networks
(SCNs), new backaul management mechanisms need to be developed to prevent the
predicted files that are downloaded by the at the small base stations (SBSs) to
be cached from jeopardizing the urgent requests that need to be served via the
backhaul. Moreover, these mechanisms must account for the heterogeneity of the
backhaul that will be encompassing both wireless backhaul links at various
frequency bands and a wired backhaul component. In this paper, the
heterogeneous backhaul management problem is formulated as a minority game in
which each SBS has to define the number of predicted files to download, without
affecting the required transmission rate of the current requests. For the
formulated game, it is shown that a unique fair proper mixed Nash equilibrium
(PMNE) exists. Self-organizing reinforcement learning algorithm is proposed and
proved to converge to a unique Boltzmann-Gibbs equilibrium which approximates
the desired PMNE. Simulation results show that the performance of the proposed
approach can be close to that of the ideal optimal algorithm while it
outperforms a centralized greedy approach in terms of the amount of data that
is cached without jeopardizing the quality-of-service of current requests.Comment: Accepted for publication at Transactions on Wireless Communication
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