2,330 research outputs found
Efficient wireless packet scheduling in a non-cooperative environment: Game theoretic analysis and algorithms
In many practical scenarios, wireless devices are autonomous and thus, may exhibit non-cooperative behaviors due to self-interests. For instance, a wireless cellular device may be programmed to report bogus channel information to gain resource allocation advantages. Such non-cooperative behaviors are highly probable as the device's software can be modified by the user. In this paper, we first analyze the impact of these rationally selfish behaviors on the performance of packet scheduling algorithms in time-slotted wireless networks. Using a mixed strategy game model, we show that the traditional maximum rate packet scheduling algorithm can cause non-cooperative devices to converge to highly inefficient Nash equilibria, in which the wireless channel resources are significantly wasted. By using a repeated game to enforce cooperation, we further propose a novel game theoretic algorithm that can lead to an efficient equilibrium. © 2010 Elsevier Inc. All rights reserved.postprin
Applications of Repeated Games in Wireless Networks: A Survey
A repeated game is an effective tool to model interactions and conflicts for
players aiming to achieve their objectives in a long-term basis. Contrary to
static noncooperative games that model an interaction among players in only one
period, in repeated games, interactions of players repeat for multiple periods;
and thus the players become aware of other players' past behaviors and their
future benefits, and will adapt their behavior accordingly. In wireless
networks, conflicts among wireless nodes can lead to selfish behaviors,
resulting in poor network performances and detrimental individual payoffs. In
this paper, we survey the applications of repeated games in different wireless
networks. The main goal is to demonstrate the use of repeated games to
encourage wireless nodes to cooperate, thereby improving network performances
and avoiding network disruption due to selfish behaviors. Furthermore, various
problems in wireless networks and variations of repeated game models together
with the corresponding solutions are discussed in this survey. Finally, we
outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference
On the impact of selfish behaviors in wireless packet scheduling
In many practical scenarios, wireless devices are autonomous and thus, may exhibit non-cooperative behaviors due to self-interests. For instance, a wireless user may report bogus channel information to gain resource allocation advantages. Such non-cooperative behaviors are practicable as the device's software could be modified by the user. In this paper, we first analyze the impact of these rationally selfish behaviors on the performance of packet scheduling algorithms in time-slotted wireless networks. Using a mixed strategy game theoretic model, we show that the traditional Maximum Rate packet scheduling algorithm can lead non-cooperative users to undesirable Nash equilibriums, in which the wireless channels are used inefficiently. By using repeated game to enforce cooperation, we further propose a novel game theoretic approach that can lead to an efficient equilibrium. ©2008 IEEE.published_or_final_versio
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Joint Scheduling and ARQ for MU-MIMO Downlink in the Presence of Inter-Cell Interference
User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the
core of high rate data-oriented downlink schemes of the next-generation of
cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users
according to their channels vector directions and SINR levels. However, when
scheduling is applied independently in each cell, the inter-cell interference
(ICI) power at each user receiver is not known in advance since it changes at
each new scheduling slot depending on the scheduling decisions of all
interfering base stations. In order to cope with this uncertainty, we consider
the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat
reQuest (ARQ). We develop a game-theoretic framework for this problem and build
on stochastic optimization techniques in order to find optimal scheduling and
ARQ schemes. Particularizing our framework to the case of "outage service
rates", we obtain a scheme based on adaptive variable-rate coding at the
physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then,
we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ)
that is able to achieve a throughput performance arbitrarily close to the
"genie-aided service rates", with no need for a genie that provides
non-causally the ICI power levels. The novel HARQ scheme is both easier to
implement and superior in performance with respect to the conventional
combination of adaptive variable-rate coding and ARQ-LLC.Comment: Submitted to IEEE Transactions on Communications, v2: small
correction
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