9,588 research outputs found
Coalitional Games with Overlapping Coalitions for Interference Management in Small Cell Networks
In this paper, we study the problem of cooperative interference management in
an OFDMA two-tier small cell network. In particular, we propose a novel
approach for allowing the small cells to cooperate, so as to optimize their
sum-rate, while cooperatively satisfying their maximum transmit power
constraints. Unlike existing work which assumes that only disjoint groups of
cooperative small cells can emerge, we formulate the small cells' cooperation
problem as a coalition formation game with overlapping coalitions. In this
game, each small cell base station can choose to participate in one or more
cooperative groups (or coalitions) simultaneously, so as to optimize the
tradeoff between the benefits and costs associated with cooperation. We study
the properties of the proposed overlapping coalition formation game and we show
that it exhibits negative externalities due to interference. Then, we propose a
novel decentralized algorithm that allows the small cell base stations to
interact and self-organize into a stable overlapping coalitional structure.
Simulation results show that the proposed algorithm results in a notable
performance advantage in terms of the total system sum-rate, relative to the
noncooperative case and the classical algorithms for coalitional games with
non-overlapping coalitions
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
Matching Theory for Backhaul Management in Small Cell Networks with mmWave Capabilities
Designing cost-effective and scalable backhaul solutions is one of the main
challenges for emerging wireless small cell networks (SCNs). In this regard,
millimeter wave (mmW) communication technologies have recently emerged as an
attractive solution to realize the vision of a high-speed and reliable wireless
small cell backhaul network (SCBN). In this paper, a novel approach is proposed
for managing the spectral resources of a heterogeneous SCBN that can exploit
simultaneously mmW and conventional frequency bands via carrier aggregation. In
particular, a new SCBN model is proposed in which small cell base stations
(SCBSs) equipped with broadband fiber backhaul allocate their frequency
resources to SCBSs with wireless backhaul, by using aggregated bands. One
unique feature of the studied model is that it jointly accounts for both
wireless channel characteristics and economic factors during resource
allocation. The problem is then formulated as a one-to-many matching game and a
distributed algorithm is proposed to find a stable outcome of the game. The
convergence of the algorithm is proven and the properties of the resulting
matching are studied. Simulation results show that under the constraints of
wireless backhauling, the proposed approach achieves substantial performance
gains, reaching up to compared to a conventional best-effort approach.Comment: In Proc. of the IEEE International Conference on Communications
(ICC), Mobile and Wireless Networks Symposium, London, UK, June 201
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
A framework for smart production-logistics systems based on CPS and industrial IoT
Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems
Scarcity may promote cooperation in populations of simple agents
In the study of the evolution of cooperation, resource limitations are
usually assumed just to provide a finite population size. Recently, however, it
has been pointed out that resource limitation may also generate dynamical
payoffs able to modify the original structure of the games. Here we study
analytically a phase transition from a homogeneous population of defectors when
resources are abundant to the survival of unconditional cooperators when
resources reduce below a threshold. To this end, we introduce a model of simple
agents, with no memory or ability of recognition, interacting in well-mixed
populations. The result might shed light on the role played by resource
constraints on the origin of multicellularity.Comment: 5 pages, 2 figure
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