40,020 research outputs found
Hybrid Decision Algorithm for Access Selection in Multi-operator Networks
In this paper, we propose a hybrid decision algorithm for the selection of
the access in multi-operator networks environment, where competing operators
share their radio access networks to meet traffic and data rate demands. The
proposed algorithm guarantees the user satisfaction and a global gain for all
cooperating operators. Simulation results prove the efficiency of the proposed
scheme and show that the cooperation between operators achieves benefits to
both users and operators; user acceptance as well as the operator resource
utilization and the operator revenue increase.Comment: WCNC, Istanbul : Turkey (2014
Best Operator Policy in a Heterogeneous Wireless Network
In this paper, we perform a business analysis of our hybrid decision
algorithm for the selection of the access in a multi-operator networks
environment. We investigate the ability of the operator to express his strategy
and influence the access selection for his client. In this purpose, we study
two important coefficients of the previously proposed cost function, Wu and
Wop, and show that the value of these coefficients is not arbitrary. Simulation
results show that the value of the ratio Wu/Wop enables a selection decision
respecting operator's strategy and it affects the achieved global profit for
all cooperating operators.Comment: ICeND, Beyrouth : Lebanon (2014
Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)
Recently, increasing works have proposed to drive evolutionary algorithms
using machine learning models. Usually, the performance of such model based
evolutionary algorithms is highly dependent on the training qualities of the
adopted models. Since it usually requires a certain amount of data (i.e. the
candidate solutions generated by the algorithms) for model training, the
performance deteriorates rapidly with the increase of the problem scales, due
to the curse of dimensionality. To address this issue, we propose a
multi-objective evolutionary algorithm driven by the generative adversarial
networks (GANs). At each generation of the proposed algorithm, the parent
solutions are first classified into real and fake samples to train the GANs;
then the offspring solutions are sampled by the trained GANs. Thanks to the
powerful generative ability of the GANs, our proposed algorithm is capable of
generating promising offspring solutions in high-dimensional decision space
with limited training data. The proposed algorithm is tested on 10 benchmark
problems with up to 200 decision variables. Experimental results on these test
problems demonstrate the effectiveness of the proposed algorithm
Green Networking in Cellular HetNets: A Unified Radio Resource Management Framework with Base Station ON/OFF Switching
In this paper, the problem of energy efficiency in cellular heterogeneous
networks (HetNets) is investigated using radio resource and power management
combined with the base station (BS) ON/OFF switching. The objective is to
minimize the total power consumption of the network while satisfying the
quality of service (QoS) requirements of each connected user. We consider the
case of co-existing macrocell BS, small cell BSs, and private femtocell access
points (FAPs). Three different network scenarios are investigated, depending on
the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs,
and HetNets with semi-closed FAPs. A unified framework is proposed to
simultaneously allocate spectrum resources to users in an energy efficient
manner and switch off redundant small cell BSs. The high complexity dual
decomposition technique is employed to achieve optimal solutions for the
problem. A low complexity iterative algorithm is also proposed and its
performances are compared to those of the optimal technique. The particularly
interesting case of semi-closed FAPs, in which the FAPs accept to serve
external users, achieves the highest energy efficiency due to increased degrees
of freedom. In this paper, a cooperation scheme between FAPs and mobile
operator is also investigated. The incentives for FAPs, e.g., renewable energy
sharing and roaming prices, enabling cooperation are discussed to be considered
as a useful guideline for inter-operator agreements.Comment: 15 pages, 9 Figures, IEEE Transactions on Vehicular Technology 201
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