Search results for "Telecommunication"

showing 10 items of 1769 documents

Field estimation in wireless sensor networks using distributed kriging

2012

In this paper, we tackle the problem of spatial interpolation for distributed estimation in Wireless Sensor Networks by using a geostatistical technique called kriging. We present a novel Distributed Iterative Kriging Algorithm (DIKA) which is composed of two main phases. First, the spatial dependence of the field is exploited by calculating semivariograms in an iterative way. Second, the kriging system of equations is solved by an initial set of nodes in a distributed manner, providing some initial interpolation weights to each node. In our algorithm, the estimation accuracy can be improved by iteratively adding new nodes and updating appropriately the weights, which leads to a reduction i…

Mathematical optimizationComputer scienceNode (networking)020206 networking & telecommunications02 engineering and technologySystem of linear equationsMultivariate interpolationReduction (complexity)Kriging0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSpatial dependenceCluster analysisAlgorithmWireless sensor networkInterpolation2012 IEEE International Conference on Communications (ICC)
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Power allocation in multi-channel cognitive radio networks with channel assembling

2011

Accepted version of a paper in the book: 2011 IEEE 12th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Published version available from the IEEE:http://dx.doi.org/10.1109/SPAWC.2011.5990485 Consider power allocation for Secondary User (SU) packet transmissions over multiple channels with variable Primary User (PU) arrival rates in cognitive radio networks. Two problems are studied in this paper: The first one is to minimize the collision probability with PUs and the second one is to maximize the data rate while keeping the collision probability bounded. It is shown that the optimal solution for the first problem is to allocate all power onto the bes…

Mathematical optimizationComputer sciencebusiness.industryNetwork packet020206 networking & telecommunications02 engineering and technologyPower budgetPower (physics)Dynamic programmingVariable (computer science)Cognitive radioBounded functionVDP::Technology: 500::Information and communication technology: 550::Telecommunication: 5520202 electrical engineering electronic engineering information engineeringbusinessComputer networkCommunication channel
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A Stochastic Search on the Line-Based Solution to Discretized Estimation

2012

Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_77 Recently, Oommen and Rueda [11] presented a strategy by which the parameters of a binomial/multinomial distribution can be estimated when the underlying distribution is nonstationary. The method has been referred to as the Stochastic Learning Weak Estimator (SLWE), and is based on the principles of continuous stochastic Learning Automata (LA). In this paper, we consider a new family of stochastic discretized weak estimators pertinent to tracking time-varying binomial distributions. As opposed to the SLWE, our p…

Mathematical optimizationDiscretizationLearning automataComputer scienceStochastic Point Locationlearning automataEstimatorVDP::Technology: 500::Information and communication technology: 550020206 networking & telecommunications02 engineering and technologyOracleVDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425weak estimatorsnon-stationary environmentsLine (geometry)Convergence (routing)0202 electrical engineering electronic engineering information engineeringApplied mathematics020201 artificial intelligence & image processingMultinomial distributionFinite set
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Multicell power allocation method based on game theory for inter-cell interference coordination

2009

As a new technology, coordinated multipoint (CoMP) transmission is included in LTE-Advanced study item. Moreover, the network architecture in LTE-Advanced system is modified to take into account coordinated transmission. Under this background, a novel power allocation game model is established to mitigate inter-cell interference with cellular coordination. In the light of cellular cooperation relationship and centralized control in eNodeB, the power allocation in each served antenna unit aims to make signal to interference plus noise ratio (SINR) balanced among inter-cells. Through the proposed power allocation game algorithm, the users' SINR can reach the Nash equilibrium, making it feasib…

Mathematical optimizationGeneral Computer ScienceComputer scienceComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSSignal-to-interference-plus-noise ratioThroughputInterference (wave propagation)Blocking (statistics)Telecomunicaciósymbols.namesakeEnodeBTransmission (telecommunications)Nash equilibriumsymbolsGame theoryComunicació i tecnologiaSimulation
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Best compromise solution for a new multiobjective scheduling problem

2006

In future wireless networks, a mobile terminal will be able to communicate with a service provider using several network connections. These connections to networks will have different properties and they will be priced separately. In order to minimize the total communication time and the total transmission costs, an automatic method for selecting the network connections is needed. Here, we describe the network connection selection problem and formulate it mathematically. We discuss solving the problem and analyse different multiobjective optimization approaches for it.

Mathematical optimizationGeneral Computer ScienceJob shop schedulingWireless networkComputer scienceModeling and SimulationManagement Science and Operations ResearchService providerTransmission timeMulti-objective optimizationTelecommunications networkAssignment problemScheduling (computing)Computers & Operations Research
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Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

2011

Part 1: - PE-CRN 2011 Workshop; International audience; In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models.

Mathematical optimizationMathematical modelComputer science020209 energycontinuous time Markov chain modelsAggregate (data warehouse)Cognitive radio networks020206 networking & telecommunications02 engineering and technologyMarkov modelchannel aggregation strategyperformance evaluationContinuous-time Markov chain[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Cognitive radio0202 electrical engineering electronic engineering information engineeringDynamic channel[INFO]Computer Science [cs]SimulationComputer Science::Information TheoryCommunication channel
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Distributed Resource Allocation in Underlay Multicast D2D Communications

2021

Multicast device-to-device communications operating underlay with cellular networks is a spectral efficient technique for disseminating data to nearby receivers. However, due to the critical challenge of having an intelligent interference coordination between multicast groups along with the cellular network, it is necessary to judiciously perform resource allocation for the combined network. In this work, we present a framework for a joint channel and power allocation strategy to maximize the sum rate of the combined network while guaranteeing minimum rate to individual groups and cellular users. The objective function is augmented by an austerity function that penalizes excessive assignmen…

Mathematical optimizationMulticastChannel allocation schemesComputer science020206 networking & telecommunications020302 automobile design & engineeringThroughput02 engineering and technology0203 mechanical engineeringDistributed algorithm0202 electrical engineering electronic engineering information engineeringCellular networkResource allocationElectrical and Electronic EngineeringUnderlayDisseminationCommunication channelIEEE Transactions on Communications
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Reinforcement Learning Based Mobility Load Balancing with the Cell Individual Offset

2021

In this study, we focus on the cell individual offset (CIO) parameter in the handover process, which represents the willingness of a cell to admit the incoming handovers. However, it is challenging to tune the CIO parameter, as any poor implementation can lead to undesired outcomes, such as making the neighboring cells over-loaded while decreasing the traffic load of the cell. In this work, a reinforcement learning-based approach for parameter selection is introduced, since it is quite convenient for dynamically changing environments. In that regard, two different techniques, namely Q-learning and SARSA, are proposed, as they are known for their multi-objective optimization capabilities. Mo…

Mathematical optimizationOffset (computer science)Computer science05 social sciences050801 communication & media studies020206 networking & telecommunicationsSelf-organizing network02 engineering and technologyLoad balancing (computing)Load management0508 media and communicationsHandoverMetric (mathematics)0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Reinforcement learning2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)
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Power allocation optimization in OFDM-based cognitive radios based on sensing information

2011

Owing to the non-zero probability of the missed detection and false alarm of active primary transmission, a certain degree of performance degradation of the primary user (PU) from cognitive radio users (CRs) is unavoidable. In this paper, we consider OFDM-based communication systems and present efficient algorithms to maximize the total rate of the CR by optimizing jointly both the detection operation and the power allocation, taking into account the influence of the probabilities of missed detection and false alarm, namely, the sensing accuracy. The optimization problem can be formulated as a two-variable non-convex problem, which can be solved approximately by using an alternating directi…

Mathematical optimizationOptimization problemCognitive radioTransmission (telecommunications)Computer scienceOrthogonal frequency-division multiplexingConvex optimizationFalse alarmCommunications systemInterference (wave propagation)2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Joint Optimization of Detection Threshold and Resource Allocation in Infrastructure-based Multi-band Cognitive Radio Networks

2012

[EN] Consider an infrastructure-based multi-band cognitive radio network (CRN) where secondary users (SUs) opportunistically access a set of sub-carriers when sensed as idle. The carrier sensing threshold which affects the access opportunities of SUs is conventionally regarded as static and treated independently from the resource allocation in the model. In this article, we study jointly the optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in such CRNs. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carrier assignment and power allocation, with constraints on…

Mathematical optimizationOptimization problemComputer scienceComputer Networks and Communications020208 electrical & electronic engineeringReal-time computing020206 networking & telecommunications02 engineering and technologyINGENIERIA TELEMATICAPower budgetComputer Science ApplicationsMulti-band cognitive radio networksBase stationCognitive radioTelecommunications linkSignal Processing0202 electrical engineering electronic engineering information engineeringResource allocationOnline algorithmResource allocationOptimization of detection threshold
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