• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.12
• /
• pp.2443-2449
• /
• 2015

Downlink (DL) data rate for a MS is influenced by not only the signal to interference and noise ratio (SINR) but also the amount of radio resources allocated to the MS. Therefore, when a MS uses SINR to select a cell to associate with, it cannot receive the fastest DL data rate all the time if it associates with a congested cell. Moreover, the SINR-based cell selection may result in cell loads unbalance, which decreases the efficiency of a network. To address the issue, we propose a novel cell selection method by considering not only SINR but also a cell load which are combined into two cell selection criteria. One is the maximum achievable data rate and the other is the minimum outage probability. The simulation results show that the cell selection based on the maximum achievable data rate is superior to the SINR-based method and the method using the minimum outage probability in terms of the system efficiency and the fairness in cell loads while the cell selection method based on the minimum outage probability is superior to the others in terms of the outage probability of a MS.

• Korean Management Science Review
• /
• v.26 no.1
• /
• pp.171-182
• /
• 2009

We consider the inventory replenishment problem and the vehicle routing problem simultaneously in the vending machine operation. This problem is known as the inventory routing problem. We design a memory cell in the clonal selection algorithm. The memory cell store the best solution of previous solved problem and use an initial solution for next problem. In general, the other clonal selection algorithm used memory cell for reserving the best solution in current problem. Experiments are performed for testing efficiency of the memory cell in demand uncertainty. Experiment result shows that the solution quality of our algorithm is similar to general clonal selection algorithm and the calculations time is reduced by 20% when the demand uncertainty is less than 30%.

• ETRI Journal
• /
• v.28 no.1
• /
• pp.77-83
• /
• 2006

In order to improve the accuracy of cell selection in heterogeneous cellular systems, this paper proposes a fuzzy multiple-objective decision-based cell selection (FMDCS) strategy. Since heterogeneous cellular systems have different access technologies and multiple traffic classes, the strategy adopts cell type, data rate, coverage, transmission delay, and call arrival rate as evaluation indices, and uses different weight vectors according to the traffic classes of the mobile host. Then, a fuzzy multiple-objective decision algorithm is applied to select the optimal cell from all candidates. This paper also gives an instance analysis and simulation. The instance analysis shows FMDCS makes different selections for different traffic classes. Simulation results of the after-handoff quality-of-service (QoS) show the selected cell can provide MH optimal service.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37B no.12
• /
• pp.1102-1112
• /
• 2012

We propose a cell selection and resource allocation scheme that assigns users to nearby accessible cells in heterogeneous wireless networks consisting of macrocell, femtocells, and Wi-Fi access points, under overload situation. Given the current power level of all accessible cells nearby users, the proposed scheme finds all possible cell assignment mappings of which user should connect to which cell to maximize the number of users that the network can accommodate at the same time. We formulate the cell selection problem with heterogeneous cells into an optimization problem of binary integer programming, and compute the optimal solution. We evaluate the proposed algorithm in terms of network access failure compared to a local ad-hoc based cell selection scheme used in practical systems using network level simulations. We demonstrate that our cell selection algorithm dramatically reduces network access failure in overload situation by fully leveraging network resources evenly across heterogeneous networks. We also validate the practical feasibility in terms of computational complexity of our binary integer program by measuring the computation time with respect to the number of users.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.4
• /
• pp.453-458
• /
• 2003

The anomaly-detection algorithm based on negative selection of T cells is representative model among self-recognition methods and it has been applied to computer immune systems in recent years. In immune systems, T cells are produced through both positive and negative selection. Positive selection is the process used to determine a MHC receptor that recognizes self-molecules. Negative selection is the process used to determine an antigen receptor that recognizes antigen, or the nonself cell. In this paper, we propose a novel self-recognition algorithm based on the positive selection of T cells. We indicate the effectiveness of the proposed algorithm by change-detection simulation of some infected data obtained from cell changes and string changes in the self-file. We also compare the self-recognition algorithm based on positive selection with the anomaly-detection algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.3A
• /
• pp.215-222
• /
• 2011

In this paper, we propose a power control scheme for effective serving cell selection in Relay environment of 3GPP (3rd Generation Partnership Project) LTE (Long Tenn Evolution)-Advanced system. A conventional serving cell selection scheme which does not use channel states of backhaul link has a problem that this scheme does not select serving cell supporting maximum throughput. Also, conventional proposed serving cell selection schemes that eNB or RN transmits channel states of backhaul link have problems that conventional schemes need to additional data transmission, serving cell selection process complexity is increased because UE considers channel states of backhaul link, and received signal is degraded because strong interference which is transmission signal from RN. Therefore, for solve these problems, we propose power control scheme that RN control transmission power according to received SINR (Signal to Interference plus Noise Ratio) of backhaul link. By extensive computer simulation, we verify that the power control Relay scheme is attractive and suitable for the Relay environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.12
• /
• pp.1079-1085
• /
• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• IMMUNE NETWORK
• /
• v.11 no.6
• /
• pp.336-341
• /
• 2011

T cell receptor (TCR) signaling plays a critical role in T cell development, survival and differentiation. In the thymus, quantitative and/or qualitative differences in TCR signaling determine the fate of developing thymocytes and lead to positive and negative selection. Recently, it has been suggested that self-reactive T cells, escape from negative selection, should be suppressed in the periphery by regulatory T cells (Tregs) expressing Foxp3 transcription factor. Foxp3 is a master factor that is critical for not only development and survival but also suppressive activity of Treg. However, signals that determine Treg fate are not completely understood. The availability of mutant mice which harbor mutations in TCR signaling mediators will certainly allow to delineate signaling events that control intrathymic (natural) Treg (nTreg) development. Thus, we summarize the recent progress on the role of TCR signaling cascade components in nTreg development from the studies with murine model.

• Journal of Power Electronics
• /
• v.12 no.1
• /
• pp.223-231
• /
• 2012

In this paper, criteria for better selection of a supercapacitor through EIS (Electrochemical Impedance Spectroscopy) experiments are presented. The performance characteristics of a supercapacitor are thoroughly analyzed in terms of losses and available energy to select the optimal product. The validity of the proposed criteria is demonstrated through the computer simulations and experiments on a fuel cell vehicle using a supercapacitor module with the FTP-72 urban dynamometer driving schedule.

• Journal of the Korean Statistical Society
• /
• v.11 no.1
• /
• pp.25-35
• /
• 1982

A problem of selecting the least probable cell in a multinomial distribution is studied in a Bayesian framework. We consider two loss components the cost of sampling and the difference in cell probabilities between the selected and the least probable cells. A Bayes sequential selection rule is derived with respect to a Dirichlet prior, and it is compared with the best fixed sample size selection rule. The continuation sets with respect to the vague prior are tabulated for certain cases.