• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4015-4033
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• 2015

The future mobile networks consist of hyper-dense heterogeneous and small cell networks of same or different radio access technologies (RAT). Integrating mobile networks of different RATs to provide seamless and smooth mobility service will be the target of future mobile converged network. Generally, handover from high-speed networks to low-speed networks faces many challenges from application perspective, such as abrupt bandwidth variation, packet loss, round trip time variation, connection disruption, and transmission blackout. Existing inter-RAT handover solutions cannot solve all the problems at the same time. Based on the high-layer convergence sublayer design, a new receiver-aided soft inter-RAT handover is proposed. This soft handover scheme takes advantage of multihoming ability of multi-mode mobile station (MS) to smooth handover procedure. In addition, handover procedure is seamless and applicable to frequent handover scenarios. The simulation results conducted in UMTS-WiMAX converged network scenario show that: in case of TCP traffics for handover from WiMAX to UMTS, not only handover latency and packet loss are eliminated completely, but also abrupt bandwidth/wireless RTT variation is smoothed. These delightful features make this soft handover scheme be a reasonable candidate of mobility management for future mobile converged networks.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2815-2817
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• 2002

Classification method of cancers using cDNA microarrays data was developed using genetic algorithms and neural networks. For gene selection, 2308 genes were ranked using genetic algorithms, and selected by frequency number of selection from 1000 of genetic iterative runs. To calculate fitness values, artificial neural networks are used as classifier. The small, round blue cell tumors (SRBCTs) which is difficult to distinguish via pathological single test was used as test diseases for classification, and the test results showed the 96% of exact classification capability for 25 test samples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5701-5722
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• 2018

The continuous increase in the cost of energy production and concerns for environmental sustainability are leading research communities, governments and industries to amass efforts to reduce energy consumption and global $CO_2$ footprint. Players in the information and communication industry are keen on reducing the operational expenditures (OpEx) and maintaining the profitability of cellular networks. Meanwhile, network virtualization has been proposed in this regard as the main enabler for 5G mobile cellular networks. In this paper, we propose a generic framework of slice resource provisioning and customized physical resource allocation for energy-efficiency and quality of service optimization. In resource slicing, we consider user demand and population resources provisioning scheme aiming to satisfy quality of service (QoS). In customized physical resource allocation, we formulate this problem with an integer non-linear programming model, which is solved by a heuristic algorithm based on minimum vertex coverage. The proposed algorithm is compared with the existing approaches, without consideration of slice resource constraints via system-level simulations. From the perspective of infrastructure providers, traffic is scheduled over a limited number of active small-cell base stations (sc-BSs) that significantly reduce the system energy consumption and improve the system's spectral efficiency. From the perspective of virtual network operators and mobile users, the proposed approach can guarantee QoS for mobile users and improve user satisfaction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.183-189
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• 2018

This paper proposes distributed file placement and coverage expansion techniques for mitigating the traffic bottleneck in backhaul for small-cell networks. In order to minimize the backhaul load with limited memory space, the proposed scheme controls the coverage and file placement of base station according to file popularity distribution and memory space of base stations. In other words, since the cache hit ratio is low when there is small memory capacity or widespread file popularity distribution, the base stations expand its coverage and cache different set of files for the user located in overlapped area to exploit multiple cached file sets of base stations. Our simulation results show that the proposed scheme outperforms the conventional cache strategy in terms of network throughput when there is small memory capacity or widespread file popularity distribution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1307-1312
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• 2015

As smart-phones become popular, mobile data traffic has been dramatically increasing and intensive researches on the next-generation mobile communication network is in progress to meet the increasing demand for mobile data traffic. In particular, heterogeneous network (HetNet) is attracting much interest because it can significantly enhance the network capacity by increasing the spatial reuse with macro and small cells. In the HetNet, we have several problems such as load imbalance and interference because of the difference in transmit power between macro and small cells and cell range expansion (CRE) can mitigate the problems. In this paper, we propose a new cell selection scheme with adaptive cell range expansion bias (CREB) for ultra dense HetNet and we analyze the performance of the proposed scheme in terms of average cell transmission rate through system-level simulations and compare it with those of other schemes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.63-66
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• 2015

As smart-phones become popular, mobile data traffic has been dramatically increasing and intensive researches on the next-generation mobile communication network is in progress to meet the increasing demand for mobile data traffic. In particular, heterogeneous network (HetNet) is attracting much interest because it can significantly enhance the network capacity by increasing the spatial resue with macro and small cells. In the HetNet, we have several problems such as load imbalance and interference because of the difference in transmit power between macro and small cells and cell range expansion (CRE) can mitigate the problems. In this paper, we propose a new cell selection scheme with adaptive cell range expansion bias (CREB) for ultra dense HetNet and we analyze the performance of the proposed scheme in terms of average cell transmission rate through system-level simulations and compare it with those of other schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.520-527
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• 2013

In this paper, a joint cell grouping and user association technique proposed for a semi-dynamic grouped network MIMO in a clustered heterogeneous cellular network (HCN). With the conventional macro BSs, small cells are being overlaid to increase a spectral efficiency per area and these small cells are expected to be concentrated to support exponentially increasing data traffic in hot spot areas. The main culprits of performance degradation in the clustered HCN are interference and load imbalance. The proposed scheme jointly handles them to maximize a proportional-fair metric. It is shown that the proposed technique can largely improve user average rate and proportional fairness among users than any other conventional schemes in the clustered HCN.

• Molecules and Cells
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• v.37 no.6
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• pp.457-466
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• 2014

Proteomic analysis is helpful in identifying cancerassociated proteins that are differentially expressed and fragmented that can be annotated as dysregulated networks and pathways during metastasis. To examine metastatic process in lung cancer, we performed a proteomics study by label-free quantitative analysis and N-terminal analysis in 2 human non-small-cell lung cancer cell lines with disparate metastatic potentials - NCI-H1703 (primary cell, stage I) and NCI-H1755 (metastatic cell, stage IV). We identified 2130 proteins, 1355 of which were common to both cell lines. In the label-free quantitative analysis, we used the NSAF normalization method, resulting in 242 differential expressed proteins. For the N-terminal proteome analysis, 325 N-terminal peptides, including 45 novel fragments, were identified in the 2 cell lines. Based on two proteomic analysis, 11 quantitatively expressed proteins and 8 N-terminal peptides were enriched for the focal adhesion pathway. Most proteins from the quantitative analysis were upregulated in metastatic cancer cells, whereas novel fragment of CRKL was detected only in primary cancer cells. This study increases our understanding of the NSCLC metastasis proteome.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6375-6378
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• 2012

Background: Small-cell lung cancer (also known as SCLC) is an aggressive form and untreated patients generally die within about 3 months. To obtain further insight into mechanism underlying malignancy with this cancer, an miRNA synergistic regulatory network was constructed and analyzed in the present study. Method: A miRNA microarray dataset was downloaded from the NCBI GEO database (GSE27435). A total of 546 miRNAs were identified to be expressed in SCLC cells. Then a miRNA synergistic network was constructed, and the included miRNAs mapped to the network. Topology analysis was also performed to analyze the properties of the synergistic network. Consequently, we could identified constitutive modules. Further, common target genes of each module were identified with CFinder. Finally, enrichment analysis was performed for target genes. Results: In this study, a miRNA synergistic network with 464 miRNAs and 2981 edges was constructed. According to the topology analysis, the topological properties between the networks constructed by LC related miRNAs and LC unrelated miRNAs were significantly different. Moreover, a module cilque0 could be identified in our network using CFinder. The module included three miRNAs (hsa-let-7c, hsa-let-7b and hsa-let-7d). In addition, several genes were found which were predicted to be common targets of cilque0. The enrichment analysis demonstrated that these target genes were enriched in MAPK signaling pathways. Conclusions: Although limitations exist in the current data, the results uncovered here are important for understanding the key roles of miRNAs in SCLC. However, further validation is required since our results were based on microarray data derived from a small sample size.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.9-17
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• 2014

Heterogeneous network (HetNet) is a network consisting of macrocells overlaid with small cells. In HetNet, the interference from macrocell to small cell users is a major cause of performance degradation of small cell users and enhanced inter-cell interference coordination (eICIC) is needed to mitigate the interference. Previous works on eICIC gives limited performance gain because these works focus on maximizing long-term throughput and rarely consider varying channel conditions over frames. This paper proposes a new algorithm which dynamically coordinates interference and schedules users on each frame to maximize the total utility of the network with lower computational complexity than exhaustive search. Simulation results show that the proposed algorithm achieves higher total throughput than the throughput with the conventional algorithm, and has higher fairness index than the conventional algorithm when there large number of users.