• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.1-8
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• 2021

Small-cells in heterogeneous networks are one of the important technologies to increase the coverage and capacity in 5G cellular networks. However, due to the randomly arranged small-cells, co-tier and cross-tier interference increase, deteriorating the system performance of the network. In order to manage the interference, some channel management methods use fractional frequency reuse(FFR) that divides the cell coverage into the inner region(IR) and outer region(OR) based on the distance from the macro base station(MBS). However, since it is impossible to properly measure the distance in the method with FFR, we propose a new interference aware FFR(IA-FFR) method to enhance the system performance. That is, the proposed IA-FFR method divides the MUEs and SBSs into the IR and OR groups based on the signal to interference plus noise ratio(SINR) of macro user equipments(MUEs) and received signals strength of small-cell base stations(SBSs) from the MBS, respectively, and then dynamically assigns subchannels to MUEs and small-cell user equipments. As a result, the proposed IA-FFR method outperforms other methods in terms of the system capacity and outage probability.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.6
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• pp.229-234
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• 2022

Lung cancer is the leading cause of cancer-related deaths worldwide. Indigo Naturalis (IN) is a dark blue powder obtained by processing leaves or stems of indigo plants, its anticancer effects have been reported in several studies. However, the pharmacological mechanism of IN in small cell lung cancer (SCLC) is not elucidated. In this study, to investigate the anticancer efficacy of IN for SCLC, we presented potential active ingredients, SCLC-related targets, and pharmacological mechanisms of IN that are expected to have anticancer activity for SCLC using a network pharmacological analysis. The phytochemical compounds of IN have been collected through TCMSP, SymMap, or HPLC documents. The active ingredients of IN such as indirubin, indican, isatin, and tryptanthrin were selected through ADME parameters or literature investigations for each compound. Using the Compounds, Disease-Target associations Databases, 124 common targets of IN and SCLC were obtained. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis was carried out. GO biological processes are associated with response to xenobiotic stimulus, positive regulation of protein phosphorylation, regulation of mitotic cell cycle, and regulation of apoptotic signaling pathway. KEGG disease pathways included Gastric cancer, Bladder cancer, SCLC, and Melanoma. The main anticancer targets of the IN for SCLC were analyzed in 14 targets, including BCL2, MYC, and TP53. In conclusion, the results of this study based on the network pharmacology of IN can provide important data for the effective prevention and treatment of SCLC.

• Genomics & Informatics
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• v.9 no.4
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• pp.173-180
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• 2011

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.58-67
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• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.33-41
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• 2018

The paradigm of mobile communication technology has changed from an increase in transmission capacity to service-based technologies satisfying various types of service requirements. One of the new paradigms is a service that provides users with a QoE (Quality Of Experience (QoE), at anytime and anywhere. 5G defines various technologies such as dense network structures and beam selection for increasing the transmission capacity and ensuring the quality of experience so as to satisfy this requirement, and related research is underway. In this paper, we describe the definition of a 5G small cell and 5G network structure as well as research trends of standardization and related technologies for constructing optimal solutions for mobile users in dense networks based on small cells.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.1-7
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• 2023

This paper proposes a small cell resource partitioning allocation method to solve interference to machine type communication devices (MTCD) and improve performance in 5G heterogeneous networks (HetNet) where macro base station (MBS) and many small cell base stations (SBS) are overlaid. In the 5G HetNet, since various types of MTCDs generate data traffic, the load on the MBS increases. Therefore, in order to reduce the MBS load, a cell range expansion (CRE) method is applied in which a bias value is added to the received signal strength from the SBS and MTCDs satisfying the condition is connected to the SBS. More MTCDs connecting to the SBS through the CRE will reduce the load on the MBS, but performance of MTCDs will degrade due to interference, so a method to solve this problem is needed. The proposed small cell resource partitioning allocation method allocates resources with less interference from the MBS to mitigate interference of MTCDs newly added in the SBS with CRE, and improve the overall MTCD performace using separating resources according to the performance of existing MTCDs in the SBS. Through simulation results, the proposed small cell resource partitioning allocation method shows performance improvement of 21% and 126% in MTCDs capacity connected to MBS and SBS respectively, compared to the existing resource allocation methods.

• 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.39A no.9
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• pp.548-556
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• 2014

To cope with recently increasing demand for data traffics, heterogeneous networks have been actively studied, where small cells are deployed within a macro cell coverage with the same frequency band. To mitigate the interference from the macro cell to small cells, an enhanced Inter-cell Interference Coordination (eICIC) technique has been proposed, where ABS (Almost Blank Subframe) is used in time domain. However, there is a waste of resource since no data is transmitted in a macro-cell in ABS. In this paper, we propose a new interference management method by using a 3D sector beam based on Active Antenna System (AAS), where Genetic Algorithm (GA) is applied to reduce the antenna gain toward a small-cell. With the proposed scheme, the macro-cell and small cells can transmit data at the same time with the AAS antenna pattern generating reduced interference to small cells. The performance of the proposed scheme is evaluated by using an LTE-Advanced system level simulator.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1110-1116
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• 2013

A 3D-ray tracing tool is a software considering reflection, penetration, and diffraction of the signals to provide accuracy. To provide communication resources effectively, communication standards adopt Heterogeneous Networks (HetNets) that includes small cells. A 3D performance evaluation methodology becomes more and more important since the coverage of the small cell networks is narrower than that of the macro cell networks. It is difficult to directly apply conventional 2D mathematical models due to the complexity of small cell network; since they have many considerations such as topography, placement of buildings and 3D beamforming techniques. In this paper, we introduce an effective performance evaluation methodology for small cell networks using 3D-ray tracing tool. From simulation results, we conclude that new performance evaluation methodologies by using 3D-ray tracing tool is more suitable than conventional methodology for small cell networks.