• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.103-114
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• 2020

In this study, a machine learning (ML) algorithm is analyzed and summarized as a self-organizing network (SON) realization technology that can minimize expert intervention in the planning, configuration, and optimization of mobile communication networks. First, the basic concept of the ML algorithm in which areas of the SON of this algorithm are applied, is briefly summarized. In addition, the requirements and performance metrics for ML are summarized from the SON perspective, and the ML algorithm that has hitherto been applied to an SON achieves a performance in terms of the SON performance metrics.

• Journal of Communications and Networks
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• v.13 no.4
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• pp.367-376
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• 2011

In this paper, we propose self-organizing schemes for the initial configuration of the neighbor cell list (NCL), maintenance of the NCL, and physical cell identifier (PCI) allocation in heterogeneous networks such as long term evolution systems where lower transmission power nodes are additionally deployed in macrocell networks. Accurate NCL maintenance is required for efficient PCI allocation and for avoiding handover delay and redundantly increased system overhead. Proposed self-organizing schemes for the initial NCL configuration and PCI allocation are based on evolved universal terrestrial radio access network NodeB (eNB) scanning that measures reference signal to interference and noise ratio and reference symbol received power, respectively, transmitted from adjacent eNBs. On the other hand, the maintenance of the NCL is managed by adding or removing cells based on periodic user equipment measurements. We provide performance analysis of the proposed schemes under various scenarios in the respects of NCL detection probability, NCL false alarm rate, handover delay area ratio, PCI conflict ratio, etc.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.800-802
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• 2000

In this paper, we propose the Self-Organizing Networks(SON) based on competitive Fuzzy Polynomial Neuron(FPN) for the optimal design of nonlinear process system. The SON architectures consist of layers with activation nodes based on fuzzy inference rules. Here each activation node is presented as FPN which includes either the simplified or regression Polynomial fuzzy inference rules. The proposed SON is a network resulting from the fusion of the Polynomial Neural Networks(PNN) and a fuzzy inference system. The conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as liner, quadratic and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership functions are studied. Chaotic time series data used to evaluate the performance of our proposed model.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.95-106
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• 2023

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.115-134
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• 2020

Several studies on machine learning (ML) based self-organizing networks (SONs) have been conducted, specifically for LTE, since studies to apply ML to optimize mobile communication systems started with 2G. However, they are still in the infancy stage. Owing to the complicated KPIs and stringent user requirements of 5G, it is necessary to design the 5G SON engine with intelligence to enable users to seamlessly and unlimitedly achieve connectivity regardless of the state of the mobile communication network. Therefore, in this study, we analyze and summarize the current state of machine learning studies applied to SONs as solutions to the complicated optimization problems that are caused by the unpredictable context of mobile communication scenarios.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.399-404
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• 2011

For the underwater wireless sensor networks, we propose the packet transmission method which distinguishes more important packet than others. Because the ocean underwater transmission environments are extremely unstable, we use SON(Self Organizing Network) techniques to adapt to the constantly varying underwater acoustic communication channels and randomly deployed sensor nodes. Especially we suppose two kinds of packets which have different priorities, and through the simulations we show that high priority packets arrive at the source node faster than lower priority packets with a proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3A
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• pp.259-266
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• 2011

Femtocells are expected as the surest way to increase the system capacity with higher-quality links and more spatial reuse in future networks. In spite of their great potential, the system capacity is highly susceptible to network density because a large portion of users are exposed to inter-cell interference (ICI). In this work, we proposed a dynamic interference avoidance scheme in densely deployed cell environments. Our proposed DDIA (Distributed Dynamic ICI Avoidance) scheme not only works in a fully distributed manner, but also controls interference link connectivity of users with high agility so that it is suited for self-organizing networks (SONs). We introduced the concept of ICI-link and two-tier scheduling in designing the DDIA scheme. To avoid ICI without any central entity, our scheme tries to harmonize all base stations (BSs) with users adaptively. Through extensive simulations, it was shown that our proposed scheme improves the throughput of users by more than twice on average compared to the frequency reuse factor 1 scheme, who are exposed to ICI while maintaining or even improving overall network performance. Our scheme operates well regardless of network density and topology.

• Electronics and Telecommunications Trends
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• v.27 no.2
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• pp.70-79
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• 2012

스마트폰 사용이 활성화되면서 모바일 데이터 사용량이 급증하고 WiFi뿐만 아니라 펨토셀을 포함한 소형셀(small cell) 인프라가 각광을 받고 있다. 이에 따라, 가정 또는 사무실과 같은 실내에서 음영 지역을 해소하고 한정된 주파수 자원을 효율적으로 사용하여 대용량 데이터 전송 서비스를 가능하게 하는 초소형 기지국 연구에 대한 요구가 많아지고 있다. 또한, 이동통신 기지국의 신규 설치 시 기지국 자체적으로 또는 인접한 기지국 간의 자동 협업을 통하여 기지국 간 간섭을 최소화하고 기지국의 용량을 증대시켜서 셀 커버리지를 최적화하는 기술에 대한 연구가 필요하게 되었다. 이를 위한 방안으로 셀 반경을 극도로 줄여 댁내 또는 소규모 비즈니스 환경에 알맞은 무선 환경을 제공하려고 하는 펨토셀 서비스는 보다 나은 무선 환경을 필요로 하는 사용자 요구에 적극 대응하고, 사업자의 사업 기회를 확대하며, 서비스의 질적 양적 개선 측면에 있어서 가장 중요하게 고려해야 할 기술이다. 본고에서는 SON(Self Organizing Networks) 및 펨토셀 관련 주요 기술적 이슈를 정리하고 현재 진행되고 있는 기술동향에 대하여 살펴 보고자 한다.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.229-232
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• 2008

급격한 이동통신 기술의 발전에 힘입어 음영지역 해소 및 고속 데이터 처리를 위해 댁내 기지국에 대한 개발 및 연구가 진행 중이다. 댁내 기지국은 크게 음영지역 해소를 위한 Open 방식의 기지국과 고속 데이터 처리를 위해 특정 가입자만 사용할 수 있는 Close 방식이 있다. 상기 방식들은 망의 특성에 맞게 이를 제공하는 망 사업자에 의해 선택 된다. 댁내 기지국을 관리하기 위해서는 많은 시간과 인력자원이 소요되므로 자동으로 설정 및 최적화시키는 기능이 요구 시 되고 있으며, 이를 3GPP에서 SON (Self Organizing Optimizing Networks) 이라 일컫고 연구진행 중이다. 본 논문은 댁내 기지국 관리를 위해 셀의 기본 인자인 PCI(Physical Layer Identity) 할당 방안과 댁내 기지국간 간섭을 최소화 시키기 위한 Adaptive Coverage 방안을 제시한다. 또한 계층적 셀 구성(Hierarchical Cell Structure)에 따른 이동성 제공 방안을 제시한다.