• 한국컴퓨터정보학회논문지
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• 제27권9호
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• pp.101-112
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• 2022

본 논문에서는 5G 네트워크 슬라이싱에 대해서 분석하고 5G 이동 통신망에서의 효율적인 네트워크 슬라이스 설정 방안을 제안한다. 5G 이동 통신망에서 네트워크 슬라이싱은 네트워크 슬라이스 인스턴스 정보에 기반하여 구분되고 수행된다. 단말과 네트워크 간의 네트워크 슬라이스 인스턴스 정보가 상호 일치하지 않는 경우, 단말의 PDU 세션 연결 요청 실패에 따른 불필요한 시그널링 오버헤드가 발생한다. 본 논문은 이러한 문제를 해결하기 위해서, 두 가지 효율적인 네트워크 슬라이스 설정 기법, 단말 기반 ENSC(Efficient Network Slice Configuration) 기법과 네트워크 기반 ENSC 기법을 제안한다. 제안하는 두 가지 기법들은 신속한 단말과 네트워크 간의 최신 변경 업데이트된 네트워크 슬라이스 정보를 제공 설정 수행하게 되어, 기존 방안과 비교하여 배터리 리소스 효율성을 향상시키고 불필요한 시그널링 오버헤드를 최소화할 수 있다.

• International Journal of Advanced Culture Technology
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• 제10권3호
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• pp.307-312
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• 2022

The commercialization of the fifth generation (5G) mobile systems has quested enabling technologies, such as intelligent reflecting surface (IRS) transmissions, towards the sixth generation (6G) networks. In this paper, we present a bit-error rate (BER) performance analysis on IRS transmissions in 5G non-orthogonal multiple access (NOMA) networks. First, we derive a closed-form expression for the BER of IRS-NOMA transmissions under Rician fading channels. Then, by Monte Carlo simulations, we validate the proposed approximate BER expression, and show numerically that the derived BER expression is in good agreement with Monte Carlo simulations. Furthermore, we also analyze the BER performance of IRS-NOMA networks under Rician fading channels with different numbers of reflecting elements, and demonstrate that the performances improve monotonically as the number of reflecting devices increases.

• International journal of advanced smart convergence
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• 제10권2호
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• pp.1-9
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• 2021

In the Internet-of-Things (IoT) and artificial intelligence (AI), complete implementations are dependent largely on the speed of the fifth generation (5G) networks. However, successive interference cancellation (SIC) in non-orthogonal multiple access (NOMA) of the 5G mobile networks can be still decoding latency and receiver complexity in the conventional SIC NOMA scheme. Thus, in order to reduce latency and complexity of inherent SIC in conventional SIC NOMA schemes, we propose a rate-lossless non-SIC NOMA scheme. First, we derive the closed-form expression for the achievable data rate of the asymmetric 2PAM non-SIC NOMA, i.e., without SIC. Second, the exact achievable power allocation interval of this rate-lossless non-SIC NOMA scheme is also derived. Then it is shown that over the derived achievable power allocation interval of user-fairness, rate-lossless non-SIC NOMA can be implemented. As a result, the asymmetric 2PAM could be a promising modulation scheme for rate-lossless non-SIC NOMA of 5G networks, under user-fairness.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.27-32
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• 2022

The fifth generation (5G) mobile communication technology is designed to meet all communication needs. Heterogeneous networks (HetNets) are a new emerging network structure. HetNets have greater potential for radio resource reuse and better service quality than homogeneous networks since they can evolve small cells into macrocells. Effective resource allocation techniques reduce inter-user interference while optimizing the utilization of limited spectrum resources in HetNets. This article discusses resource allocation in 5G HetNets. This paper explains HetNets and how they work. Typical cell types in HetNets are summarized. Also, HetNets models are explained in the third section. The fourth component addresses radio resource control and mobility management. Moreover, future study in this subject may benefit from this article's significant insights on how HetNets function.

• 스마트미디어저널
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• 제12권11호
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• pp.113-124
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• 2023

5G 및 B5G(Beyond 5G) 네트워크의 등장으로 기존 네트워크 한계를 극복할 수 있는 네트워크 가상화 기술이 주목받고 있다. 네트워크 가상화의 목적은 효율적 네트워크 자원의 활용과 다양한 전송요구 서비스에 대한 솔루션을 제공하기 위함이다. 이와 관련하여 여러 가지 휴리스틱 기반의 VNE 기법이 연구되고 있으나 네트워크 자원할당 및 서비스의 유연성이 제한되는 문제점을 지니고 있다. 본 논문에서는 다양한 응용의 서비스 요구사항을 충족하기 위해 GNN 기반의 네트워크 슬라이싱 분류 기법과 최적의 자원할당을 위한 RL 기반 VNE 기법을 제안한다. 제안된 기법에서는 Actor-Critic 네트워크를 이용하여 최적의 VNE를 수행한다. 또한 성능 평가를 위해 제안된 기법과 기존의 Node Rank, MCST-VNE, GCN-VNE 기법과의 성능을 비교분석하고 서비스 수용률 제고 및 효율적 자원 할당 측면에서 성능이 향상됨을 보인다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.139-146
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• 2022

Wireless access technologies are emerging to enable high data rates for mobile users and novel applications that encompass both human and machine-type interactions. An essential approach to meet the rising demands on network capacity and offer high coverage for wireless users on upcoming fifth generation (5G) networks is heterogeneous networks (HetNets), which are generated by combining the installation of macro cells with a large number of densely distributed small cells Deployment in 5G architecture has several issues because to the rising complexity of network topology in 5G HetNets with many distinct base station types. Aside from the numerous benefits that dense small cell deployment delivers, it also introduces key mobility management issues such as frequent handover (HO), failures, delays and pingpong HO. This article investigates 5G HetNet mobility management in terms of radio resource control. This article also discusses the key challenges for 5G mobility management.

• 한국전자통신학회논문지
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• 제16권6호
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• pp.1069-1074
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• 2021

최근 들어 5G 상용통신의 보급으로 이동통신기술은 새로운 시대를 맞이 하고 있다. 현재 도시지역을 중심으로 5G 이동 통신 서비스가 제공되고 있으나 조만간 전국을 대상으로 서비스가 확대될 것으로 전망된다. mmWave 기술을 기반으로 하는 5G 이동통신은 초기 단계로 일반인 대상으로 하는 음성 및 인터넷 서비스 중심으로 전개되고 있으나 전국망 구축이 완료되면 산업통신으로 확장될 것으로 예상된다. 이 산업 통신분야의 대표적인 예가 철도통신 시스템이다. 따라서 본 논문에서는 5G 이동통신을 기반으로 하는 철도통신망의 트래픽 전송 성능을 컴퓨터 시뮬레이션을 사용하여 분석한다. 이 분석 결과를 기반으로 5G 기반 철도통신망의 구축 조건을 살펴본다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.327-332
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• 2005

We investigatea new fuzzy-neural networks-Hybrid Fuzzy set based polynomial Neural Networks (HFSPNN). These networks consist of genetically optimized multi-layer with two kinds of heterogeneous neurons thatare fuzzy set based polynomial neurons (FSPNs) and polynomial neurons (PNs). We have developed a comprehensive design methodology to determine the optimal structure of networks dynamically. The augmented genetically optimized HFSPNN (namely gHFSPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of gHFSPNN leads to the selection leads to the selection of preferred nodes (FSPNs or PNs) available within the HFSPNN. In the sequel, the structural optimization is realized via GAs, whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is quantified through experimentation where we use a number of modeling benchmarks synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.235-245
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• 2023

Smart applications based on the Network of Everything also known as Internet of Everything (IoE) are increasing popularity as network connectivity requires rise further. As a result, there will be a greater need for developing 6G technologies for wireless communications in order to overcome the primary limitations of visible 5G networks. Furthermore, implementing neural networks into 6G will bring remedies for the most complex optimizing networks challenges. Future 6G mobile phone networks must handle huge applications that require data and an increasing amount of users. With a ten-year time skyline from thought to the real world, it is presently time for pondering what 6th era (6G) remote correspondence will be just before 5G application. In this article, we talk about 6G dreams to clear the street for the headway of 6G and then some. We start with the conversation of imaginative 5G organizations and afterward underline the need of exploring 6G. Treating proceeding and impending remote organization improvement in a serious way, we expect 6G to contain three critical components: cell phones super broadband, very The Web of Things (or IoT and falsely clever (artificial intelligence). The 6G project is currently in its early phases, and people everywhere must envision and come up with its conceptualization, realization, implementation, and use cases. To that aim, this article presents an environment for Presented Distributed Artificial Intelligence as-a-Services (DAIaaS) supplying in IoE and 6G applications. The case histories and the DAIaaS architecture have been evaluated in terms of from end to end latency and bandwidth consumption, use of energy, and cost savings, with suggestion to improve efficiency.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.226-234
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• 2024

The frequent handover problem and playing ping-pong effects in 5G (5th Generation) ultra-dense networking cannot be effectively resolved by the conventional handover decision methods, which rely on the handover thresholds and measurement reports. For instance, millimetre-wave LANs, broadband remote association techniques, and 5G/6G organizations are instances of group of people yet to come frameworks that request greater security, lower idleness, and dependable principles and correspondence limit. One of the critical parts of 5G and 6G innovation is believed to be successful blockage the board. With further developed help quality, it empowers administrator to run many systems administration recreations on a solitary association. To guarantee load adjusting, forestall network cut disappointment, and give substitute cuts in case of blockage or cut frustration, a modern pursuing choices framework to deal with showing up network information is require. Our goal is to balance the strain on BSs while optimizing the value of the information that is transferred from satellites to BSs. Nevertheless, due to their irregular flight characteristic, some satellites frequently cannot establish a connection with Base Stations (BSs), which further complicates the joint satellite-BS connection and channel allocation. SF redistribution techniques based on Deep Reinforcement Learning (DRL) have been devised, taking into account the randomness of the data received by the terminal. In order to predict the best capacity improvements in the wireless instruments of 5G and 6G IoT networks, a hybrid algorithm for deep learning is being used in this study. To control the level of congestion within a 5G/6G network, the suggested approach is put into effect to a training set. With 0.933 accuracy and 0.067 miss rate, the suggested method produced encouraging results.