2023 International Conference on Information Networking (ICOIN)最新文献_第4页

Selective Competition for NOMA-capable Devices Using RIS 使用RIS的支持noma的设备的选择性竞争

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/icoin56518.2023.10048932

Min-Seok Yoon, K. Kim, Tae-Jin Lee

引用次数: 0

Classification performance evaluation of latent vector in encoder-decoder model 编码器-解码器模型中潜在向量的分类性能评价

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048940

K. Kang, Changseok Bae

{"title":"Classification performance evaluation of latent vector in encoder-decoder model","authors":"K. Kang, Changseok Bae","doi":"10.1109/ICOIN56518.2023.10048940","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048940","url":null,"abstract":"This paper compares and analyzes the classification performance of latent vectors in the encoder-decoder model. A typical encoder-decoder model, such as an autoencoder, transforms the encoder input into a latent vector and feeds it into the decoder. In this process, the encoder-decoder model learns to produce a decoder output similar to the encoder input. We can consider that the latent vector of the encoder-decoder model is well preserved by abstracting the characteristics of the encoder input. Further, it is possible to apply to unsupervised learning if the latent vector guarantees a sufficient distance between clusters in the feature space. In this paper, the classification performance of latent vectors is analyzed as a basic study for applying latent vectors in encoder-decoder models to unsupervised and continual learning. The latent vectors obtained by the stacked autoencoder and 2 types of CNN-based autoencoder are applied to 6 kinds of classifiers including KNN and random forest. Experimental results show that the latent vector using the CNN-based autoencoder with a dense layer shows superior classification performance by up to 2% compared to the result of the stacked autoencoder. Based on the results in this paper, it is possible to extend the latent vector obtained by using a CNN-based auto-encoder with dense layer to unsupervised learning.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131605004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Height Pattern Estimation Method Using the Combination of Radio Map and 3D Map for Spectrum Sharing 基于无线电图和三维图的频谱共享高度模式估计方法

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048945

Sunao Miyamoto, S. Yamada, T. Fujii

{"title":"Height Pattern Estimation Method Using the Combination of Radio Map and 3D Map for Spectrum Sharing","authors":"Sunao Miyamoto, S. Yamada, T. Fujii","doi":"10.1109/ICOIN56518.2023.10048945","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048945","url":null,"abstract":"Nowadays, spectrum sharing is attracting attention as a solution to spectrum shortage. In order to maximize the spectrum utilization efficiency while avoiding interference from the Secondary User to the Primary User, it is necessary to estimate radio propagation with high accuracy. In recent years, a radio map based on measurements is focused as a highly accurate radio propagation estimation method. It is necessary to estimate the height pattern characteristics and extrapolate the observed values on the ground level in order to estimate the radio propagation in places where there are no observed data sets such as on the upper sky. In this paper, we propose a height pattern estimation method using the radio map and the 3D map. In the proposed method, the main structure on the propagation path is recognized, and dominant propagation path between transmitter and receiver is estimated. Then, the height pattern is estimated by calculating the loss value due to the structures on the selected propagation path using the main structure and the dominant propagation path information. The evaluation results using the measurement datasets show that the estimated performance of the proposed method is improved compared to without extrapolation.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134453567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Survey on Mobile Edge Computing for Deep Learning 面向深度学习的移动边缘计算研究综述

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048953

Pyeongjun Choi, Jeongho Kwak

引用次数: 1

Small Object Detection Technology Using Multi-Modal Data Based on Deep Learning 基于深度学习的多模态数据小目标检测技术

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049014

Chi-Won Park, Yuri Seo, Teh-Jen Sun, Ga-Won Lee, E. Huh

引用次数: 0

A Survey on Fuzzy Logic for Cluster Head Selection in Wireless Sensor Networks 无线传感器网络簇头选择的模糊逻辑研究

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049015

Geeranuch Woraphonbenjakul, Arooj Masood, Sungrae Cho

引用次数: 0

Secure, Dynamic and Uncomplicated Licensing of Movies on a Blockchain Infrastructure 在区块链基础设施上安全，动态和简单的电影许可

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049017

João Santos, Ivone Amorim, Alexandre Ulisses, J. C. Lopes, Vasco Filipe

引用次数: 1

Cooperative User Relaying with RSMA for 6G Networks: Overview, Research Challenges and Future Trends 基于RSMA的6G网络合作用户中继:概述、研究挑战和未来趋势

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048951

Cuong Manh Ho, The-Vi Nguyen, Chunghyun Lee, Thi Xuan My Nguyen, Sungrae Cho

{"title":"Cooperative User Relaying with RSMA for 6G Networks: Overview, Research Challenges and Future Trends","authors":"Cuong Manh Ho, The-Vi Nguyen, Chunghyun Lee, Thi Xuan My Nguyen, Sungrae Cho","doi":"10.1109/ICOIN56518.2023.10048951","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10048951","url":null,"abstract":"Cooperative user relaying (CUR) is emerged as an effective framework for 6G networks to address and improve the coverage, system capacity, and transference reliability, without the limitation of antennas at the transceivers. Based on the principle of CUR, CUR allows some users to receive information from the transmitter and forward them to other users. Rate Splitting Multiple Access (RSMA) currently has been noticed as a promising scheme for the management strategies of interference, the design of multiple access (MA) systems, and optimization of non-orthogonal transmission (non-OT) for 6G networks. Recently, one of the most outstanding schemes and interference strategies for CUR is RSMA. This paper presents a comprehensive tutorial on Cooperative User Relaying with RSMA of wireless network 6G. After analyzing the overview of CUR with RSMA and the cooperative rate-slipping (CRS) scheme, the core challenges of CUR with RSMA will be exploited. Finally, the future directions of CUR with RSMA are defined, aiming to conduct the optimization system of CUR with RSMA into 6G networks.","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128911231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

T-PASS: A Blockchain-based NFT Enabled Property Management and Exchange System T-PASS:基于区块链的NFT资产管理和交易系统

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10048973

K. Haribabu, Ankit Agrawal, Ritika Bhatia, Ashutosh Bhatia, Kamlesh Tiwari

引用次数: 3

Spectral Efficiency Maximization for V2V Communication Underlaid Cellular Uplink Using Deep Neural Networks 基于深度神经网络的V2V通信蜂窝上行链路频谱效率最大化

2023 International Conference on Information Networking (ICOIN) Pub Date : 2023-01-11 DOI: 10.1109/ICOIN56518.2023.10049008

Dara Ron, Eun-Jeong Han, Jung-Ryun Lee

{"title":"Spectral Efficiency Maximization for V2V Communication Underlaid Cellular Uplink Using Deep Neural Networks","authors":"Dara Ron, Eun-Jeong Han, Jung-Ryun Lee","doi":"10.1109/ICOIN56518.2023.10049008","DOIUrl":"https://doi.org/10.1109/ICOIN56518.2023.10049008","url":null,"abstract":"Vehicle-to-vehicle (V2V) communication has been considered as a key technology of the intelligent transportation system because it has emerged with significant benefits such as improving driver safety and reducing traffic congestion and accidents. Although the V2V technology has provided some key advantages, the challenge still exists. Since V2V communication enables the transceiver pairs to exchange emergency information in the same cellular frequency band, the interferences of V2V links and vehicle-to-cellular (V2C) links should occur. Therefore, in our study, we tackle the interference problem by optimizing the transmit powers of the V2V users and the cellular users. The problem-solving process begins with formulating the optimization problem with linear constraints, where the objective function is the sum of data rates, and the transmit powers of all transmitters are the control variables. Then, we design a proper deep neural network (DNN) to solve the optimization problem. DNN obtains the optimal solution via training the neural networks in a way to minimize the loss function. The simulation results show that the proposed DNN algorithm is better than those of weighted minimum mean squared error (WMMSE), fixed transmit power, and Dinkelbach’s methods, and particularly achieves near-global optimum with lower computation complexity than the exhaustive search (ES).","PeriodicalId":285763,"journal":{"name":"2023 International Conference on Information Networking (ICOIN)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127143521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1