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Analysis of integrated IDFT and Zadoff–Chu matrix precoding processes in OFDM systems OFDM系统中集成IDFT和Zadoff-Chu矩阵预编码过程分析
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-26 DOI: 10.1016/j.icte.2025.02.005
Kouji Ohuchi
{"title":"Analysis of integrated IDFT and Zadoff–Chu matrix precoding processes in OFDM systems","authors":"Kouji Ohuchi","doi":"10.1016/j.icte.2025.02.005","DOIUrl":"10.1016/j.icte.2025.02.005","url":null,"abstract":"<div><div>Peak signal reduction is a critical problem in orthogonal frequency-division multiplexing (OFDM) systems. Herein, we focus on Zadoff–Chu matrix (ZCM) precoding as a peak signal reduction method and analyze its integration using the discrete Fourier transform process. The analysis reveals that the integrated process can be substituted by a sparse matrix multiplication and the influence of ZCM parameters on the sparse matrix is mathematically clarified. The results also show that the ZCM precoding works to produce a single-carrier signal and explains how the ZCM precoding reduces the peak of the OFDM signal.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 354-357"},"PeriodicalIF":4.1,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Robust hierarchical anomaly detection using feature impact in IoT networks 基于物联网网络特征影响的鲁棒分层异常检测
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-25 DOI: 10.1016/j.icte.2025.02.009
Joohong Rheey, Hyunggon Park
{"title":"Robust hierarchical anomaly detection using feature impact in IoT networks","authors":"Joohong Rheey,&nbsp;Hyunggon Park","doi":"10.1016/j.icte.2025.02.009","DOIUrl":"10.1016/j.icte.2025.02.009","url":null,"abstract":"<div><div>Security threats in Internet of Things (IoT) networks increased, but the lack of labeled data and limited resources hinder intrusion detection system design for IoT networks. We propose a robust hierarchical anomaly detection method based on a variational autoencoder for IoT networks. Our proposed approach includes a shallow detection stage for obvious outliers with an in-depth detection stage that explicitly measures the impact of individual features on latent representations using Shapley values, enhancing the ability to detect adversarial attacks without adversarial training. Simulations confirm the effectiveness against adversarial attacks, with almost 100% detection rates for NSL-KDD and CIC-IDS2017 datasets.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 358-363"},"PeriodicalIF":4.1,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Parallel implementation of GCM on GPUs GCM在gpu上的并行实现
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-14 DOI: 10.1016/j.icte.2025.01.006
JaeSeok Lee , DongCheon Kim , Seog Chung Seo
{"title":"Parallel implementation of GCM on GPUs","authors":"JaeSeok Lee ,&nbsp;DongCheon Kim ,&nbsp;Seog Chung Seo","doi":"10.1016/j.icte.2025.01.006","DOIUrl":"10.1016/j.icte.2025.01.006","url":null,"abstract":"<div><div>This paper presents the first fully parallelized optimization of GCM in a GPU environment. As the era of IoT emerges, a large number of clients communicate with servers, necessitating encrypted communications for security. GCM is a type of AEAD and is currently used in various security protocols, including TLS 1.3 and IPsec. Due to the burden of performing encrypted communication with numerous clients, there has been significant research on utilizing GPUs for high-speed parallel processing in encryption. However, to date, there has been no fully parallelized implementation of GCM on GPUs. This paper proposes a method for parallelizing the challenging GHASH computation in GCM mode, leading to a high-speed parallel implementation of AES-GCM that can exceed 400Gb/s, meeting the requirements of next-generation communication systems. The proposed approach is algorithm-independent and can be applied to any block ciphers. Our implementation on an RTX 4090 demonstrates a performance improvement of <span><math><mrow><mo>×</mo><mn>15</mn><mo>.</mo><mn>38</mn></mrow></math></span> compared to the maximum processing throughput of a multi-threaded Intel(R) Core(TM) i7-13700K. It also achieves a <span><math><mrow><mo>×</mo><mn>17</mn><mo>.</mo><mn>87</mn></mrow></math></span> improvement compared to a hybrid CPU–GPU system. Compared to the most researched FPGA implementation for GCM, specifically Xilinx Ultrascale FPGA, our implementation achieves <span><math><mrow><mo>×</mo><mn>1</mn><mo>.</mo><mn>11</mn></mrow></math></span> better performance. For not only throughput but also power efficiency also better than other implementation, it achieves <span><math><mrow><mo>×</mo><mn>3</mn><mo>.</mo><mn>33</mn></mrow></math></span> compared to CPU implementation on Intel Xeon E3-1220, also it achieves <span><math><mrow><mo>×</mo><mn>21</mn><mo>.</mo><mn>09</mn></mrow></math></span> compared to FPGA implementation for AES on Xilinx Virtex 7 series, which is not including full GCM.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 310-316"},"PeriodicalIF":4.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bit flipping-based error correcting output code construction for adversarial robustness of neural networks 基于位翻转的神经网络对抗鲁棒性纠错输出码构造
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-13 DOI: 10.1016/j.icte.2025.02.002
Wooram Jang , Woojin Hwang , Kezhong Jin , Hosung Park
{"title":"Bit flipping-based error correcting output code construction for adversarial robustness of neural networks","authors":"Wooram Jang ,&nbsp;Woojin Hwang ,&nbsp;Kezhong Jin ,&nbsp;Hosung Park","doi":"10.1016/j.icte.2025.02.002","DOIUrl":"10.1016/j.icte.2025.02.002","url":null,"abstract":"<div><div>In this paper, we propose a method for constructing error-correcting output codes (ECOCs) based on a codeword bit flipping algorithm to enhance adversarial robustness of neural networks. In the previous work in Verma and Swami (2019), ECOCs are applied to deep neural networks (DNNs) based on the analogy between channel noise and adversarial examples to achieve state-of-the-art adversarial robustness. To improve adversarial robustness, it was proposed in Wan et al. (2022) to optimize the Hamming distance between codewords and employ codeword assignment algorithms. Our study achieves approximately a 8% accuracy improvement on MNIST and CIFAR-10 under adversarial attacks compared to the method proposed in Wan et al. (2022).</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 348-353"},"PeriodicalIF":4.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Deep learning based energy-efficient transmission control for STAR-RIS aided cell-free massive MIMO networks 基于深度学习的STAR-RIS辅助无小区大规模MIMO网络节能传输控制
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-11 DOI: 10.1016/j.icte.2025.02.001
Chihyun Song , Donghyun Lee , Yunseong Lee , Wonjong Noh , Sungrae Cho
{"title":"Deep learning based energy-efficient transmission control for STAR-RIS aided cell-free massive MIMO networks","authors":"Chihyun Song ,&nbsp;Donghyun Lee ,&nbsp;Yunseong Lee ,&nbsp;Wonjong Noh ,&nbsp;Sungrae Cho","doi":"10.1016/j.icte.2025.02.001","DOIUrl":"10.1016/j.icte.2025.02.001","url":null,"abstract":"<div><div>Recently, the simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS) has been gaining attention as a key enabler for sixth-generation networks, providing additional links with reduction in power consumption. This paper investigates the STAR-RIS’s potential in a cell-free (CF) massive multiple-input multiple-output (mMIMO) network, where distributed APs serve user over the same time/frequency. We propose a deep deterministic policy gradient framework satisfying system-specific and per-user spectral efficiency constraints, exploiting a post-normalization and a penalized reward. From the simulations, it is revealed the proposed algorithm provides better energy performance than benchmarks, highlighting the benefits of STAR-RIS in the CF network.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 341-347"},"PeriodicalIF":4.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DDS-P: Stochastic models based performance of IoT disaster detection systems across multiple geographic areas DDS-P：基于随机模型的物联网灾害检测系统跨多个地理区域的性能
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.005
Israel Araújo , Luis Guilherme Silva , Carlos Brito , Dugki Min , Jae-Woo Lee , Tuan Anh Nguyen , Erico Leão , Francisco A. Silva
{"title":"DDS-P: Stochastic models based performance of IoT disaster detection systems across multiple geographic areas","authors":"Israel Araújo ,&nbsp;Luis Guilherme Silva ,&nbsp;Carlos Brito ,&nbsp;Dugki Min ,&nbsp;Jae-Woo Lee ,&nbsp;Tuan Anh Nguyen ,&nbsp;Erico Leão ,&nbsp;Francisco A. Silva","doi":"10.1016/j.icte.2024.09.005","DOIUrl":"10.1016/j.icte.2024.09.005","url":null,"abstract":"<div><div>Effective management of catastrophic events in high-risk zones necessitates a holistic technological approach to protect ecosystems, biodiversity, and native populations. Limitations in sensor range and connectivity hamper real-time data gathering in secluded areas, while financial and technical hurdles hinder the creation of cost-effective, automated systems. This study presents stochastic models, the LoRaW protocol, and cloud technology to enhance sensor deployment simulations. Wireless Sensor Networks and LoRa technology are crucial for extensive monitoring and communication infrastructures. Stochastic Petri Net models optimize system components by assessing crucial performance indicators, such as average response time and system utilization, thus improving disaster response and supporting research hypotheses.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 34-40"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sky visibility analysis under urban networks: A stochastic geometry approach 城市网络下的天空能见度分析：一种随机几何方法
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.12.002
Heejung Yu , Sooyeob Jung , Joon Gyu Ryu , Junse Lee
{"title":"Sky visibility analysis under urban networks: A stochastic geometry approach","authors":"Heejung Yu ,&nbsp;Sooyeob Jung ,&nbsp;Joon Gyu Ryu ,&nbsp;Junse Lee","doi":"10.1016/j.icte.2024.12.002","DOIUrl":"10.1016/j.icte.2024.12.002","url":null,"abstract":"<div><div>We propose a novel framework to analyze a ground user’s sky visibility in an urban outdoor network. In order to measure the user’s sky visibility, the point process theory is used to represent buildings of urban outdoor networks. We characterize the line-of-sight (LoS) probability between the ground user and a non-terrestrial network node such as a low-Earth-orbit (LEO) satellite. Then, we quantify how many satellites are observable by the user. This provides intuition for cell planning by answering how many satellites are needed for a ground user without discontinuity of network services. Our analysis is cross-validated by numerical experiments.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 157-160"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Two-stage optimization of computation offloading for ICN-assisted mobile edge computing in 6G network 6G网络中icn辅助移动边缘计算的两阶段卸载优化
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.006
Jiajian Li , Yanjun Shi , Yu Yang
{"title":"Two-stage optimization of computation offloading for ICN-assisted mobile edge computing in 6G network","authors":"Jiajian Li ,&nbsp;Yanjun Shi ,&nbsp;Yu Yang","doi":"10.1016/j.icte.2024.09.006","DOIUrl":"10.1016/j.icte.2024.09.006","url":null,"abstract":"<div><div>This paper investigates QoS-aware computation offloading issues for mobile edge computing in the 6G network. To minimize the end-to-end delay, we harness the Information-Centric Network (ICN) to ensure resource-constrained mobile user offloading computation-sensitive tasks in a distributed manner. Then, a two-stage approach based on a Multi-Agent Reinforcement Learning (MARL) algorithm entwined with optimization-embedding offloading ratio is proposed to enhance server selection for load balancing. Numeral results demonstrate that, with reference to a workshop-scale scenario, the proposed method can achieve outperformed performance in reducing delay and balancing loads on edge servers than the other four baseline schemes.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 26-33"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Disparity estimation of stereo-endoscopic images using deep generative network 基于深度生成网络的立体内窥镜图像视差估计
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.017
Bo Yang , Siyuan Xu , Lirong Yin , Chao Liu , Wenfeng Zheng
{"title":"Disparity estimation of stereo-endoscopic images using deep generative network","authors":"Bo Yang ,&nbsp;Siyuan Xu ,&nbsp;Lirong Yin ,&nbsp;Chao Liu ,&nbsp;Wenfeng Zheng","doi":"10.1016/j.icte.2024.09.017","DOIUrl":"10.1016/j.icte.2024.09.017","url":null,"abstract":"<div><div>A novel disparity estimation pipeline is proposed for 3D reconstruction of dynamic soft tissues in minimally invasive surgery (MIS), which uses a deep generative network to learn manifold distributions of reasonable disparity maps from past stereo images in the training phase, and transforms stereo matching into an optimization problem with respect to the low-dimensional latent vector of the learned generator in the application phase. The proposed pipeline is particularly suitable for dynamic MIS scenarios with insufficient training data, as the photometric loss is explicitly used in the application phase and the scenario priors are introduced via a deep generative network.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 74-79"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Learning strategies for neural min-sum decoding of LDPC codes LDPC码神经最小和译码的学习策略
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.010
Hyeyeon Na , Hosung Park , Hee-Youl Kwak , Seok-Ki Ahn
{"title":"Learning strategies for neural min-sum decoding of LDPC codes","authors":"Hyeyeon Na ,&nbsp;Hosung Park ,&nbsp;Hee-Youl Kwak ,&nbsp;Seok-Ki Ahn","doi":"10.1016/j.icte.2024.09.010","DOIUrl":"10.1016/j.icte.2024.09.010","url":null,"abstract":"<div><div>The min-sum (MS) decoding for low-density parity-check codes, though less complex than the sum–product algorithm, suffers from worse error-correcting performance. For enhancement, neural MS decoders leveraging deep learning have recently been introduced, but how to train them has not been sufficiently discussed. In this paper, we propose a novel dataset construction method and also propose systematic learning strategies by finding a good combination of dataset composition, loss functions, weight sharing, weight assignment, and weight update method. Simulations demonstrate that the proposed method achieves better error-correcting performance than other works, especially in the error floor region, within a limited number of iterations.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 161-166"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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