Journal of Communications and Networks最新文献_第3页

IF 3 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-06-01 Epub Date: 2026-07-14 DOI: 10.23919/JCN.2025.000140

引用次数: 0

Pilot-efficient channel estimation for 6G MU-mMIMO using LS initialization and GAN-augmented CNN refinement 使用LS初始化和gan增强CNN改进的6G MU-mMIMO导频有效信道估计

IF 3 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-06-01 Epub Date: 2026-04-16 DOI: 10.23919/JCN.2025.000112

Pooya Hejazi;Masoud Sabaei;Ali Hajmahmoudi

{"title":"Pilot-efficient channel estimation for 6G MU-mMIMO using LS initialization and GAN-augmented CNN refinement","authors":"Pooya Hejazi;Masoud Sabaei;Ali Hajmahmoudi","doi":"10.23919/JCN.2025.000112","DOIUrl":"https://doi.org/10.23919/JCN.2025.000112","url":null,"abstract":"Accurate channel estimation with limited pilot overhead is a key bottleneck for 6G MU-mMIMO, particularly at mmWave (with implications for THz) where path loss and multiuser interference are severe. We propose a two-stage least squares convolutional neural network (LS-CNN) framework in which a robust LS estimator provides a stable coarse channel estimate, avoiding the sparsity assumptions of compressed sensing algorithms that often fail in rich-scattering outdoor environments. In the second stage, this estimate is refined using a CNN trained on a hybrid dataset expanded through controlled augmentation of a generative adversarial network (GAN), improving generalization while minimizing pilot overhead. Training data is refined using mean squared error (MSE) thresholds to ensure high-quality samples, and a robust standardization method is used to stabilize learning with complex-valued input. Simulations on the DeepMIMO ray-tracing dataset demonstrate that the proposed approach provides an up to 8 dB normalized MSE (NMSE) improvement at low signal-to-noise ratio (SNR) over classical LS and MMSE estimators. In our experiments, it achieves performance comparable to that of the ideal MMSE estimator while requiring 60% fewer pilot symbols. Complexity analysis confirms that the proposed hybrid architecture is significantly more efficient than state-of-the-art Vision Transformers, making it practical for real-time 6G deployments.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 3","pages":"401-408"},"PeriodicalIF":3.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11482819","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442840","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

Privacy preserving in wiretap channels beyond Shannon's paradigm: Current trends and future challenges 超越香农范式的窃听渠道中的隐私保护：当前趋势和未来挑战

IF 3 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-06-01 Epub Date: 2026-03-23 DOI: 10.23919/JCN.2025.000103

Mahshid Narimani Kenari;Giancarlo Sciddurlo;Luigi Alfredo Grieco;Nicola Cordeschi

{"title":"Privacy preserving in wiretap channels beyond Shannon's paradigm: Current trends and future challenges","authors":"Mahshid Narimani Kenari;Giancarlo Sciddurlo;Luigi Alfredo Grieco;Nicola Cordeschi","doi":"10.23919/JCN.2025.000103","DOIUrl":"https://doi.org/10.23919/JCN.2025.000103","url":null,"abstract":"Shannon's classical information theory has long underpinned communication systems by ensuring bit-level fidelity, yet it remains agnostic to the semantic content of transmitted data. Semantic communication (SemCom) introduces a paradigm shift beyond Shannon's model by enabling the transmission of meaning-relevant information, thereby enhancing communication efficiency. By leveraging artificial intelligence (AI), SemCom prioritizes task-relevant features, achieving significant reductions in bandwidth usage and latency, while improving throughput and system performance. Despite these advantages, SemCom introduces novel security vulnerabilities. The inherent openness of wireless channels, high correlation between source and transmitted representations, and structural weaknesses in AI models render SemCom particularly susceptible to eavesdropping and privacy breaches. These risks necessitate a reassessment of traditional security paradigms. This paper presents a comprehensive survey of emerging security strategies for SemCom against eavesdropping, encompassing physical-layer security, cryptographic frameworks, data-driven approaches, and semantic-level covertness. Each class of techniques is analyzed with respect to its methodological foundations, effectiveness, limitations, and its deviation from conventional communication security mechanisms. Distinctively, this survey provides a comparative analysis of these strategies under model inversion-based eavesdropping attacks, offering a unique perspective absent in existing literature. The paper concludes by identifying critical research challenges and outlining prospective directions for secure and trustworthy SemCom systems.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 3","pages":"380-400"},"PeriodicalIF":3.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11454690","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443112","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

Adaptive OTP generation using AI-based risk assessment for context-aware two-factor authentication systems 使用基于ai的风险评估自适应OTP生成上下文感知双因素身份验证系统

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-02-25 DOI: 10.23919/JCN.2025.000091

Insoo Kim

{"title":"Adaptive OTP generation using AI-based risk assessment for context-aware two-factor authentication systems","authors":"Insoo Kim","doi":"10.23919/JCN.2025.000091","DOIUrl":"https://doi.org/10.23919/JCN.2025.000091","url":null,"abstract":"Traditional one-time password (OTP) systems rely on fixed-length numeric codes, making them vulnerable to replay attacks, phishing, and social engineering. This paper proposes an adaptive OTP generation framework that integrates AI-based risk assessment with context-aware two-factor authentication. The proposed system evaluates contextual metadata—including device information, geolocation, and user behavior—to classify risk levels in real time using a lightweight machine learning model. Based on the assessed risk, the OTP generation policy dynamically adjusts both length and character complexity. It produces simple six-digit numeric OTPs in low-risk scenarios and transitions to alphanumeric or symbolic OTPs exceeding ten characters in high-risk conditions. This adaptive strategy enhances security while preserving usability. The architecture is modular and platform-independent, enabling seamless deployment without cloud dependency or specialized hardware. Experimental evaluations demonstrate that the proposed system increases resistance to targeted attacks while maintaining authentication speed and user convenience. This work offers a practical and scalable enhancement to conventional authentication systems, particularly for mobile and resource-constrained environments.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 2","pages":"147-159"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11413252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147923906","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

CSI-based beamforming and localization for massive MIMO using deep learning 基于csi的大规模MIMO波束形成与深度学习定位

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-02-25 DOI: 10.23919/JCN.2025.000099

Mikael Ade Krisna Respati;Byung Moo Lee

{"title":"CSI-based beamforming and localization for massive MIMO using deep learning","authors":"Mikael Ade Krisna Respati;Byung Moo Lee","doi":"10.23919/JCN.2025.000099","DOIUrl":"https://doi.org/10.23919/JCN.2025.000099","url":null,"abstract":"In 6G technology, integrated sensing and communication (ISAC) is an emerging approach that enhances communication efficiency by enabling simultaneous sensing tasks. This paper leverages the multitasking capabilities of deep learning to optimize beamforming selection and user localization. A convolutional neural network (CNN) is employed to extract features from channel state information (CSI) data, which are then processed through a fully connected neural network to identify the optimal beamforming configuration and estimate user location. A weighted loss function is introduced to balance the importance of each task, ensuring that the model effectively prioritizes its objectives. Experimental results show that the proposed model achieves a Top-1 beamforming classification accuracy of up to 78.2% and a Top-3 accuracy of 99.21% with 64 antennas, while reducing localization error to as low as 2.11 meters. Compared to traditional single-task models, our approach improves classification accuracy by up to 7% and reduces localization error by up to 81%. This study highlights the potential of multitask learning in advancing ISAC capabilities and provides valuable insights for practical deployment in 6G systems.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 2","pages":"250-263"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11413838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147923912","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

Information for authors 作者信息

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-03-13 DOI: 10.23919/JCN.2025.000125

引用次数: 0

Minimum secrecy rate maximization for intelligent reflecting surface assisted multi-user communication system 智能反射面辅助多用户通信系统的最小保密率最大化

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-02-25 DOI: 10.23919/JCN.2025.000102

Siyao Chen;Jin Li;Haofei Lu;Yonghao Chen;Shixuan Qi;Xin Gao;Weigang Wang

{"title":"Minimum secrecy rate maximization for intelligent reflecting surface assisted multi-user communication system","authors":"Siyao Chen;Jin Li;Haofei Lu;Yonghao Chen;Shixuan Qi;Xin Gao;Weigang Wang","doi":"10.23919/JCN.2025.000102","DOIUrl":"https://doi.org/10.23919/JCN.2025.000102","url":null,"abstract":"Intelligent reflecting surface (IRS) has recently received considerable attention from the wireless communications research community. In this paper, we investigate a secure communication system aided by an IRS, comprising multi-user and a single eavesdropper. Specifically, under the unit modulus constraint at the IRS and the transmit power constraint at the access point (AP), we maximize the minimum secrecy rate by jointly optimizing the beamforming vectors at the multi-antenna AP and the phase shift matrix of the IRS. In order to solve the non-convex optimization problem, we propose an alternating optimization (AO) algorithm and obtain a suboptimal solution. Firstly, to optimize the beamforming vectors, the semidefinite relaxation (SDR) technique is employed. Secondly, with the aim of addressing the issue of phase shift matrix optimization at the IRS, the successive convex approximation (SCA) method is applied. Simulation results demonstrate that our proposed scheme performs better than the benchmark schemes in terms of both algorithm convergence and secrecy rate performance.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 2","pages":"136-146"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11413839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147923890","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

Sensing-assisted CSI feedback with echo prior information for mmWave massive MIMO systems 基于回波先验信息的毫米波大规模MIMO系统传感辅助CSI反馈

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-03-23 DOI: 10.23919/JCN.2025.000105

Chaojin Qing;Yuqiao Yang;Zilong Wang;Haowen Jiang;Linsi He;Pengfei Du

{"title":"Sensing-assisted CSI feedback with echo prior information for mmWave massive MIMO systems","authors":"Chaojin Qing;Yuqiao Yang;Zilong Wang;Haowen Jiang;Linsi He;Pengfei Du","doi":"10.23919/JCN.2025.000105","DOIUrl":"https://doi.org/10.23919/JCN.2025.000105","url":null,"abstract":"Accurate acquisition of downlink channel state information (CSI) at the base station (BS) is crucial in frequency division duplex (FDD) millimeter wave (mmWave) massive multiple-input multiple-output (mMIMO) systems. Although compressive sensing (CS) and deep learning (DL)-based CSI feedback methods demonstrate their advantages, the recovery accuracy of downlink CSI still faces severe challenges due to the facts of high path loss, significant user equipment (UE) estimation errors, and typical compression requirements, etc. To tackle these issues, improving the accuracy of downlink CSI recovery has become an urgent task. Inspired by sensing-assisted communication techniques, an echo sensing information-assisted CSI feedback with echo sensing information method is proposed in this paper. In the proposed method, the communication echo signals observed at the BS are utilized to extract the dedicated sensing prior information for the downlink CSI recovery. With the extracted sensing prior information, a CSI denoising method is developed to suppress the non-path entries of the downlink CSI matrix in the angular-delay domain, thereby improving the recovery accuracy of downlink CSI at the BS. The proposed method establishes an embedding framework for improving the recovery accuracy of downlink CSI in FDD mmWave mMIMO systems. In this framework, the echo sensing information-assisted CSI recovery algorithm is directly embedded in the BS receiver to enhance the recovery accuracy of downlink CSI without modifying the UE transmitter. Simulation results demonstrate that the proposed method improves the recovery accuracy of downlink CSI compared to the classic DL-based and the CS-based CSI feedback methods. Furthermore, the proposed method exhibits its robustness against the impact of parameter variations.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 2","pages":"199-212"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11454668","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147923940","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

Performance analysis of UAV-assisted RF-EH and NOMA for D2D wireless sensor networks with kNN-based user selection 基于knn用户选择的无人机辅助RF-EH和NOMA D2D无线传感器网络性能分析

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-02-25 DOI: 10.23919/JCN.2025.000090

Meyra Chusna Mayarakaca;Byung Moo Lee

{"title":"Performance analysis of UAV-assisted RF-EH and NOMA for D2D wireless sensor networks with kNN-based user selection","authors":"Meyra Chusna Mayarakaca;Byung Moo Lee","doi":"10.23919/JCN.2025.000090","DOIUrl":"https://doi.org/10.23919/JCN.2025.000090","url":null,"abstract":"Increasing demand for wireless sensor networks (WSNs) raises challenges in energy constraints and communication sustainability, especially in remote or disaster-affected areas where resources are limited. To address the constraints, this study proposes an integration of unmanned aerial vehicle (UAV)-assisted radio-frequency energy harvesting (RF-EH), non-orthogonal multiple access (NOMA), and device-to-device (D2D) communication to help with WSN energy constraints. The proposed system employs a UAV to transfer an RF signal for the WSN to perform EH, which will be used as a power source. The WSN operates in a D2D communication framework using NOMA communication. The system employs an EH time-switching (TS) protocol and dynamic power allocation to mitigate the impact of imperfect successive interference cancellation (SIC). The proposed system utilizes a machine learning-based k-nearest neighbor (kNN) algorithm to perform node selection at the UAV. Simulation results indicate that the kNN-based user selection improves the energy harvested by the WSN through the RF-EH process, which can reduce the BER by approximately 22.8%. Overall, the proposed system demonstrates superior performance by achieving lower bit error rate (BER) compared to conventional scenarios without the RF-EH process.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 2","pages":"213-222"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11413835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147923898","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

Online/offline learning to enable robust beamforming: Limited feedback meets deep generative models 在线/离线学习实现鲁棒波束形成：有限反馈满足深度生成模型

IF 3.2 3区计算机科学

Journal of Communications and Networks Pub Date : 2026-04-01 Epub Date: 2026-02-25 DOI: 10.23919/JCN.2025.000089

Ying Li;Zhidi Lin;Kai Li;Michael Minyi Zhang

{"title":"Online/offline learning to enable robust beamforming: Limited feedback meets deep generative models","authors":"Ying Li;Zhidi Lin;Kai Li;Michael Minyi Zhang","doi":"10.23919/JCN.2025.000089","DOIUrl":"https://doi.org/10.23919/JCN.2025.000089","url":null,"abstract":"Robust beamforming is a pivotal technique in massive multiple-input multiple-output (MIMO) systems as it mitigates interference among user equipment (UE). One current risk-neutral approach to robust beamforming is the stochastic weighted minimum mean square error method (WMMSE). However, this method necessitates statistical channel information, which is typically inaccessible, particularly in fifth-generation new radio frequency division duplex cellular systems with limited feedback. To tackle this challenge, we propose a novel approach that leverages a channel variational auto-encoder (CVAE) to simulate channel behaviors using limited feedback, eliminating the need for specific distribution assumptions present in existing methods. To seamlessly integrate model learning into practical wireless communication systems, this paper introduces two learning strategies to prepare the CVAE model for practical deployment. Firstly, motivated by the digital twin technology, we advocate employing a high-performance channel simulator to generate training data, enabling pretraining of the proposed CVAE while ensuring non-disruption to the practical wireless communication system. Moreover, we present an alternative online method for CVAE learning, where online training data is sourced based on channel estimations using Type II codebook. Numerical results demonstrate the effectiveness of these strategies, highlighting their exceptional performance in channel generation and robust beamforming applications.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"28 2","pages":"160-172"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11413254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147923905","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