IET Communications最新文献

{"title":"Real-world UAV recognition based on radio frequency fingerprinting with transformer","authors":"Jia Han,&nbsp;Zhiyong Yu,&nbsp;Jian Yang","doi":"10.1049/cmu2.70004","DOIUrl":"https://doi.org/10.1049/cmu2.70004","url":null,"abstract":"<p>Many unmanned aerial vehicles (UAVs) require the installation of automatic dependent surveillance-broadcast (ADS-B) transponders to facilitate their daily management. However, since ADS-B transponders do not have a good security mechanism, they introduce problems including impersonation, spoofing, and private changing of the registration number, making UAV surveillance inconvenient. Radio frequency fingerprinting (RFF) recognition is carried out by utilizing the fact that different electronic devices in a given transponder will affect the transmitted signals, resulting in the formation of RFF features that are unique to the transponder and difficult to forge. Therefore, in this work, a deep learning architecture is proposed to classify UAVs based on ADS-B signals, and a multi-head self-attention RFF recognition model is constructed using variational mode decomposition (VMD) of the preamble data and a transformer encoder for validation. The model achieves better results in terms of noise, Doppler shifting, and multipath effect interference. This method demonstrates that the transformer architecture of natural language processing, combined with appropriate data preprocessing methods, can also be used for RFF recognition, and provides advantages in accuracy and robustness (67.83% vs. 64.17%).</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"QoE-based dynamic resource allocation for heterogeneous smart distribution grids","authors":"You Li,&nbsp;Yan Huo,&nbsp;Zhongguo Zhou,&nbsp;Qinghe Gao,&nbsp;Tao Jing,&nbsp;Tao Yan,&nbsp;Sisi Xiao","doi":"10.1049/cmu2.70001","DOIUrl":"https://doi.org/10.1049/cmu2.70001","url":null,"abstract":"<p>In the realm of conventional smart distribution grid resource allocation, the prevalent issue resides in its narrow focus on base station capacity, striving to optimize resource allocation for base station communication while disregarding the genuine requirements on the user side. This inadvertently leads to excessive squandering of wireless resources, despite already fulfilling the fundamental service demands of terminal operations. This article, while taking into account the capacity of base stations, introduces an innovative approach by amalgamating the terminal operations concerning data rate, latency, and packet loss rate. Through the construction of a Quality of Experience (QoE) evaluation framework, a scenario is realized within which user experience requirements are ensured by terminals in various practical settings of smart distribution grids, without wireless resources being needlessly dissipated. In this article, the dynamic resource allocation is tackled using Deep Q-Networks (DQN), while the reward function is formulated based on QoE. The simulation results, which track the accumulation of reward values throughout the entire operational process, provide substantial validation for the effectiveness and practicality of the ultimately formulated dynamic resource allocation scheme.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"Effective neural coding method based on maximum entropy","authors":"Dongbin He,&nbsp;Aiqun Hu,&nbsp;Kaiwen Sheng","doi":"10.1049/cmu2.70000","DOIUrl":"https://doi.org/10.1049/cmu2.70000","url":null,"abstract":"<p>There are a large number of perceptrons in the new bionic network. To improve the efficiency of data transmission in the bionic network, a maximum entropy neural coding method is proposed. By drawing on the characteristics of human nerve conduction, the authors designed a data transmission model and adopted an adaptive spike firing rate encoding strategy to maximize information entropy, thereby improving encoding efficiency. The simulation experiment results and the applications of the maximum entropy neural coding method to fault detection and seismic detection have validated the effectiveness of the maximum entropy neural coding method. Even if there is certain data distortion, the statistical characteristics of the decoded data and the fault detection performance will not be affected. This research not only proposes novel approaches for efficient data transmission in bionic network, but also identifies possible directions for enhancing data transmission efficiency through the integration of task-oriented semantic communications in future applications.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"AoI-optimal path planning for UAV-assisted data collection with heterogeneous information aging speed","authors":"Chen Xie,&nbsp;Binbin Wu,&nbsp;Zihao Pan,&nbsp;Daoxing Guo,&nbsp;Wenfeng Ma","doi":"10.1049/cmu2.12768","DOIUrl":"https://doi.org/10.1049/cmu2.12768","url":null,"abstract":"<p>This article investigates a problem involving the collection of data from sensor nodes (SNs) with heterogeneous information aging speed (IAS) by an unmanned aerial vehicle (UAV) in a dense obstacle environment. The objective is to minimize the average age of information (AoI) of the SNs through UAV path planning. The problem is challenging due to the tight coupling of obstacle avoidance, information timeliness, and the heterogeneity of SNs. Directly solving this path planning problem is difficult, and the conventional approach involves planning the access sequence without considering obstacle avoidance and then optimizing the UAV trajectory while incorporating safety constraints. However, optimizing the trajectory for safe flight introduces changes in the flight time cost, resulting in the average AoI not reaching its minimum value. To address this, a UAV safe flight network is first established by generating trajectories using a combination of A*-based and successive convex approximation (SCA)-based algorithms. Subsequently, a genetic algorithm (GA)-based method is employed and compared with the time greedy strategy. The numerical results demonstrate that the time greedy strategy, which aligns with intuitive understanding, can achieve a smaller total UAV flight time, while the proposed method effectively minimizes the average AoI of SNs.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12768","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"A neural coding method based on feature sensing","authors":"Dongbin He,&nbsp;Aiqun Hu,&nbsp;Kaiwen Sheng","doi":"10.1049/cmu2.12882","DOIUrl":"https://doi.org/10.1049/cmu2.12882","url":null,"abstract":"<p>The novel network contains many sensors, which greatly heightens data transmission burdens. Some networks require the data perceived by sensors for a period to make decisions. Drawing inspiration from the human neural conduction mechanism, a waveform data encoding method called feature sensing neural coding (FSNC) is proposed to enhance network data transmission efficiency. It involves feature decomposition of information and subsequent non-linear encoding of feature coefficients for data transmission. This approach exploits the unique neuronal responses to diverse stimuli and the inherent non-linear characteristics of human neural coding. Finally, taking the speech signal and seismic wave signal as examples, the effectiveness of FSNC is verified by simulating the auditory nerve conduction process with frequency as a feature according to the mechanism of travelling wave motion of the basilar membrane in the cochlea. Moreover, experiments on seismic waveform signals have demonstrated the wide applicability of FSNC. Compared with traditional speech coding schemes, the FSNC bit rate is only 6.4 kbps, which greatly reduces the amount of data transmitted. Not only that, FSNC also has a certain fault tolerance, and parallel transmission can also greatly increase the transmission rate. This research provides new ideas for efficient data transmission over new networks.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12882","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"Research on automatic modulation recognition of shortwave signals in few-shot scenarios based on knowledge distillation","authors":"Qi Yao,&nbsp;Jingjing Yang,&nbsp;Ming Huang","doi":"10.1049/cmu2.12881","DOIUrl":"https://doi.org/10.1049/cmu2.12881","url":null,"abstract":"<p>Automatic modulation recognition plays an important role in wireless communication and radio regulation. Existing deep learning-based automatic modulation recognition techniques perform well with large datasets and high computational power but require significant resources for labelled data and complex pre-processing. This paper proposes a multi-information fusion method for few-shot modulation recognition, which involves converting <i>I</i>/<i>Q</i> signals into <i>A</i>/<i>P</i> signals and training with a combination of VGG and LSTM network models. An ensemble knowledge distillation (EKD) approach is employed to streamline the network model, meeting the demands for deploying neural network models on compact devices. Experimental results demonstrate that using only 1% of the shortwave modulation signal dataset as the training set, the proposed model achieves an average classification accuracy of 71.08% under all signal-to-noise ratios, surpassing the currently popular deep learning models. Moreover, two small-scale networks, MobileNetV3 and convolutional neural network are trained, through EKD. Compared to the teacher network, the floating-point operations of the distilled models are reduced by 99.8% and 99.7%, respectively, and the average prediction accuracy only decreases by 16.05% and 8.09%. The lightweight, few-shot networks designed in this study for shortwave modulation signals aim to achieve fast and accurate modulation recognition on compact devices.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12881","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"Fine-grained multi-path channel estimation and matched reception by single metasurface antenna","authors":"Yinuo Hao,&nbsp;Liang Jin,&nbsp;Shuaifang Xiao","doi":"10.1049/cmu2.12871","DOIUrl":"https://doi.org/10.1049/cmu2.12871","url":null,"abstract":"<p>This paper investigates methods to enhance antenna's channel information extraction capabilities in wireless communications, particularly in challenging multi-path environments. Focusing on the issues of channel information loss due to multi-path superposition at the receiver and multi-path fading during wireless channel propagation, this paper utilizes metasurface antennas to rapidly reconfigure antenna patterns and construct high-dimensional projection spaces, thus improving information sensing resolution. Based on this, a channel-matched receiving pattern design method is proposed to mitigate the communication performance loss caused by multi-path fading. Furthermore, this paper analyses the comprehensive impact of various metasurface parameters on the performance of the proposed scheme, providing theoretical guidance for engineering implementation. Simulation results demonstrate that the proposed scheme can achieve the performance of multi-path channel estimation and reception close to those of multi-antenna arrays using a single radio frequency link.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12871","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"Predictive handover mechanism for seamless mobility in 5G and beyond networks","authors":"Thafer H. Sulaiman,&nbsp;Hamed S. Al-Raweshidy","doi":"10.1049/cmu2.12878","DOIUrl":"https://doi.org/10.1049/cmu2.12878","url":null,"abstract":"<p>Scalability is one of the important parameters for mobile communication networks of the present generation and further to the future 5G and beyond networks. When a user is in motion transferring from one cell site to another, then the handover procedure becomes important in the sense that it ensures that a user gets consistent connection without interruption. Nevertheless, the classic handover process in cellular networks has some sort of drawback like causing service interruptions, affecting packet transmission, and increased latency which is highly uncongenial to the evolving applications which have stringent requirement to latency. To overcome these challenges and improve the mobile handover in 5G and future mobile networks, this article puts forth a predictive handover mechanism using reinforcement learning algorithm. The RL algorithm outperforms the ML algorithm in several aspects. Compared to ML, RL has a higher handover success rate (∼95% vs. ∼90%), lower latency (∼30 ms vs. ∼40 ms), reduced failure rate (∼5% vs. ∼10%), and shorter disconnection time (∼50 ms vs. ∼70 ms). This demonstrates the RL algorithm's superior ability to adapt to dynamic network conditions.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"MMSE-based passive beamforming for reconfigurable intelligent surface aided millimeter wave MIMO","authors":"Prabhat Raj Gautam,&nbsp;Li Zhang,&nbsp;Pingzhi Fan","doi":"10.1049/cmu2.12873","DOIUrl":"https://doi.org/10.1049/cmu2.12873","url":null,"abstract":"<p>Reconfigurable intelligent surfaces (RISs) have emerged as propitious solution to configure random wireless channel into suitable propagation environment by adjusting a large number of low-cost passive reflecting elements. It is considered that narrowband downlink millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication is aided by deploying an RIS. Large antenna arrays are used to counter the huge propagation loss suffered by the mmWave signals. Hybrid precoding in which precoding is performed in digital and analog domains is employed to reduce the number of costly and power-consuming radio frequency (RF) chains. Passive beamforming at RIS is designed together with precoder and combiner through joint optimization problem to minimize the mean square error between the transmit signal and the estimate of signal at the receiver. The optimization problem is solved by an iterative procedure in which solution to the non-convex reflecting coefficients design problem is approximated by extracting the phases of the solution to unconstrained problem without unit amplitude constraint of the reflecting elements. It is shown that the proposed design principle also applies to the wideband channel. Simulation results show that the proposed design delivers performance better than existing state-of-the-art solutions, but at lower complexity.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12873","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}

{"title":"Enhancing intrusion detection against denial of service and distributed denial of service attacks: Leveraging extended Berkeley packet filter and machine learning algorithms","authors":"Nemalikanti Anand,&nbsp;Saifulla M A,&nbsp;Pavan Kumar Aakula,&nbsp;Raveendra Babu Ponnuru,&nbsp;Rizwan Patan,&nbsp;Chegireddy Rama Prakasha Reddy","doi":"10.1049/cmu2.12879","DOIUrl":"https://doi.org/10.1049/cmu2.12879","url":null,"abstract":"<p>As organizations increasingly rely on network services, the prevalence and severity of Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks have emerged as significant threats. The cornerstone of effectively addressing these challenges lies in the timely and precise detection capabilities offered by advanced intrusion detection systems (IDS). Hence, an innovative IDS framework is introduced that seamlessly integrates the extended Berkeley Packet Filter (eBPF) with powerful machine learning algorithms—specifically Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and TwinSVM—enabling unparalleled real-time detection of DDoS attacks. This cutting-edge solution provides a robust and scalable IDS framework to combat DoS and DDoS threats with high efficiency, leveraging eBPF's capabilities within the Linux kernel to bypass typical user space constraints. The methodology encompasses several key steps: (a) Collection of data from the renowned CIC-IDS-2017 repository; (b) Processing the raw data through a meticulous series of steps, including transmission, cleaning, reduction, and discretization; (c) Utilizing an ANOVA F-test for the extraction of critical features from the preprocessed data; (d) Application of various ML algorithms (DT, RF, SVM, and TwinSVM) to analyze the extracted features for potential intrusion; (e) Implementing an eBPF program to capture network traffic and harness trained model parameters for efficient attack detection directly within the kernel. The experimental results reveal outstanding accuracy rates of 99.38%, 99.44%, 88.73%, and 93.82% for DT, RF, SVM, and TwinSVM, respectively, alongside remarkable precision values of 99.71%, 99.65%, 84.31%, and 98.49%. This high-speed, accurate detection model is ideally suited for high-traffic environments such as data centers. Furthermore, its foundational architecture paves the way for future advancements, including the potential integration of eBPF with XDP to achieve even lower-latency packet processing. The experimental code is available at the GitHub repository link: https://github.com/NemalikantiAnand/Project.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12879","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}