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  Subjects -> ELECTRONICS (Total: 202 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advanced Materials Technologies     Hybrid Journal  
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 9)
Advances in Electronics     Open Access   (Followers: 99)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Power Electronics     Open Access   (Followers: 39)
Advancing Microelectronics     Hybrid Journal  
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 28)
Annals of Telecommunications     Hybrid Journal   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 15)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal  
Batteries     Open Access   (Followers: 9)
Batteries & Supercaps     Hybrid Journal   (Followers: 4)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 31)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 304)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 2)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 123)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 108)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 103)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage     Hybrid Journal   (Followers: 1)
Energy Storage Materials     Full-text available via subscription   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal  
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 10)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 100)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 56)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 2)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 52)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 3)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 42)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 2)
IEEE Open Journal of Industry Applications     Open Access   (Followers: 2)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 2)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 77)
IEEE Pulse     Hybrid Journal   (Followers: 5)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 22)
IEEE Solid-State Circuits Letters     Hybrid Journal   (Followers: 2)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 365)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 74)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 59)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 38)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 13)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 45)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 221)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 76)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 40)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 27)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 79)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 4)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 79)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 11)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 16)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 59)
IET Smart Grid     Open Access   (Followers: 1)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 13)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 12)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 12)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 37)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronic Science and Technology     Open Access   (Followers: 1)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 3)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 182)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 1)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 31)
Journal of Power Electronics     Hybrid Journal   (Followers: 1)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 26)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 28)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 9)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 4)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 11)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 56)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Solid State Electronics Letters     Open Access  
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 1)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
Visión Electrónica : algo más que un estado sólido     Open Access   (Followers: 1)
Wireless and Mobile Technologies     Open Access   (Followers: 6)

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Similar Journals
Journal Cover
China Communications
Journal Prestige (SJR): 0.314
Citation Impact (citeScore): 2
Number of Followers: 9  
  Full-text available via subscription Subscription journal
ISSN (Online) 1673-5447
Published by IEEE Homepage  [228 journals]
  • Front and back cover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Guest editorial: Artificial intelligence (AI)-driven spectrum management
    • Authors: Zan Li;Zhiguo Ding;Jia Shi;Walid Saad;Lie-Liang Yang;
      Abstract: Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle (UAV) communication to smart cognitive networks and massive Internet of Things (IoT) systems. Enabling these emerging applications over the fifth generation (5G) of wireless cellular systems requires meeting numerous challenges pertaining to spectrum sharing and management. In fact, most 5G applications will be highly reliant on intelligent spectrum management techniques, which should adapt to dynamic network environments while also guaranteeing high reliability and high quality-of-experience (QoE). In this context, the use of artificial intelligence (AI) techniques that include deep learning, convolutional neural networks, and reinforcement learning, among many others, is expected to play a very important role in paving the way towards truly AI-driven spectrum management, thus enabling tomorrow's smart city services. Therefore, it has become imperative to investigate and apply AI techniques to solve emerging spectrum management problems in various wireless networks. This includes leveraging AI to address a wide range of wireless networking challenges ranging from network management to dynamic spectrum sharing and resource management.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • A broad learning-driven network traffic analysis system based on fog
           computing paradigm
    • Authors: Xiting Peng;Kaoru Ota;Mianxiong Dong;
      Pages: 1 - 13
      Abstract: The development of communication technologies which support traffic-intensive applications presents new challenges in designing a real-time traffic analysis architecture and an accurate method that suitable for a wide variety of traffic types. Current traffic analysis methods are executed on the cloud, which needs to upload the traffic data. Fog computing is a more promising way to save bandwidth resources by offloading these tasks to the fog nodes. However, traffic analysis models based on traditional machine learning need to retrain all traffic data when updating the trained model, which are not suitable for fog computing due to the poor computing power. In this study, we design a novel fog computing based traffic analysis system using broad learning. For one thing, fog computing can provide a distributed architecture for saving the bandwidth resources. For another, we use the broad learning to incrementally train the traffic data, which is more suitable for fog computing because it can support incremental updates of models without retraining all data. We implement our system on the Raspberry Pi, and experimental results show that we have a 98% probability to accurately identify these traffic data. Moreover, our method has a faster training speed compared with Convolutional Neural Network (CNN).
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Generative neural network based spectrum sharing using linear sum
           assignment problems
    • Authors: Ahmed B. Zaky;Joshua Zhexue Huang;Kaishun Wu;Basem M. ElHalawany;
      Pages: 14 - 29
      Abstract: Spectrum management and resource allocation (RA) problems are challenging and critical in a vast number of research areas such as wireless communications and computer networks. The traditional approaches for solving such problems usually consume time and memory, especially for large-size problems. Recently different machine learning approaches have been considered as potential promising techniques for combinatorial optimization problems, especially the generative model of the deep neural networks. In this work, we propose a resource allocation deep autoencoder network, as one of the promising generative models, for enabling spectrum sharing in underlay device-to-device (D2D) communication by solving linear sum assignment problems (LSAPs). Specifically, we investigate the performance of three different architectures for the conditional variational autoencoders (CVAE). The three proposed architecture are the convolutional neural network (CVAE-CNN) autoencoder, the feed-forward neural network (CVAE-FNN) autoencoder, and the hybrid (H-CVAE) autoencoder. The simulation results show that the proposed approach could be used as a replacement of the conventional RA techniques, such as the Hungarian algorithm, due to its ability to find solutions of LASPs of different sizes with high accuracy and very fast execution time. Moreover, the simulation results reveal that the accuracy of the proposed hybrid autoencoder architecture outperforms the other proposed architectures and the state-of-the-art DNN techniques.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Finite-state Markov wireless channel modeling for railway tunnel
    • Authors: Cuiran Li;Ling Liu;Jianli Xie;
      Pages: 30 - 39
      Abstract: In recent years, high-speed railways (HSRs) have developed rapidly with a high transportation capacity and high comfort level. A tunnel is a complex high-speed rail terrain environment. It is very important to establish an accurate channel propagation model for a railway tunnel environment to improve the safety of HSR operation. In this paper, a method for finite-state Markov chain (FSMC) channel modeling with least squares fitting based on non-uniform interval division is proposed. First, a path loss model is obtained according to measured data. The communication distance between the transmitter and receiver in the tunnel is non-uniformly divided into several large non-overlapping intervals based on the path loss model. Then, the Lloyd-Max quantization method is used to determine the threshold of the signal-to-noise ratio (SNR) and the channel state quantization value and obtain the FSMC state transition probability matrix. Simulation experiments show that the proposed wireless channel model has a low mean square error (MSE) and can accurately predict the received signal power in a railway tunnel environment.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Heterogeneous network selection optimization algorithm based on a Markov
           decision model
    • Authors: Jianli Xie;Wenjuan Gao;Cuiran Li;
      Pages: 40 - 53
      Abstract: A network selection optimization algorithm based on the Markov decision process (MDP) is proposed so that mobile terminals can always connect to the best wireless network in a heterogeneous network environment. Considering the different types of service requirements, the MDP model and its reward function are constructed based on the quality of service (QoS) attribute parameters of the mobile users, and the network attribute weights are calculated by using the analytic hierarchy process (AHP). The network handoff decision condition is designed according to the different types of user services and the time-varying characteristics of the network, and the MDP model is solved by using the genetic algorithm and simulated annealing (GA-SA), thus, users can seamlessly switch to the network with the best long-term expected reward value. Simulation results show that the proposed algorithm has good convergence performance, and can guarantee that users with different service types will obtain satisfactory expected total reward values and have low numbers of network handoffs.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Inter-data commonality detection for spectrum monitoring in wireless
           sensor networks
    • Authors: Zhijuan Hu;Danyang Wang;Chenxi Li;Tingting Wang;
      Pages: 54 - 65
      Abstract: Cooperative spectrum monitoring with multiple sensors has been deemed as an efficient mechanism for improving the monitoring accuracy and enlarging the monitoring area in wireless sensor networks. However, there exists redundancy among the spectrum data collected by a sensor node within a data collection period, which may reduce the data uploading efficiency. In this paper, we investigate the inter-data commonality detection which describes how much two data have in common. We define common segment set and divide it into six categories firstly, then a method to measure a common segment set is conducted by extracting commonality between two files. Moreover, the existing algorithms fail in finding a good common segment set, so Common Data Measurement (CDM) algorithm that can identify a good common segment set based on inter-data commonality detection is proposed. Theoretical analysis proves that CDM algorithm achieves a good measurement for the commonality between two strings. In addition, we conduct an synthetic dataset which are produced randomly. Numerical results shows that CDM algorithm can get better performance in measuring commonality between two binary files compared with Greedy-String-Tiling (GST) algorithm and simple greedy algorithm.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Cross-band spectrum prediction based on deep transfer learning
    • Authors: Fandi Lin;Jin Chen;Jiachen Sun;Guoru Ding;Ling Yu;
      Pages: 66 - 80
      Abstract: Spectrum prediction is a promising technology to infer future spectrum state by exploiting inherent patterns of historical spectrum data. In practice, for a given spectrum band of interest, when facing relatively scarce historical data, spectrum prediction based on traditional learning methods does not work well. Thus, this paper proposes a cross-band spectrum prediction model based on transfer learning. Firstly, by analysing service activities and computing the distances between various frequency points based on Dynamic Time Warping, the similarity between spectrum bands has been verified. Next, the features, which mainly affect the performance of transfer learning in the crossband spectrum prediction, are explored by leveraging transfer component analysis. Then, the effectiveness of transfer learning for the cross-band spectrum prediction has been demonstrated. Further, experimental results with real-world spectrum data demonstrate that the performance of the proposed model is better than the state-of-the-art models when the historical spectrum data is limited.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Collaborative spectrum sensing for illegal drone detection: A deep
           learning-based image classification perspective
    • Authors: Huichao Chen;Zheng Wang;Linyuan Zhang;
      Pages: 81 - 92
      Abstract: Drones, also known as mini-unmanned aerial vehicles (UAVs), are enjoying great popularity in recent years due to their advantages of low cost, easy to pilot and small size, which also makes them hard to detect. They can provide real time situational awareness information by live videos or high definition pictures and pose serious threats to public security. In this article, we combine collaborative spectrum sensing with deep learning to effectively detect potential illegal drones with states of high uncertainty. First, we formulate the detection of potential illegal drones under illegitimate access and rogue power emission as a quaternary hypothesis test problem. Then, we propose an algorithm of image classification based on convolutional neural network which converts the cooperative spectrum sensing data at a sensing slot into one image. Furthermore, to exploit more information and improve the detection performance, we develop a trajectory classification algorithm which converts the flight process of the drones in consecutive multiple sensing slots into trajectory images. In addition, simulations are provided to verify the proposed methods' performance under various parameter configurations.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Deep learning based physical layer security of D2D underlay cellular
    • Authors: Lixin Li;Youbing Hu;Huisheng Zhang;Wei Liang;Ang Gao;
      Pages: 93 - 106
      Abstract: In order to improve the physical layer security of the device-to-device (D2D) cellular network, we propose a collaborative scheme for the transmit antenna selection and the optimal D2D pair establishment based on deep learning. Due to the mobility of users, using the current channel state information to select a transmit antenna or establish a D2D pair for the next time slot cannot ensure secure communication. Therefore, in this paper, we utilize the Echo State Network (ESN) to select the transmit antenna and the Long Short-Term Memory (LSTM) to establish the D2D pair. The simulation results show that the LSTM-based and ESN-based collaboration scheme can effectively improve the security capacity of the cellular network with D2D and increase the life of the base station.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Passive localization of signal source based on UAVs in complex environment
    • Authors: Pengwu Wan;Qiongdan Huang;Guangyue Lu;Jin Wang;Qianli Yan;Yufei Chen;
      Pages: 107 - 116
      Abstract: For the influence caused by multipath fading and non-line-of-sight (NLOS) transmission, it is challenging to accurately localize a moving signal source in complex environment by using the wireless sensor network (WSN) on the ground. In this paper, we establish a special WSN in the sky to address this challenge, where each sensor is loaded on an unmanned aerial vehicle (UAV) and the operation center of all the UAVs is fixed on the ground. Based on the analyzing of the optimal distribution and the position error calibration of all the sensors, we formulate the localization scheme to estimate the position of the target source, which combines the time difference of arrival (TDOA) method and the frequency difference of arrival (FDOA) method. Then by employing the semidefinite programming approach, we accurately obtain the position and velocity of the signal source. In the simulation, the validity of the proposed method is verified through the performance comparison.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Face image recognition based on convolutional neural network
    • Authors: Guangxin Lou;Hongzhen Shi;
      Pages: 117 - 124
      Abstract: With the continuous progress of The Times and the development of technology, the rise of network social media has also brought the "explosive" growth of image data. As one of the main ways of People's Daily communication, image is widely used as a carrier of communication because of its rich content, intuitive and other advantages. Image recognition based on convolution neural network is the first application in the field of image recognition. A series of algorithm operations such as image eigenvalue extraction, recognition and convolution are used to identify and analyze different images. The rapid development of artificial intelligence makes machine learning more and more important in its research field. Use algorithms to learn each piece of data and predict the outcome. This has become an important key to open the door of artificial intelligence. In machine vision, image recognition is the foundation, but how to associate the low-level information in the image with the high-level image semantics becomes the key problem of image recognition. Predecessors have provided many model algorithms, which have laid a solid foundation for the development of artificial intelligence and image recognition. The multi-level information fusion model based on the VGG16 model is an improvement on the fully connected neural network. Different from full connection network, convolutional neural network does not use full connection method in each layer of neurons of neural network, but USES some nodes for connection. Although this method reduces the computation time, due to the fact that the convolutional neural network model will lose some useful feature information in the process of propagation and calculation, this paper improves the model to be a multi-level information fusion of the convolution calculation method, and further recovers the discarded feature information, so as to improve the recognition rate of the image. VGG divides the netwo-k into five groups (mimicking the five layers of AlexNet), yet it USES 3∗3 filters and combines them as a convolution sequence. Network deeper DCNN, channel number is bigger. The recognition rate of the model was verified by 0RL Face Database, BioID Face Database and CASIA Face Image Database.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Cooperative privacy provisioning for energy harvesting based cognitive
           multi-relay networks
    • Authors: Dawei Wang;Wei Liang;Xiaoyu Hu;Daosen Zhai;Di Zhang;
      Pages: 125 - 137
      Abstract: In order to provide privacy provisioning for the secondary information, we propose an energy harvesting based secure transmission scheme for the cognitive multi-relay networks. In the proposed scheme, two secondary relays harvest energy to power the secondary transmitter and assist the secondary secure transmission without interfere the secondary transmission. Specifically, the proposed secure transmission policy is implemented into two phases. In the first phase, the secondary transmitter transmits the secrecy information and jamming signal through the power split method. After harvesting energy from a fraction of received radio-frequency signals, one secondary relay adopts the amplify-and-forward relay protocol to assist the secondary secure transmission and the other secondary relay just forwards the new designed jamming signal to protect the secondary privacy information and degrade the jamming interference at the secondary receiver. For the proposed scheme, we first analyze the average secrecy rate, the secondary secrecy outage probability, and the ergodic secrecy rate, and derive their closed-form expressions. Following the above results, we optimally allocate the transmission power such that the secrecy rate is maximized under the secrecy outage probability constraint. For the optimization problem, an AI based simulated annealing algorithm is proposed to allocate the transmit power. Numerical results are presented to validate the performance analytical results and show the performance superiority of the proposed scheme in terms of the average secrecy rate.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Spectrum sensing based on deep learning classification for cognitive
    • Authors: Shilian Zheng;Shichuan Chen;Peihan Qi;Huaji Zhou;Xiaoniu Yang;
      Pages: 138 - 148
      Abstract: Spectrum sensing is a key technology for cognitive radios. We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classification. We normalize the received signal power to overcome the effects of noise power uncertainty. We train the model with as many types of signals as possible as well as noise data to enable the trained network model to adapt to untrained new signals. We also use transfer learning strategies to improve the performance for real-world signals. Extensive experiments are conducted to evaluate the performance of this method. The simulation results show that the proposed method performs better than two traditional spectrum sensing methods, i.e., maximum-minimum eigenvalue ratio-based method and frequency domain entropy-based method. In addition, the experimental results of the new untrained signal types show that our method can adapt to the detection of these new signals. Furthermore, the real-world signal detection experiment results show that the detection performance can be further improved by transfer learning. Finally, experiments under colored noise show that our proposed method has superior detection performance under colored noise, while the traditional methods have a significant performance degradation, which further validate the superiority of our method.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • EARS: Intelligence-driven experiential network architecture for automatic
           routing in software-defined networking
    • Authors: Yuxiang Hu;Ziyong Li;Julong Lan;Jiangxing Wu;Lan Yao;
      Pages: 149 - 162
      Abstract: Software-Defined Networking (SDN) adapts logically-centralized control by decoupling control plane from data plane and provides the efficient use of network resources. However, due to the limitation of traditional routing strategies relying on manual configuration, SDN may suffer from link congestion and inefficient bandwidth allocation among flows, which could degrade network performance significantly. In this paper, we propose EARS, an intelligence-driven experiential network architecture for automatic routing. EARS adapts deep reinforcement learning (DRL) to simulate the human methods of learning experiential knowledge, employs the closed-loop network control mechanism incorporating with network monitoring technologies to realize the interaction with network environment. The proposed EARS can learn to make better control decision from its own experience by interacting with network environment and optimize the network intelligently by adjusting services and resources offered based on network requirements and environmental conditions. Under the network architecture, we design the network utility function with throughput and delay awareness, differentiate flows based on their size characteristics, and design a DDPG-based automatic routing algorithm as DRL decision brain to find the near-optimal paths for mice and elephant flows. To validate the network architecture, we implement it on a real network environment. Extensive simulation results show that EARS significantly improve the network throughput and reduces the average packet delay in comparison with baseline schemes (e.g. OSPF, ECMP).
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Optimal power allocation with limited feedback of channel state
           information in multi-user MIMO systems
    • Authors: Kusi Ankrah Bonsu;Weiwei Zhou;Su Pan;Yan Yan;
      Pages: 163 - 175
      Abstract: In this paper, an expression for the user's achievable data rate in the multi-user multiple-input multiple-output (MU-MIMO) system with limited feedback (LF) of channel state information (CSI) is derived. The energy efficiency (EE) is optimized through power allocation under quality of service (QoS) constraints. Based on mathematical equivalence and Lagrange multiplier approach, an energy-efficient unequal power allocation (EEUPA) with LF of CSI scheme is proposed. The simulation results show that as the number of transmitting antennas increases, the EE also increases which is promising for the next generation wireless communication networks. Moreover, it can be seen that the QoS requirement has an effect on the EE of the system. Ultimately, the proposed EEUPA with LF of CSI algorithm performs better than the existing energy-efficient equal power allocation (EEEPA) with LF of CSI schemes.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • A personalized search model using online social network data based on a
           holonic multiagent system
    • Authors: Meijia Wang;Qingshan Li;Yishuai Lin;
      Pages: 176 - 205
      Abstract: Personalized search utilizes user preferences to optimize search results, and most existing studies obtain user preferences by analyzing user behaviors in search engines that provide click-through data. However, the behavioral data are noisy because users often clicked some irrelevant documents to find their required information, and the new user cold start issue represents a serious problem, greatly reducing the performance of personalized search. This paper attempts to utilize online social network data to obtain user preferences that can be used to personalize search results, mine the knowledge of user interests, user influence and user relationships from online social networks, and use this knowledge to optimize the results returned by search engines. The proposed model is based on a holonic multiagent system that improves the adaptability and scalability of the model. The experimental results show that utilizing online social network data to implement personalized search is feasible and that online social network data are significant for personalized search.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Quantitative survivability analysis using probability model checking: A
           study of cluster-based vehicle networks with dual cluster heads
    • Authors: Li Jin;Guoan Zhang;Jue Wang;Hao Zhu;Wei Duan;
      Pages: 206 - 219
      Abstract: As an important part of future 5G wireless networks, a vehicular network demands safety, reliability and connectivity. In this context, networking survivability is usually considered an important metric to evaluate network performance. In this paper, we propose a survivability model for vehicle communication networking based on dual cluster heads, wherein a backup cluster head (CH) will be activated if the primary CH fails, thereby effectively enhancing the network lifetime. Additionally, we introduce a software rejuvenation strategy for the prime CH to further improve the survivability of the entire network. Using the Probabilistic Symbolic Model Checker (PRISM), we verify and discuss the proposed survivability model via numerical simulations. The results show that network survivability can be effectively improved by introducing an additional CH and further enhanced by adopting the software rejuvenation technique.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Improved clustering and resource allocation for ultra-dense networks
    • Authors: Xinji Tian;Wenjie Jia;
      Pages: 220 - 231
      Abstract: To reduce the interference among small cells of Ultra-Dense Networks (UDN), an improved Clustering-Assisted Resource Allocation (CARA) scheme is proposed in this paper. The proposed scheme is divided into three steps. First, an Interference-Limited Clustering Algorithm (ILCA) based on interference graph corresponding to the interference relationship between Femtocell Base Stations (FBSs), is proposed to group FBSs into disjoint clusters, in which a pre-threshold is set to constrain the sum of interference in each cluster, and a Cluster Head (CH) is selected for each cluster. Then, CH performs a two-stage sub-channel allocation within its associated cluster, where the first stage assigns one sub-channel to each user of the cluster and the second stage assigns a second sub-channel to some users. Finally, a power allocation method is designed to maximize throughput for a given clustering and sub-channel configuration. Simulation results indicate that the proposed scheme distributes FBSs into each cluster more evenly, and significantly improves the system throughput compared with the existing schemes in the same scenario.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Cache hit ratio maximization in device-to-device communications overlaying
           cellular networks
    • Authors: Liang Zhong;Xueqian Zheng;Yong Liu;Mengting Wang;Yang Cao;
      Pages: 232 - 238
      Abstract: This paper investigates the content placement problem to maximize the cache hit ratio in device-to-device (D2D) communications overlaying cellular networks. We consider offloading contents by users themselves, D2D communications and multicast, and we analyze the relationship between these offloading methods and the cache hit ratio. Based on this relationship, we formulate the content placement optimization as a cache hit ratio maximization problem, and propose a heuristic algorithm to solve it. Numerical results demonstrate that the proposed scheme can outperform existing schemes in terms of the cache hit ratio.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
  • Towards the design of ethics aware systems for the Internet of Things
    • Authors: Sahil Sholla;Roohie Naaz Mir;Mohammad Ahsan Chishti;
      Pages: 239 - 252
      Abstract: The Internet of Things promises to offer numerous societal benefits by providing a spectrum of user applications. However, ethical ramifications of adopting such pervasive technology on a society-wide scale have not been adequately considered. Smart things endowed with artificial intelligence may carry out decisions that entail ethical consequences. It is assumed that the functioning of a smart device does not involve any ethical responsibility vis-a-vis its application context. Such a perspective may precipitate situations that endanger essential human values or cause physical or emotional harm. Therefore, it is necessary to consider the design of ethics within intelligent systems to safeguard human interests. In order to address these concerns, we propose a novel method based on Boolean algebra that enables a machine to exhibit varying ethical behaviour by employing the concept of ethics categories and ethics modes. Such enhancement of smart things offers a way to design ethically compliant smart devices and paves way for human friendly technology ecosystems.
      PubDate: Feb. 2020
      Issue No: Vol. 17, No. 2 (2020)
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