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IEEE Workshop on Signal Processing Advances in Wireless communications (SPAWC)

作者： Jianping Zhang Pin-Hsun Lin Karl-Ludwig Besser Eduard A. Jorswieck Institute for Communications Technology Technische Universität Braunschweig Germany Department of Electrical and Computer Engineering Princeton University USA

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

In the classical wiretap channel, the transmitted messages are completely protected. This is inefficient when the number of communication devices increases immensely in the Internet of Things era. Latent variable secrecy (LVS) is a method that can improve transmission efficiency by protecting only the necessary part of the information. In this paper, we focus on the practical design of the LVS system including the following two parts: 1) Latent variable selection and extraction from a given database: to distinguish messages with high and low correlation to the latent variable, such that we can do more efficient protection, 2) Achievable transmission scheme and privacy amplification design to implement the wiretap coding. As a simple example, we compare the LVS rate by our design using BCH codes with full protection by wiretap coding transmitted through a binary symmetric wiretap channel with transition probabilities (0.01, 0.04). Under blocklength as 15 and message size as 3.5 (after rate matching), we show a 44.46% rate gain with information leakage upper bounded by 0.08 bit and a leakage reduction of 49.47% by the proposed grouping versus random grouping.

关键词： Codes Wireless networks Surveillance Forensics Simulation Oral communication Signal processing Encoding Protection Eavesdropping

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Jamming Resilient Multi-Channel Transmission for Cognitive Radio IoT-based Medical Networks

Jamming Resilient Multi-Channel Transmission for Cognitive R...

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作者： Khadr, Monette H. Bany Salameh, Haythem Ayyash, Moussa Elgala, Hany Almajali, Sufyan Electrical and Computer Engineering Department University at Albany United States Department of Network & Communications Engineering Al Ain University United Arab Emirates Department of Telecommunications Engineering Yarmouk University Jordan Department of Computing Information and Mathematical Sciences and Technology Chicago State University United States Computer Science Department Princess Sumaya University for Technology Jordan

The era of the Internet-of-things (IoT) comes with tremendous burdens on pre-existing network infrastructures and protocols due to spectrum scarcity and reliability concerns. Cognitive radio (CR) technology is proposed for IoT applications to alleviate the spectrum scarcity paradigm. In CR-IoTbased networks, the IoT devices/nodes share the spectrum with primary users (PUs). However, in order not to interfere with PUs communications and to conform with the elevating throughput requirements, efficient multi-radio/multi-channel assignment algorithms are required. Additionally, in order to ensure reliable transmission, algorithms need to be resilient to jamming attacks, which have detrimental impacts on network performance. In this paper, parallel-channel security-aware medium access control (PCS-MAC) is proposed as a probabilistic-based jamming resilient multi-channel assignment algorithm proposed for medical networks. PCS-MAC considers primary user activity, channel conditions, jamming attack levels, and data-rate requirements to provide spectrally efficient data transmission between CRIoT nodes subject to delay constraints under jamming attacks to assure the delivery of time-critical patient data. The performance of PCS-MAC is practically validated using the open large-scale future Internet-of-things (FIT) IoT-LAB testbed. Practical results show that our proposed algorithm significantly enhances network performance, yielding throughput rates that supersedes the stateof-the-art algorithms presented in literature. © 2022 KICS.

关键词： Cognitive radio

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Toward Enhanced Brain Tumor Segmentation in MRI: An Ensemble Deep Learning Approach

Toward Enhanced Brain Tumor Segmentation in MRI: An Ensemble...

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Canadian Conference on Electrical and computer engineering (CCECE)

作者： Shaimaa E. Nassar Ahmed Elnakib Abdallah S. Abdallah Mohamed A. El-Azim Electronics and Communications Engineering Department Faculty of Engineering Mansoura University Egypt Electrical and Computer Engineering Department School of Engineering Penn State Erie - The Behrend College PA USA

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

Convolutional neural networks (CNNs) have played a pivotal role in enhancing brain tumor segmentation techniques. In this research, we employed an integrated approach using three distinct CNN architectures: U-Net, SegNet, and DeepLabv3+, to segment brain tumors from MRI scans. The integration of these models’ outputs was accomplished through a smart majority voting technique (SMVT), which considers the accuracy levels of the individual networks. Our evaluation on the high-grade glioma (HGG) subset from the 2018 BraTS challenge revealed impressive dice similarity coefficients: 0.92 for the enhancing tumor (ET) region, 0.94 for the tumor core (TC), and 0.96 for the whole tumor (WT) area. These findings not only exhibit superior performance over several existing approaches but also underscore the effectiveness of ensemble deep learning models in medical image analysis.

关键词： Deep learning Image segmentation Solid modeling Three-dimensional displays Magnetic resonance imaging Brain modeling Convolutional neural networks

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Exploring Impact of Prioritizing Intra-Singer Acoustic Variations on Singer Embedding Extractor Construction for Singer Verification

Exploring Impact of Prioritizing Intra-Singer Acoustic Varia...

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Oriental COCOSDA International Conference on Speech Database and Assessments

作者： Sayaka Toma Tomoki Ariga Yosuke Higuchil Ichiju Hayasaka Rie Shigyo Tetsuji Ogawa Department of Communications and Computer Engineering Waseda University Tokyo Japan DAIICHIKOSHO CO. LTD. Tokyo Japan

ISBN: (数字)9798331506032

ISBN: (纸本)9798331506049

We explored the significance of prioritizing acoustic variations within singers while training a singer embedding ex-tractor for singer verification. Neural networks effective for speaker verification, like ECAPA-TDNN, may lead to in-creased false rejections as the number of identifiable speakers grows. Therefore, it is crucial to enhance the variation in training data per speaker. Singing voice, with its diverse ex-pressions and singing techniques, is believed to exhibit more intra-speaker variability compared to spoken voice. This study aimed to investigate the impact of intra-singer acous-tic variations on training singer embeddings. Experiments conducted with a self-constructed Japanese singing voice corpus revealed the following findings: 1) the importance of using multiple songs per singer, 2) the limited significance of increasing the total number of identifiable singers, and 3) the detrimental effects of discrepancies in singing technique between enrollment and verification data.

关键词： Training Databases Neural networks Training data Acoustics Data mining

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Deep Learning-Based Automatic Modulation Format Identification For I2V Visible Light Communication

Deep Learning-Based Automatic Modulation Format Identificati...

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National Conference on Radio Science (NSRC)

作者： Nancy A. Arafa Saied M. Abd El-Att Hossien B. Eldeeb Mohamed S. Arafa Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Computer and Communication Engineering Khalifa University Abu Dhabi UAE

The performance of Infrastructure-to-vehicle (I2V) visible light communication (VLC) links is influenced by multiple elements, rendering fixed modulation order inadequate for data transmission. Consequently, adaptive modulation techniques become necessary for optimal communication quality in different traffic scenarios. However, to enable proper modulation type selection and avoid unnecessary overhead, modulation format identification at the receiver end becomes crucial. Therefore, this paper proposes an automatic modulation format identification (AMFI) scheme based on deep learning (DL) specifically for the I2V-VLC application scenario. Two different features are considered, the first one utilizes the constellation diagram of received modulated signals, while the second is a novel scheme, it employs the Voronoi diagram. Various VLC modulation formats are further taken into account, including Q/8/16-phase shift keying (PSK) and 4/8/16/32/64-quadrature amplitude modulation (QAM). Benchmark pre-trained classifiers such as AlexNet, SqueezeNet, and GoogleNet are employed and their accuracies are compared. Additionally, the impact of different weather conditions on the model’s accuracies is investigated. The findings illustrate the efficiency of the proposed approach in accurately identifying the VLC modulation format, even in diverse weather conditions and at low signal-to-noise ratio values.

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Optimality of the Bussgang Linear MMSE Channel Estimator for MIMO Systems with 1-Bit ADCs

Optimality of the Bussgang Linear MMSE Channel Estimator for...

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IEEE Workshop on Signal Processing Advances in Wireless communications (SPAWC)

作者： Minhua Ding Italo Atzeni Antti Tölli A. Lee Swindlehurst Centre for Wireless Communications University of Oulu Finland Department of Electrical Engineering and Computer Science University of California Irvine USA

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

In this paper, we study the optimality of the Bussgang linear minimum mean squared error (BLMMSE) channel estimator for multiple-input multiple-output systems with 1-bit analog-to-digital converters. We compare the BLMMSE with the optimal minimum mean squared error (MMSE) channel estimator, which is generally non-linear, and we develop a novel framework based on the orthant probability of a multivariate normal distribution to compute the MMSE channel estimate. Then, we analyze the equivalence of the MMSE and BLMMSE channel estimators under specific assumptions on the channel correlation or pilot symbols. Interestingly, the BLMMSE channel estimator turns out to be optimal in several specific cases. Our study culminates with the presentation of a necessary and sufficient condition for the BLMMSE channel estimator to be optimal.

关键词： Wireless communication Sufficient conditions Correlation Conferences Channel estimation Symbols Signal processing Gaussian distribution MIMO communication Analog-digital conversion

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Power Control and Interference Pricing Strategies for Heterogeneous Networks With Renewable Energy Sources

Power Control and Interference Pricing Strategies for Hetero...

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作者： Zhou, Chengcheng Xu, Haitao Tang, Runze Lin, Ruijie Guo, Chao Han, Zhu University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Beijing Institute of Electronic System Engineering Beijing China China Academy of Information and Communications Technology Beijing China Beijing Electronics Science and Technology Institute Department of Electronic and Communication Engineering Beijing China University of Houston HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

In this article, the power control and interference pricing problems between the macro base station (MBS) and small cell base stations (SBSs) in Heterogeneous networks (HetNets) are investigated. To optimally allocate power resources and effectively manage the power resources to reduce interference in HetNets, an innovative Stackelberg differential game approach is proposed. In the proposed Stackelberg game, the SBSs control their transmit power to achieve cost minimization based on the interference price offered by the MBS. Given the optimal power control strategies of SBSs, the MBS can adjust the interference price to realize the objective optimization. Renewable energy sources are introduced into the proposed HetNets, and differential equations formulate the SBSs' dynamic energy. Meanwhile, the MBS's state is given by the dynamic spectrum resources. Then the differential game is imported to achieve optimal power control and interference pricing. The open-loop Nash equilibrium solutions are first analyzed for the MBS and SBSs. Then the feedback Nash equilibrium solutions are given. Under the feedback pattern, the proposed model's performances in the non-cooperative and cooperative situations are discussed. Numerical simulations are given to show the convergence and effectiveness of the proposed game approach. © 1967-2012 IEEE.

关键词： Power control

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Survey on Security Based Approach to Prevent Attacks in SDN Using IoT Framework 2

Survey on Security Based Approach to Prevent Attacks in SDN ...

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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Prabhu, V. Balamurugan, P. School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur Tamilnadu Chengalpattu603 203 India School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur Tamilnadu Chengalpattu603 203 India

ISBN: (纸本)9798350347579

Network evolution trendincludes Internet of Things (IoT) and Software-Defined Networking (SDN). By separating the data plane from the control plane, the software defined networking architectural framework is used and it will makes the network admins works more easily. SDN mainly focuses on network management and controls at the higher levels to monitoring and sharing the connection between the devices with the help of network connectivity in real time using the Internet of Things concepts. Almost in all the fields, IoT devices used so have to improve the security of IoT devices. The SDN has the centralized control logic, if the number of network traffic increases then centralized controller may not be handle all the network traffic requests at the same time, because the SDN controller is a single point of failure, its failure can bring the entire network down. The Software Defined Network (SDN) is easily exposed to various attacks mostly to DDoS attacks. Majority of the existing research is concentrated only on sensing of HR-DDoS attacks occurring over the control layer and not focusing on LR-DDoS attack occurring over the data layer because the accuracy of attacks on the LR-DDoS attacks are very low. This study mainly focusing on how to design the multi controller SDN architecture to improve the scalability, how to increase the detection accuracy of low-rate DDoS attacks on the SDN data layer and how to detect the attacks using machine learning algorithms. © 2023 IEEE.

关键词： Internet of things

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Augmented Node Placement Model in t-WSN Through Multiobjective Approach

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computers, Materials & Continua 2021年第12期69卷 3629-3644页

作者： Kalaipriyan Thirugnansambandam Debnath Bhattacharyya Jaroslav Frnda Dinesh Kumar Anguraj Jan Nedoma School of Computer Science and Engineering VIT UniversityChennai CampusTamilnaduIndia Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramGunturIndia Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026 ZilinaSlovakia Department of Telecommunications Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of Ostrava70833 Ostrava-PorubaCzech Republic

In Wireless Sensor Network(WSN),coverage and connectivity are the vital challenges in the target-based *** linear objective is to find the positions to cover the complete target nodes and connectivity between each sensor for data forwarding towards the base station given a grid with target points and a potential sensor placement *** this paper,a multiobjective problem on target-based WSN(t-WSN)is derived,which minimizes the number of deployed nodes,and maximizes the cost of coverage and sensing *** Evolutionary-based Non-Dominated Sorting Genetic Algorithm-II(NSGA-II)is incorporated to tackle this multiobjective problem *** problems are intended to solve different objectives of a problem ***-inspired algorithms address the NP-hard problem most effectively in recent *** NSGA-II,the Non-Dominated sorting preserves the better solution in different objectives simultaneously using dominance *** the diversity maintenance phase,density estimation and crowd comparison are the two components that balance the exploration and exploitation phase of the *** of NSGA-II on this multiobjective problem is evaluated in terms of performance indicators Overall Non-dominated Vector Generation(ONGV)and Spacing(SP).The simulation results show the proposed method performs outperforms the existing algorithms in different aspects of the model.

关键词： Focused wireless sensor network m-coverage k-connectivity problem non-dominated sorting NSGA-II

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HILCodec: High-Fidelity and Lightweight Neural Audio Codec

arXiv

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arXiv 2024年

作者： Ahn, Sunghwan Woo, Beom Jun Han, Min Hyun Moon, Chanyeong Kim, Nam Soo Department of Electrical and Computer Engineering The Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of

The recent advancement of end-to-end neural audio codecs enables compressing audio at very low bitrates while reconstructing the output audio with high fidelity. Nonetheless, such improvements often come at the cost of increased model complexity. In this paper, we identify and address the problems of existing neural audio codecs. We show that the performance of the SEANet-based codec does not increase consistently as the network depth increases. We analyze the root cause of such a phenomenon and suggest a variance-constrained design. Also, we reveal various distortions in previous waveform domain discriminators and propose a novel distortion-free discriminator. The resulting model, HILCodec, is a real-time streaming audio codec that demonstrates state-of-the-art quality across various bitrates and audio types. Copyright © 2024, The Authors. All rights reserved.

关键词： Discriminators

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