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Two-Dimensional Golay Complementary Array Sets with Arbitrary Lengths for Omnidirectional MIMO Transmission

IEEE Transactions on communications 2024年第2期72卷 1135-1145页

作者： Zhao, You-Qi Pai, Cheng-Yu Huang, Zhen-Ming Liu, Zilong Chen, Chao-Yu National Cheng Kung University Department of Engineering Science Tainan701 Taiwan National Cheng Kung University Department of Engineering Science and the Institute of Computer and Communication Engineering Tainan701 Taiwan University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom National Cheng Kung University Department of Electrical Engineering and the Institute of Computer and Communication Engineering Tainan701 Taiwan

This paper presents a coding approach for achieving omnidirectional transmission of certain common signals in massive multi-input multi-output (MIMO) networks such that the received power at any direction in a cell remains constant for any given distance. Specifically, two-dimensional (2D) Golay complementary array set (GCAS) can be used to design the massive MIMO precoding matrix so as to achieve omnidirectional transmission due to its complementary autocorrelation property. In this paper, novel constructions of new 2D GCASs with arbitrary array lengths are proposed. Our key idea is to carefully truncate the columns of certain larger arrays generated by 2D generalized Boolean functions. Finally, the power radiation patterns and numerical results are provided to verify the omnidirectional property of the GCAS-based precoding. The error performances of the proposed precoding scheme are presented to validate its superiority over the existing alternatives. © 1972-2012 IEEE.

关键词： Peak to average power ratio

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Enhanced Cross Z-Complementary Set and Its Application in Generalized Spatial Modulation

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the communications Society 2024年 5卷 4674-4690页

作者： Huang, Zhen-Ming Pai, Cheng-Yu Liu, Zilong Chen, Chao-Yu Institute of Computer and Communication Engineering National Cheng Kung University Tainan701 Taiwan National Cheng Kung University Department of Engineering Science Tainan701 Taiwan National Cheng Kung University Department of Electrical Engineering Tainan701 Taiwan University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

Generalized spatial modulation (GSM) is a novel multiple-antenna technique offering flexibility among spectral efficiency, energy efficiency, and the cost of RF chains. In this paper, a novel class of sequence sets, called enhanced cross Z-complementary set (E-CZCS), is proposed for efficient and feasible training sequence design in broadband GSM systems. Specifically, an E-CZCS consists of multiple CZCSs possessing front-end and tail-end zero-correlation zones (ZCZs), whereby any two distinct CZCSs have a tail-end ZCZ when a novel type of cross-channel aperiodic correlation sums is considered. The theoretical upper bound on the ZCZ width is first derived, upon which E-CZCSs with maximum ZCZ width and flexible parameters are constructed. For optimal channel estimation over frequency-selective channels, we introduce and evaluate a novel GSM training framework employing the proposed E-CZCSs. Numerical results demonstrate that the proposed E-CZCS-based training can achieve the minimum channel estimation mean square error (MSE) and outperform other classes of sequences. © 2020 IEEE.

关键词： Mean square error

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Cost-Effective Authenticated Solution (CAS) for 6G-Enabled Artificial Intelligence of Medical Things (AIoMT)

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IEEE Internet of Things Journal 2024年第13期11卷 23977-23984页

作者： Mahmood, Khalid Obaidat, Mohammad S. Shamshad, Salman Alenazi, Mohammed J. F. Kumar, Gulshan Anisi, Mohammad Hossein Conti, Mauro National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Jordan King Abdullah II School of Information Technology Amman11942 Jordan University of Science and Technology Beijing School of Communication and Computing Engineering Beijing100083 China Amity University Amity School of Engineering and Technology Noida201301 India University of Lahore Department of Software Engineering Lahore54590 Pakistan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh12311 Saudi Arabia University of Padua Department of Mathematics Padua35131 Italy Lovely Professional University Department of Computer Science and Engineering Phagwara144411 India University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

The Internet of Things (IoT) is a network of interconnected objects, which congregate and exchange gigantic amounts of data. Usually, predeployed embedded sensors sense this massive data. Soon, several applications of IoT are anticipated to exploit emerging 6G technology. Healthcare is one of them, where the 6G-inspired paradigm may facilitate the users to exchange information through hundreds of sensors under the assumption of Artificial Intelligence of Things (AIoT). Integration of medical sensors with AIoT is known as Artificial Intelligence of Medical Things (AIoMT). The secure and seamless interactions among 6G-enabled AIoMT users should be the primary challenge. Furthermore, resource-constrained wearable sensing devices, with their inability to execute complex security solutions, provide an ideal attraction for malicious entities to launch diverse attacks. These challenges have motivated us to design a cost-effective authenticated solution (CAS) for 6G-enabled AIoMT healthcare applications. Our CAS protocol not only prevents cyber threats like impersonation session key secrecy but it can also prevent physical threats like hardware tampering. We observe formal and informal security validations to endorse its robustness and effectiveness. Performance comparison reveals that the CAS protocol offers maximum security enrichment. Moreover, CAS is cost-effective as it has achieved 33% and 60% reduction in computation and communication overheads, respectively, compared to contemporary competing related protocols. © 2014 IEEE.

关键词： Authentication

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Hybrid Quantum Noise Approximation and Pattern Analysis on Parameterized Component Distributions

Hybrid Quantum Noise Approximation and Pattern Analysis on P...

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2024 IEEE Middle East Conference on communications and Networking, MECOM 2024

作者： Chakraborty, Mouli Mukherjee, Anshu Krikidis, Ioannis Nag, Avishek Chandra, Subhash The University of Dublin College Green School of Natural Sciences Trinity College Dublin Dublin 2 Ireland University College Dublin Belfield School of Electrical and Electronic Engineering Dublin 4 Ireland University of Cyprus IRIDA Research Centre for Communication Technologies Department of Electrical and Computer Engineering Nicosia Cyprus University College Dublin Belfield School of Computer Science Dublin 4 Ireland

ISBN: (纸本)9798350376715

Noise is a vital factor in determining the accuracy of processing the information of the quantum channel. One must consider classical noise effects associated with quantum noise sources for more realistic modelling of quantum channels. A hybrid quantum noise model incorporating both quantum Poisson noise and classical additive white Gaussian noise (AWGN) can be interpreted as an infinite mixture of Gaussians with weightage from the Poisson distribution. The entropy measure of this function is difficult to calculate. This research developed how the infinite mixture can be well approximated by a finite mixture distribution depending on the Poisson parametric setting compared to the number of mixture components. The mathematical analysis of the characterization of hybrid quantum noise has been demonstrated based on Gaussian and Poisson parametric analysis. This helps in the pattern analysis of the parametric values of the component distribution, and it also helps in the calculation of hybrid noise entropy to understand hybrid quantum noise better. © 2024 IEEE.

关键词： Quantum noise

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A Digital-Twin-Empowered Lightweight Model-Sharing Scheme for Multirobot Systems

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IEEE Internet of Things Journal 2023年第19期10卷 17231-17242页

作者： Xiong, Kai Wang, Zhihong Leng, Supeng He, Jianhua University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

Multirobot system for manufacturing is an Industry Internet of Things (IIoT) paradigm with significant operational cost savings and productivity improvement, where unmanned aerial vehicles (UAVs) are employed to control and implement collaborative productions without human intervention. This mission-critical system relies on 3-dimension (3-D) scene recognition to improve operation accuracy in the production line and autonomous piloting. However, implementing 3-D point cloud learning, such as Pointnet, is challenging due to limited sensing and computing resources equipped with UAVs. Therefore, we propose a digital twin (DT) empowered knowledge distillation (KD) method to generate several lightweight learning models and select the optimal model to deploy on UAVs. With a digital replica of the UAVs preserved at the edge server, the DT system controls the model-sharing network topology and learning model structure to improve recognition accuracy further. Moreover, we employ network calculus to formulate and solve the model sharing configuration problem toward minimal resource consumption, as well as convergence. Simulation experiments are conducted over a popular point cloud data set to evaluate the proposed scheme. Experiment results show that the proposed model-sharing scheme outperforms the individual model in terms of computing resource consumption and recognition accuracy. © 2014 IEEE.

关键词： Multipurpose robots

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A Generalized Noise Reconstruction Approach for Robust DOA Estimation

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2023年 1卷 382-394页

作者： Cong, Jingyu Wang, Xianpeng Lan, Xiang Liu, Wei State Key Laboratory of Marine Resource Utilization in South China Sea the School of Information and Communication Engineering Hainan University Haikou570228 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom

A generalized noise reconstruction approach is proposed for improved direction-of-arrival (DOA) estimation. First, coarse estimation of the noise component in the received data is obtained based on cumulative sum of an approximate first-order finite difference series, where the generalized pattern search (GPS) algorithm is used to find the best initial value. The objective function is constructed with the total noise power estimated by the least squares (LS) method. After that, a new cumulative sum constructed with the solution from the previous step is used to accurately reconstruct the noise component in the data. Finally, robust DOA estimation is achieved through the denoised data. In simulations, different cases of noise, such as non-uniform noise, colored noise, impulsive noise, and K-distribution sea clutter, are considered. TI frequency-modulated continuous wave (FMCW) multiple-input multiple-output (MIMO) radar data is also used to demonstrate the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Direction of arrival

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RHC-Based Systematic Design of a Wide-Angle Periodic Coded THz Reflectarray 11

RHC-Based Systematic Design of a Wide-Angle Periodic Coded T...

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11th International Symposium on Telecommunication, IST 2024

作者： Yousefi, Pezhman Khajeh, Ali Yahaghi, Alireza Hosseini, Keyhan Polytechnic University of Bari Department of Electrical and Information Engineering Via Orabona 4 Bari70125 Italy Shiraz University School of Electrical and Computer Engineering Shiraz71946 Iran University of Kurdistan Faculty of Engineering Department of Electronics and Communication Engineering Kurdistan Sanandaj66177 Iran

ISBN: (纸本)9798350356250

A reflectarray designed by Random Hill Climbing (RHC) optimization process is demonstrated and simulated. On the basis of top layer effect on reflection phase and exploiting the relation between phase distribution and the direction of the reflected beam, six pixelated subcells are optimized for two incident angle waves simultaneously. The far field plot shows that for beams of incident angles 19.471° and 41.81° and in the precincts of them the reflectarray deflects the incident waves into reflections close to normal to the reflectarray surface. This shows a proximate independency of incident wave angle for the reflectarray in a certain angular range. The proposed cells provide 342° reflection phase range. Also, the reflection loss of the cell for the incident angles 19.471° and 41.81° are -1.9 dB and -1.4 dB, respectively. The pattern gain and fractional bandwidth for a finite reflectarray of size 300 λ x 150 λ are reported to be 19.44 dB and 25% for the incident angle 19.471°, and 19.17 dB and 30% for the incident angle 41.81°. © 2024 IEEE.

关键词： Reflection

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Maximizing Energy Efficiency in IRS-Assisted Phase Cooperative PS-SWIPT-Based Self-Sustainable IoT Network

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the communications Society 2025年 6卷 4311-4327页

作者： Sadia, Haleema Kamal Hassan, Ahmad Haq Abbas, Ziaul Abbas, Ghulam Baker, Thar Saeed, Nasir United Arab Emirates University College of Engineering Department of Electrical and Communication Engineering Al Ain United Arab Emirates Ghulam Ishaq Khan Institute of Engineering and Technology Faculty of Electrical Engineering Topi23460 Pakistan Ghulam Ishaq Khan Institute of Engineering and Technology Faculty of Computer Science and Engineering Topi23460 Pakistan University of Brighton School of Architecture Technology and Engineering BrightonBN2 4GJ United Kingdom

Power splitting based simultaneous wireless information and power transfer (PS-SWIPT) appears to be a promising solution to support future self-sustainable Internet of Things (SS-IoT) networks. However, the performance of these networks is constrained by radio frequency signal strength and channel impairments. To overcome this challenge, intelligent reflecting surfaces (IRSs) have recently been introduced in IoT networks to improve network efficiency by controlling signal reflections. In this article, we propose a novel IRS-enabled phase cooperative framework that aims to maximize the energy efficiency (EE) of the PS-SWIPT based SS-IoT network. Our framework leverages the idea of phase cooperation between two distinct networks without requiring additional hardware resources. We employed transmit beamforming (BF) at access points (APs) and phase shift optimization at the IRS with effective phase cooperation between APs. The EE maximization problem turns out to be NP-hard, so first, an alternating optimization (AO) is solved for the user’s network using heuristic BF approaches and phase optimization via semidefinite relaxation (SDR) approaches. To combat the computational complexity of AO, we also propose a low-complexity alternative solution by exploiting heuristic BF schemes and an iterative algorithm, i.e., the element-wise block-coordinate descent method for phase shifts optimization. The proposed solutions’ analysis shows low computational complexity and fast convergence, achieving near-optimal EE performance for different network settings. We conducted extensive simulations to evaluate our proposed framework’s performance and unveiled significant EE performance achieved by the IoT network consistent with the numerical findings. This work demonstrates the potential of IRS phase cooperation for enhancing the EE of different networks without constraining hardware resources. © 2020 IEEE.

关键词： Energy transfer

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Cyber Attacks Detection using Deep Learning Methods for Resilient Operation in DC Shipboard Microgrids

Cyber Attacks Detection using Deep Learning Methods for Resi...

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2024 IEEE IAS Industrial and Commercial Power System Asia, I and CPS Asia 2024

作者： Ali, Zulfiqar Hussain, Tahir Su, Chun-Lien Jurcut, Anca Delia Baloch, Shazia Sadiq, Muhammad National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung city Taiwan Graduate School of Informatics and Engineering The University of Electro-Communication Department of Informatics Tokyo Japan School of Computer Science University College Dublin BelfieldDublin 4 Ireland Balochistan University of Engineering and Technology Department of Electrical Engineering Khuzdar Pakistan

ISBN: (纸本)9798350352290

Cyber resilience has become paramount as a transition of maritime systems towards digitization, particularly within DC shipboard microgrids (SMGs). Adopting innovative communication technologies can enhance the resilience of SMGs for stable operation. However, challenges like false data injection and Man-in-The-Middle attacks pose significant threats to SMG operations when integrating these technologies into ship intelligent grids. In this regard, this paper proposes a reliable deep learning (DL) method, especially an Artificial neural network (ANN) with a deep encoder-decoder architecture, for the detection of cyber-intrusions and mitigating their effects, ensuring system control and stability for resilient operation of SMG. Detecting malicious data intrusions is crucial for maintaining optimal grid conditions and preventing disruptions in load dispatch. The proposed method utilizes a fusion of current and voltage data features for comprehensive DL model training, resulting in an adequate level of detection accuracy and providing cybersecurity analysis for SMGs, addressing component-level attacks, and devising defense strategies from aspects of detection, mitigation, and prevention. Furthermore, the deep ANN is fine-tuned with optimal hyperparameters to effectively counter cyberattacks, achieving an enhanced accuracy rate of 97.51% and minimal loss of 0.101%, surpassing conventional machine learning approaches. Rigorous test scenarios are performed to validate the robustness of the proposed method, emphasizing the cyber resilience of DC SMGs for enhanced security and operational integrity. © 2024 IEEE.

关键词： Network intrusion

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D-STAR: Dual Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces for Joint Uplink/Downlink Transmission

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IEEE Transactions on communications 2024年第6期72卷 3305-3322页

作者： Shen, Li-Hsiang Wu, Po-Chen Ku, Chia-Jou Li, Yu-Ting Feng, Kai-Ten Liu, Yuanwei Hanzo, Lajos National Central University Department of Communication Engineering Taoyuan320317 Taiwan Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom University of Southampton Next Generation Wireless Research Group SouthamptonSO17 1BJ United Kingdom

The joint uplink/downlink (JUD) design of simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) is conceived in support of both uplink (UL) and downlink (DL) users. Furthermore, the dual STAR-RISs (D-STAR) concept is conceived as a promising architecture for 360-degree full-plane service coverage, including UL/DL users located between the base station (BS) and the D-STAR as well as beyond. The corresponding regions are termed as primary (P) and secondary (S) regions. Both BS/users exist in the P-region, but only users are located in the S-region. The primary STAR-RIS (STAR-P) plays an important role in terms of tackling the P-region inter-user interference, the self-interference (SI) from the BS and from the reflective as well as refractive UL users imposed on the DL receiver. By contrast, the secondary STAR-RIS (STAR-S) aims for mitigating the S-region interferences. The non-linear and non-convex rate-maximization problem formulated is solved by alternating optimization amongst the decomposed convex sub-problems of the BS beamformer, and the D-STAR amplitude as well as phase shift configurations. We also propose a D-STAR based active beamforming and passive STAR-RIS amplitude/phase (DBAP) optimization scheme to solve the respective sub-problems by Lagrange dual with Dinkelbach's transformation, alternating direction method of multipliers (ADMM) with successive convex approximation (SCA), and penalty convex-concave procedure (PCCP). Our simulation results reveal that the proposed D-STAR architecture outperforms the conventional single RIS, single STAR-RIS, and half-duplex networks. The proposed DBAP of D-STAR outperforms the state-of-the-art solutions found in the open literature for different numbers of quantization levels, geographic deployment, transmit power and for diverse numbers of transmit antennas, patch partitions as well as D-STAR elements. © 1972-2012 IEEE.

关键词： Beamforming

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