Publications

Gill, A 2024, 'Adaptive Information Architecture for Sustainable Digital Ecosystem' in Sustainability Handbook.

Ansari, M, Zetterstrom, O, Fonseca, NJG, Quevedo-Teruel, O & Guo, YJ 2024, 'A Lightweight Spherical Generalized Luneburg Lens Antenna With Low Cross-Polarization Over a Wide Range in Azimuth and Elevation', IEEE Open Journal of Antennas and Propagation, vol. 5, no. 1, pp. 58-66.
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Babakian, A, Huston, G, Braun, R & Lipman, J 2024, 'Internet Identifiers: A Survey of History, Challenges, and Future Perspectives', IEEE Access, vol. 12, pp. 51919-51941.
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Beydoun, G, Low, G, Gill, A, Moniruzzaman, M & Shen, J 2024, 'Tailoring ontology retrieval for supporting requirements analysis', Advanced Engineering Informatics, vol. 59, pp. 102231-102231.
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It is well accepted that domain ontologies can support requirement analysis activities, particularly in detecting inconsistencies and incompleteness of requirement models. These benefits critically depend on the provision of a suitable ontology. We observe the context of supporting requirement analysis provides both opportunities and restrictions when choosing the most appropriate ontology retrieval mechanisms. Requirement models are the basis for retrieving the most influential ontologies and are not the typical retrieval domain ontologies. For instance, a retrieval ontology derived from the requirement is not expected only to be a hierarchical taxonomy, nor is it limited to the boundaries of a single domain, nor does it cover any particular domain completely. Hence, retrieval methods cannot be based on classes only and computational constraints do not necessarily apply as the retrieval process is expected to run only once at the outset of the analysis phase. It is also important to assume that the retrieval in this context is targeting multiple ontologies describing multiple but related domains. In this paper, we deduce that avoiding structural based retrieval mechanisms in fact benefits to the requirement models. Instead, we formulate a new retrieval method based on the PageRank algorithm that takes into account the indirect influences of various concepts within plausible supporting ontologies. This paper provides an empirical analysis that evidences the strength of our retrieval algorithm in supporting the identification of ontologies to support requirement analysis.

Chen, J, Zhu, K, Wu, K, Niu, J & Zhang, JA 2024, 'Introducing User Grouping to Counteract Channel Correlation in IRS-Assisted ISAC', IEEE Communications Letters, vol. 28, no. 4, pp. 808-812.
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Chen, L, Liu, Y, Ban, Y-L, Yang, S & Jay Guo, Y 2024, 'Synthesis of Large-Scale Planar Isophoric Sparse Arrays Utilizing Iterative Least Squares With Non-Redundant Constraints (ILS-NRC)', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Chen, X, Feng, Z, Zhang, JA, Wei, Z, Yuan, X, Zhang, P & Peng, J 2024, 'Downlink and Uplink Cooperative Joint Communication and Sensing', IEEE Transactions on Vehicular Technology, pp. 1-15.
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Chen, Y, Li, G, An, P, Liu, Z, Huang, X & Wu, Q 2024, 'Light Field Salient Object Detection With Sparse Views via Complementary and Discriminative Interaction Network', IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 2, pp. 1070-1085.
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Chu, NH, Hoang, DT, Nguyen, DN, Phan, KT, Dutkiewicz, E, Niyato, D & Shu, T 2024, 'MetaSlicing: A Novel Resource Allocation Framework for Metaverse', IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 4145-4162.
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Creating and maintaining the Metaverse requires enormous resources that have never been seen before, especially computing resources for intensive data processing to support the Extended Reality, enormous storage resources, and massive networking resources for maintaining ultra high-speed and low-latency connections. Therefore, this work aims to propose a novel framework, namely MetaSlicing, that can provide a highly effective and comprehensive solution in managing and allocating different types of resources for Metaverse applications. In particular, by observing that Metaverse applications may have common functions, we first propose grouping applications into clusters, called MetaInstances. In a MetaInstance, common functions can be shared among applications. As such, the same resources can be used by multiple applications simultaneously, thereby enhancing resource utilization dramatically. To address the real-time characteristic and resource demand's dynamic and uncertainty in the Metaverse, we develop an effective framework based on the semi-Markov decision process and propose an intelligent admission control algorithm that can maximize resource utilization and enhance the Quality-of-Service for end-users. Extensive simulation results show that our proposed solution outperforms the Greedy-based policies by up to 80% and 47% in terms of long-term revenue for Metaverse providers and request acceptance probability, respectively.

Dhull, P, Schreurs, D, Paolini, G, Costanzo, A, Abolhasan, M & Shariati, N 2024, 'Multitone PSK Modulation Design for Simultaneous Wireless Information and Power Transfer', IEEE Transactions on Microwave Theory and Techniques, vol. 72, no. 1, pp. 446-460.
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Dinh, PV, Nguyen, QU, Hoang, DT, Nguyen, DN, Bao, SP & Dutkiewicz, E 2024, 'Constrained Twin Variational Auto-Encoder for Intrusion Detection in IoT Systems', IEEE Internet of Things Journal, vol. 11, no. 8, pp. 14789-14803.
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Du, A, Zhou, T, Pang, S, Wu, Q & Zhang, J 2024, 'PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation', IEEE Transactions on Multimedia, pp. 1-12.
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Geng, C, Lian, J-W, Guo, YJ & Ding, D 2024, 'Millimeter-Wave Three-Layer Substrate-Integrated 9 × 9 Butler Matrix and Its Application to Wide-Angle Endfire Multibeam Metasurface Antenna', IEEE Transactions on Microwave Theory and Techniques, vol. 72, no. 4, pp. 2253-2266.
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Gu, Z, He, X, Yu, P, Jia, W, Yang, X, Peng, G, Hu, P, Chen, S, Chen, H & Lin, Y 2024, 'Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model', Artificial Intelligence in Medicine, vol. 150, pp. 102822-102822.
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Guo, CA, Guo, YJ & Yuan, J 2024, 'Multibeam Receiving Antennas Employing Generalized Joined Coupler Matrix', IEEE Transactions on Antennas and Propagation, vol. 72, no. 1, pp. 424-432.
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Owing to the characteristics of directional couplers, series fed multibeam receiving antenna arrays require different treatment from their transmitting counterparts. In this paper, the theory and strategies for the feed network synthesis of multibeam receiving antennas employing the generalized joined coupler matrix (GJC) are presented. Given M incident waves in any set of directions, we first derive the output signal matrix as a function of the incident signal matrix. This serves as an important tool for both synthesizing and analysing GJC receiving matrices. Then, we present three different synthesis strategies and show how they are related to the array patterns. We also reveal how the receiving power efficiency of the GJC matrix changes with the antenna beam pattern. We further demonstrate that, despite the employment of matched loads, high receiving power efficiencies can be achieved using the GJC matrix.

He, K, Vu, TX, Hoang, DT, Nguyen, DN, Chatzinotas, S & Ottersten, B 2024, 'Risk-Aware Antenna Selection for Multiuser Massive MIMO under Incomplete CSI', IEEE Transactions on Wireless Communications, pp. 1-1.
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He, Y, Ding, C, Chang, C, Wei, G & Guo, YJ 2024, 'A Bowl-Shaped Filtering Antenna with Wideband Cross-Band Scattering Mitigation for Dual-Band Base Stations', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Hu, X, Liu, T, Shu, T & Nguyen, D 2024, 'Spoofing Detection for LiDAR in Autonomous Vehicles: A Physical-Layer Approach', IEEE Internet of Things Journal, pp. 1-1.
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Hu, Y, Deng, W, Zhang, JA & Guo, YJ 2024, 'Resource Optimization for Delay Estimation in Perceptive Mobile Networks', IEEE Wireless Communications Letters, vol. 13, no. 1, pp. 223-227.
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HU, Y, LI, H, ZHANG, JA, HUANG, X & CHENG, Z 2024, 'Optimal Design of Wideband mmWave LoS MIMO Systems Using Hybrid Arrays with Beam Squint', IEICE Transactions on Communications, vol. E107.B, no. 1, pp. 244-252.
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Huang, J, Gong, Y, Shi, Y, Zhang, X, Zhang, J & Yin, Y 2024, 'Focusing on Subtle Differences: A Feature Disentanglement Model for Series Photo Selection', IEEE Transactions on Multimedia, pp. 1-14.
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Huang, J, Gong, Y, Zhang, L, Zhang, J, Nie, L & Yin, Y 2024, 'Modeling Multiple Aesthetic Views for Series Photo Selection', IEEE Transactions on Multimedia, vol. 26, pp. 1983-1995.
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Huang, S, Zheng, J, Qin, P, Zhan, Q & Chen, X 2024, 'Improved planar near-field measurement based on data assimilation', Measurement, vol. 227, pp. 114265-114265.
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Huang, Y, Huang, Y, Zhang, Z, Wu, Q, Zhong, Y & Wang, L 2024, 'Enhancing Person Re-Identification Performance Through In Vivo Learning', IEEE Transactions on Image Processing, vol. 33, pp. 639-654.
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Huang, Y, Wu, Q, Zhang, Z, Shan, C, Huang, Y, Zhong, Y & Wang, L 2024, 'Meta Clothing Status Calibration for Long-Term Person Re-Identification', IEEE Transactions on Image Processing, vol. 33, pp. 2334-2346.
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Huang, Y, Zhang, Z, Huang, Y, Wu, Q, Huang, H, Zhong, Y & Wang, L 2024, 'Customized meta-dataset for automatic classifier accuracy evaluation', Pattern Recognition, vol. 146, pp. 110026-110026.
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Huynh, NV, Wang, J, Du, H, Hoang, DT, Niyato, D, Nguyen, DN, Kim, DI & Letaief, KB 2024, 'Generative AI for Physical Layer Communications: A Survey', IEEE Transactions on Cognitive Communications and Networking, pp. 1-1.
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Keshavarz, R, Majidi, E, Raza, A & Shariati, N 2024, 'Ultra-Fast and Efficient Design Method Using Deep Learning for Capacitive Coupling WPT System', IEEE Transactions on Power Electronics, vol. 39, no. 1, pp. 1738-1748.
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Keshavarz, R, Nikkhah, N & Shariati, N 2024, 'In Situ Wide-Range Permittivity Measurement: Compact, Cost-Effective, and Highly Sensitive Sensor Using Reconfigurable Phase Shifter', IEEE Transactions on Circuits and Systems I: Regular Papers, pp. 1-10.
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Keshavarz, R, Sounas, DL, Keshavarz, S & Shariati, N 2024, 'Enabling Wireless Communications, Energy Harvesting, and Energy Saving by Using a Multimode Smart Nonlinear Circuit (MSNC)', IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-11.
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Khoa, TV, Son, DH, Hoang, DT, Trung, NL, Quynh, TTT, Nguyen, DN, Ha, NV & Dutkiewicz, E 2024, 'Collaborative Learning for Cyberattack Detection in Blockchain Networks', IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1-14.
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Le, AT, Huang, X, Ding, C, Zhang, H & Guo, YJ 2024, 'An In-Band Full-Duplex Prototype With Joint Self-Interference Cancellation in Antenna, Analog, and Digital Domains', IEEE Transactions on Microwave Theory and Techniques, pp. 1-10.
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Le, M, Hoang, DT, Nguyen, DN, Hwang, W-J & Pham, Q-V 2024, 'Wirelessly Powered Federated Learning Networks: Joint Power Transfer, Data Sensing, Model Training, and Resource Allocation', IEEE Internet of Things Journal, pp. 1-1.
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Liu, B, Ni, W, Liu, RP, Guo, YJ & Zhu, H 2024, 'Optimal Electric Vehicle Charging Strategies for Long-Distance Driving', IEEE Transactions on Vehicular Technology, vol. 73, no. 4, pp. 4949-4960.
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Electric vehicles (EVs) provide sustainable and eco-friendly transportation. However, long-range driving is challenging due to limited battery capacity. While charging stations can replenish the battery, they are not as widely deployed as gas stations, causing the battery depletion of EVs. This paper presents a novel optimal charging strategy for EV long-range driving. The strategy offers EV drivers the optimal charging instructions for a given trip. A new finite-horizon Markov decision process (FH-MDP) problem is formulated to minimize the travel time of an EV while preventing its battery depletion, by optimally selecting the charging stations and charging times along the trip. By confirming the monotonicity and subadditivity of the FH-MDP, we prove the existence of a monotone deterministic Markovian policy for the optimal charging decision and reveal the optimal charging time is monotone regarding the remaining battery level and driven distance. We also reveal that the optimal charging time only changes when either of two thresholds regarding the remaining battery level or driving distance is met. By comparing its state with the thresholds, the EV can make optimal decisions with linear complexity. Simulations corroborate that our algorithm can save travel time by at least 12.6% under our simulation settings, compared to alternative methods.

Liu, J, Wu, K, Su, T & Zhang, JA 2024, 'Practical frequency-hopping MIMO joint radar communications: design and experiment', Digital Communications and Networks.
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Nguyen, C-H, Saputra, YM, Hoang, DT, Nguyen, DN, Nguyen, V-D, Xiao, Y & Dutkiewicz, E 2024, 'Encrypted Data Caching and Learning Framework for Robust Federated Learning-Based Mobile Edge Computing', IEEE/ACM Transactions on Networking, pp. 1-16.
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Nguyen, CT, Hoang, DT, Nguyen, DN, Xiao, Y, Niyato, D & Dutkiewicz, E 2024, 'MetaShard: A Novel Sharding Blockchain Platform for Metaverse Applications', IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 4348-4361.
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Due to its security, transparency, and flexibility in verifying virtual assets, blockchain has been identified as one of the key technologies for Metaverse. Unfortunately, blockchain-based Metaverse faces serious challenges such as massive resource demands, scalability, and security/privacy concerns. To address these issues, this paper proposes a novel sharding-based blockchain framework, namely MetaShard, for Metaverse applications. Particularly, we first develop an effective consensus mechanism, namely Proof-of-Engagement, that can incentivize MUs' data and computing resource contribution. Moreover, to improve the scalability of MetaShard, we propose an innovative sharding management scheme to maximize the network's throughput while protecting the shards from 51% attacks. Since the optimization problem is NP-complete, we develop a hybrid approach that decomposes the problem (using the binary search method) into sub-problems that can be solved effectively by the Lagrangian method. As a result, the proposed approach can obtain solutions in polynomial time, thereby enabling flexible shard reconfiguration and reducing the risk of corruption from the adversary. Extensive numerical experiments show that, compared to the state-of-the-art commercial solvers, our proposed approach can achieve up to 66.6% higher throughput in less than 1/30 running time. Moreover, the proposed approach can achieve global optimal solutions in most experiments.

Nguyen, V-D, Vu, TX, Nguyen, NT, Nguyen, DC, Juntti, M, Luong, NC, Hoang, DT, Nguyen, DN & Chatzinotas, S 2024, 'Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework', IEEE Journal on Selected Areas in Communications, vol. 42, no. 2, pp. 389-405.
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Nikkhah, N, Keshavarz, R, Abolhasan, M, Lipman, J & Shariati, N 2024, 'Highly Sensitive Differential Microwave Sensor Using Enhanced Spiral Resonators for Precision Permittivity Measurement', IEEE Sensors Journal, pp. 1-1.
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Piyathilaka, L, Kodagoda, S, Thiyagarajan, K, Piccardi, M, Preethichandra, DMG & Izhar, U 2024, 'Learning Spatial Affordances From 3D Point Clouds for Mapping Unseen Human Actions in Indoor Environments', IEEE Access, vol. 12, pp. 868-877.
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Raza, A, Keshavarz, R & Shariati, N 2024, 'Precision Agriculture: Ultra-Compact Sensor and Reconfigurable Antenna for Joint Sensing and Communication', IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-13.
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Raza, MA, Abolhasan, M, Lipman, J, Shariati, N, Ni, W & Jamalipour, A 2024, 'Multi-Agent Multi-Armed Bandit Learning for Grant-Free Access in Ultra-Dense IoT Networks', IEEE Transactions on Cognitive Communications and Networking, pp. 1-1.
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Ren, Y, Zhang, H, Cao, X, Yang, C, Zhang, J & Li, H 2024, 'Promoting or Hindering: Stealthy Black-Box Attacks Against DRL-Based Traffic Signal Control', IEEE Internet of Things Journal, vol. 11, no. 4, pp. 5816-5825.
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Song, L, Zhang, T, Qin, P-Y, Du, J & Guo, YJ 2024, 'Sub-THz Broadband Transmitting Metasurfaces With Enhanced Frequency-Scanning Capability', IEEE Transactions on Terahertz Science and Technology, vol. 14, no. 1, pp. 82-90.
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In this manuscript, broadband transmitting metasurfaces are developed to enhance frequency-dependent beam scanning. A triple-gold-layer unit cell is designed for wideband transmissions with low losses and quasi-linear phase variations. Comprehensive analyses of phase-gradient metasurfaces are provided to enable high-efficiency and wide-angle frequency scanning. For verifications, two metasurfaces with different phase gradients are simulated, manufactured, and measured. Continuous beam scanning performance has been demonstrated successfully from 80 GHz to 220 GHz, showing beam scanning ranges of 25° and 31.5° from two prototypes, respectively. Peak transmission efficiencies of 84% and 75% have been obtained from experiments. The results from simulation and measurement agree very well. The developed metasurfaces have many potential applications such as frequency-scanning terahertz (THz) imaging.

Sun, J, Liu, Y, Luo, Q, Ren, Y & Guo, YJ 2024, 'Efficient and Accurate Pattern Synthesis of Circular Antenna Array Employing Iterative Fast Segmented Cyclic Convolution', IEEE Antennas and Wireless Propagation Letters, vol. 23, no. 1, pp. 269-273.
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Tuan, HD, Nasir, AA, Dutkiewicz, E, Poor, HV & Hanzo, L 2024, 'RIS-Aided Multiple-Input Multiple-Output Broadcast Channel Capacity', IEEE Transactions on Communications, vol. 72, no. 1, pp. 117-132.
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Wang, X, Fei, Z, Liu, P, Zhang, JA, Wu, Q & Wu, N 2024, 'Sensing Aided Covert Communications: Turning Interference into Allies', IEEE Transactions on Wireless Communications, pp. 1-1.
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Wang, Y, Wang, Z, Zhang, JA, Zhang, H & Xu, M 2024, 'Vital Sign Monitoring in Dynamic Environment via mmWave Radar and Camera Fusion', IEEE Transactions on Mobile Computing, vol. 23, no. 5, pp. 4163-4180.
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Wei, G, Wang, Y, He, Y, Ziolkowski, RW & Guo, YJ 2024, 'Ultra-Wideband Vertically-Polarized Long-Slot Circular Phased Array', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Wei, Z, Piao, J, Yuan, X, Wu, H, Zhang, JA, Feng, Z, Wang, L & Zhang, P 2024, 'Waveform Design for MIMO-OFDM Integrated Sensing and Communication System: An Information Theoretical Approach', IEEE Transactions on Communications, vol. 72, no. 1, pp. 496-509.
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Weththasinghe, K, Jayawickrama, B & He, Y 2024, 'Machine Learning-Based Channel Estimation for 5G New Radio', IEEE Wireless Communications Letters, vol. 13, no. 4, pp. 1133-1137.
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Wu, K, Zhang, JA, Ni, Z, Huang, X, Guo, YJ & Chen, S 2024, 'Joint Communications and Sensing Employing Optimized MIMO-OFDM Signals', IEEE Internet of Things Journal, vol. 11, no. 6, pp. 10368-10383.
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Xi, Y, Jia, W, Miao, Q, Feng, J, Ren, J & Luo, H 2024, 'Detection-Driven Exposure-Correction Network for Nighttime Drone-View Object Detection', IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-14.
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Xu, Y, Li, Y, Zhang, JA, Renzo, MD & Quek, TQS 2024, 'Joint Beamforming for RIS-Assisted Integrated Sensing and Communication Systems', IEEE Transactions on Communications, vol. 72, no. 4, pp. 2232-2246.
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Xu, Y, Zhu, H & Guo, YJ 2024, 'Compact Multi-Beamforming Networks Based on Generalized Joined Coupler Matrix With Flexible Beam Angles and Low Sidelobe Levels', IEEE Open Journal of Antennas and Propagation, pp. 1-1.
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Xu, Y, Zhu, H & Guo, YJ 2024, 'Compact Wideband 3 × 3 Nolen Matrix With Couplers Integrated With Phase Shifters', IEEE Microwave and Wireless Technology Letters, vol. 34, no. 2, pp. 159-162.
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Yang, X, Li, H, Guo, Q, Zhang, JA, Huang, X & Cheng, Z 2024, 'Sensing Aided Uplink Transmission in OTFS ISAC With Joint Parameter Association, Channel Estimation and Signal Detection', IEEE Transactions on Vehicular Technology, pp. 1-6.
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Yu, G, Wang, X, Sun, C, Wang, Q, Yu, P, Ni, W & Liu, RP 2024, 'IronForge: An Open, Secure, Fair, Decentralized Federated Learning', IEEE Transactions on Neural Networks and Learning Systems, vol. PP, pp. 1-15.
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Federated learning (FL) offers an effective learning architecture to protect data privacy in a distributed manner. However, the inevitable network asynchrony, overdependence on a central coordinator, and lack of an open and fair incentive mechanism collectively hinder FL's further development. We propose IronForge, a new generation of FL framework, that features a directed acyclic graph (DAG)-based structure, where nodes represent uploaded models, and referencing relationships between models form the DAG that guides the aggregation process. This design eliminates the need for central coordinators to achieve fully decentralized operations. IronForge runs in a public and open network and launches a fair incentive mechanism by enabling state consistency in the DAG. Hence, the system fits in networks where training resources are unevenly distributed. In addition, dedicated defense strategies against prevalent FL attacks on incentive fairness and data privacy are presented to ensure the security of IronForge. Experimental results based on a newly developed test bed FLSim highlight the superiority of IronForge to the existing prevalent FL frameworks under various specifications in performance, fairness, and security. To the best of our knowledge, IronForge is the first secure and fully decentralized FL (DFL) framework that can be applied in open networks with realistic network and training settings.

Yu, H, Tuan, HD, Nasir, AA, Dutkiewicz, E & Hanzo, L 2024, 'Rate-Fairness-Aware Low Resolution RIS-Aided Multi-User OFDM Beamforming', IEEE Transactions on Vehicular Technology, vol. 73, no. 2, pp. 2401-2415.
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Zhang, H, Huang, X & Zhang, JA 2024, 'Low-Overhead OTFS Transmission With Frequency or Time Domain Channel Estimation', IEEE Transactions on Vehicular Technology, vol. 73, no. 1, pp. 799-811.
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Zhang, H, Xia, J, Zhang, G & Xu, M 2024, 'Learning Graph Representations Through Learning and Propagating Edge Features', IEEE Transactions on Neural Networks and Learning Systems, pp. 1-12.
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Zhang, H, Xu, M, Zhang, G & Niwa, K 2024, 'SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolutional Networks', IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 2223-2234.
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Zhang, T, Zhang, S & Jia, W 2024, 'Person Reidentification Based on Adaptive Relation Attention Network in Intelligent Monitoring System for the IoB', IEEE Transactions on Engineering Management, pp. 1-10.
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Zhang, X, Wang, X, So, HC, Zoubir, AM, Zhang, JA & Guo, YJ 2024, 'Transmit Waveform Design for Integrated Wideband MIMO Radar and Bi-Directional Communications', IEEE Transactions on Vehicular Technology, pp. 1-16.
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Zhang, Y, Liu, Y, Hu, R, Wu, Q & Zhang, J 2024, 'Mutual Dual-Task Generator With Adaptive Attention Fusion for Image Inpainting', IEEE Transactions on Multimedia, vol. 26, pp. 1539-1550.
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Zhao, L, Zhu, H, Ding, C, Liu, G, Zhao, H, Mou, J & Guo, YJ 2024, 'An Ultrawideband Dual-Polarized Tightly Coupled Dipole Array (TCDA) With Wide Scanning Range', IEEE Antennas and Wireless Propagation Letters, pp. 1-5.
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Zhou, C, Lyu, B, You, C & Hoang, DT 2024, 'Cooperative Commensal and Parasitic Symbiotic Radio Communication Systems', IEEE Wireless Communications Letters, vol. 13, no. 3, pp. 676-680.
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Zhou, I, Tofigh, F, Piccardi, M, Abolhasan, M, Franklin, D & Lipman, J 2024, 'Secure Multi-Party Computation for Machine Learning: A Survey', IEEE Access, pp. 1-1.
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Zhu, H, Wang, G, Wang, K, Liu, G, Zhou, Y, Xie, S, Di, Y, Xu, J, Zhou, H, Mou, J & Ding, C 2024, 'Grid composite meta-surface absorber with thermal isolation structure for terahertz detection', Optics Express, vol. 32, no. 1, pp. 205-205.
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This paper specifically focuses on the absorber, the critical component responsible for the detector's response performance. The meta-surface absorber combines two resonant structures and achieves over 80% absorptance around 210 GHz, resulting in a broad operating frequency range. FR-4 is selected as the dielectric layer to be compatible with standard printed circuit board (PCB) technology, which reduces the overall fabrication time and cost. The absorbing unit and array layout are symmetrically designed, providing stable absorptance performance even under incident waves of different polarization angles. The polarization-insensitive absorptance characteristic further enhances the compatibility between the absorber and the detector in the application scenario. Furthermore, the thermal insulation performance of the absorber is ensured by introducing thermal insulation gaps. After completing fabrication through PCB technology, testing revealed that the absorber maintained excellent absorptance performance within its primary operating frequency range. This performance consistency closely matched the simulation results.

Zhu, HY, Hieu, NQ, Hoang, DT, Nguyen, DN & Lin, C-T 2024, 'A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey', IEEE Communications Surveys & Tutorials, pp. 1-1.
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Zhu, W, Tuan, HD, Dutkiewicz, E, Poor, HV & Hanzo, L 2024, 'A New Class of Analog Precoding for Multi-Antenna Multi-User Communications over High-Frequency Bands', IEEE Transactions on Wireless Communications, pp. 1-1.
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A network relying on a large antenna-array-aided base station is designed for delivering multiple information streams to multi-antenna users over high-frequency bands such as the millimeter-wave and sub-Terahertz bands. The state-of-the-art analog precoder (AP) dissipates excessive circuit power due to its reliance on a large number of phase shifters. To mitigate the power consumption, we propose a novel AP relying on a controlled number of phase shifters. Within this new AP framework, we design a hybrid precoder (HP) for maximizing the users’ minimum throughput, which poses a computationally challenging problem of large-scale, nonsmooth mixed discrete-continuous log-determinant optimization. To tackle this challenge, we develop an algorithm which iterates through solving convex problems to generate a sequence of HPs that converges to the max-min solution. We also introduce a new framework of smooth optimization termed soft max-min throughput optimization. Additionally, we develop another algorithm, which iterates by evaluating closed-form expressions to generate a sequence of HPs that converges to the soft max-min solution. Simulation results reveal that the HP soft max-min solution approaches the Pareto-optimal solution constructed for simultaneously optimizing both the minimum throughput and sum-throughput. Explicitly, it achieves a minimum throughput similar to directly maximizing the users’ minimum throughput and it also attains a sum-throughput similar to directly maximizing the sum-throughput.

Zhu, W, Tuan, HD, Dutkiewicz, E, Poor, HV & Hanzo, L 2024, 'Max-min Rate Optimization of Low-Complexity Hybrid Multi-User Beamforming Maintaining Rate-Fairness', IEEE Transactions on Wireless Communications, pp. 1-1.
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Gill, A 1970, 'Adaptive Information Architecture: Information Element Identification and Organisation Patterns for Digital Ecosystem', The 20th International Conference on Information and Knowledge Engineering, Springer, Las Vegas.

Dinh, PV, Nguyen, DN, Hoang, DT, Nguyen, QU, Dutkiewicz, E & Bao, SP 2024, 'Multiple-Input Auto-Encoder Guided Feature Selection for IoT Intrusion Detection Systems'.

Dinh, PV, Nguyen, QU, Dinh, TH, Nguyen, DN, Pham, BS & Dutkiewicz, E 2024, 'Twin Auto-Encoder Model for Learning Separable Representation in Cyberattack Detection'.

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