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Future Terahertz communications exhibit significant potential in accommodating ultra-high-rate services. Employing extremely large-scale array antennas is a key approach to realize this potential, as they can harness substantial beamforming gains to overcome the severe path loss and leverage the electromagnetic advantages in the near field. This paper proposes novel estimation methods designed to enhance efficiency in Terahertz widely-spaced multi-subarray (WSMS) systems. Initially, we introduce three sparse channel representation methods: polar-domain representation (PD-R), multi-angular-domain representation (MAD-R), and two-dimensional polar-angular-domain representation (2D-PAD-R). Each method is meticulously developed for near-field WSMS channels, capitalizing on their sparsity characteristics. Building on this, we propose four estimation frameworks using the sparse recovery theory: polar-domain estimation (PD-E), multi-angular-domain estimation (MAD-E), two-stage polar-angular-domain estimation (TS-PAD-E), and two-dimensional polar-angular-domain estimation (2D-PAD-E). Particularly, 2D-PAD-E, integrating a 2D dictionary process, and TS-PAD-E, with its sequential approach to angle and distance estimation, stand out as particularly effective for near-field angle-distance estimation, enabling decoupled calculation of these parameters. Overall, these frameworks provide versatile and efficient solutions for WSMS channel estimation, balancing low complexity with high-performance outcomes. Additionally, they represent a fresh perspective on near-field signal processing.

Obtaining all perfect matchings of a graph is a tough problem in graph theory, and its complexity belongs to the #P-Complete class. The problem is closely related to combinatorics, marriage matching problems, dense subgraphs, the Gaussian boson sampling, chemical molecular structures, and dimer physics. In this paper, we propose a quadratic unconstrained binary optimization formula of the perfect matching problem and translate it into the quantum Ising model. We can obtain all perfect matchings by mapping them to the ground state of the quantum Ising Hamiltonian and solving it with the variational quantum eigensolver. Adjusting the model’s parameters can also achieve the maximum or minimum weighted perfect matching. The experimental results on a superconducting quantum computer of the Origin Quantum Computing Technology Company show that our model can encode 2ⁿ dimensional optimization space with only O(n) qubits consumption and achieve a high success probability of the ground state corresponding to all perfect matchings. In addition, the further simulation results show that the model can support a scale of more than 14 qubits, effectively resist the adverse effects of noise, and obtain a high success probability at a shallow variational depth. This method can be extended to other combinatorial optimization problems.

In this study, we conducted a rigorous analysis of the signal characteristics of both the received echoes of targets and mutual interference. We then considered the low-rank property of strong mutual interference in the time domain, alongside the sparsity of targets within the RD domain. We then introduced a novel method predicated on RD sparse regularization for interference mitigation, target detection, and the estimation of three-dimensional parameters (range, velocity, and direction) for automotive radars. Detailed iteration deviation and experiment simulation can be found in Appendix B.

Delay/disruption tolerant networking (DTN) is proposed as a networking architecture to overcome challenging space communication characteristics for reliable data transmission service in presence of long propagation delays and/or lengthy link disruptions. Bundle protocol (BP) and Licklider Transmission Protocol (LTP) are the main key technologies for DTN. LTP red transmission offers a reliable transmission mechanism for space networks. One of the key metrics used to measure the performance of LTP in space applications is the end-to-end data delivery delay, which is influenced by factors such as the quality of spatial channels and the size of cross-layer packets. In this paper, an end-to-end reliable data delivery delay model of LTP red transmission is proposed using a roulette wheel algorithm, and the roulette wheel algorithm is more in line with the typical random characteristics in space networks. The proposed models are validated through real data transmission experiments on a semi-physical testing platform. Furthermore, the impact of cross-layer packet size on the performance of LTP reliable transmission is analyzed, with a focus on bundle size, block size, and segment size. The analysis and study results presented in this paper offer valuable contributions towards enhancing the reliability of LTP transmission in space communication scenarios.

In recent years, artificial intelligence technology has been widely used in many fields, such as computer vision, natural language processing and autonomous driving. Machine learning algorithms, as the core technique of AI, have significantly facilitated people’s lives. However, underlying fairness issues in machine learning systems can pose risks to individual fairness and social security. Studying fairness definitions, sources of problems, and testing and debugging methods of fairness can help ensure the fairness of machine learning systems and promote the wide application of artificial intelligence technology in various fields. This paper introduces relevant definitions of machine learning fairness and analyzes the sources of fairness problems. Besides, it provides guidance on fairness testing and debugging methods and summarizes popular datasets. This paper also discusses the technical advancements in machine learning fairness and highlights future challenges in this area.

Symbiotic radio (SR) is one of the attractive communication technologies to facilitate large-scale Internet of Things (IoT) connections with enhanced energy and spectrum efficiency, where passive backscatter devices (BDs) modulate their information over the radio frequency (RF) signals emitted by the active primary transmitters (PTs). Meanwhile, the primary transmission can be strengthened with the additional multipaths created by BDs. To capitalize to a greater extent on the mutualism relationship between the two types of communication, this paper studies multiple-input multiple-output (MIMO) SR communication systems including multiple PTs and massive BDs. We derive the achievable rate expressions of each PT and BD, as well as the sum rate expressions of primary and secondary communication, respectively. Then asymptotic analysis is given to derive the active and passive communication rates with a large number of BDs. Furthermore, for the general case with a finite number of BDs, we study the precoding optimization problem to maximize the sum rate of primary communication, while ensuring that the sum rate of secondary communication and the individual rate for each PT and BD in the prescribed active and passive user sets satisfy the specified thresholds. Simulation results are presented to verify the analytical studies.

Feedback shift registers (FSRs) are pivotal in generating pseudorandom sequences for stream ciphers and play a crucial role in error detection and code correction. This paper investigates the resilience of grain-like cascade FSRs (GLC-FSRs) against two types of fault attacks: hard and soft. First, we introduce a new criterion for assessing the nonsingularity of GLC-FSRs using the structure matrices of feedback functions, which enable the measurement of the number of nonsingular GLC-FSRs. Second, we demonstrate that GLC-FSRs subject to hard fault attacks become singular as determined by this new criterion. Ultimately, by constructing a soft fault bit set, we discuss the resilience of GLC-FSRs to soft fault attacks. Results demonstrate that singular GLC-FSRs remain singular after being injected by soft fault attacks. Conversely, for nonsingular GLC-FSRs, suitable soft fault attacks are designed to maintain their nonsingular status.

The threshold voltage modulation of carbon nanotube thin-film transistors (TFTs) and flexible three-dimensional (3D) integration circuits has become hot research topics for carbon-based electronics. In this paper, a doping-free gate electrode technology is introduced to significantly modulate the threshold voltage of polymer-sorted semiconducting single-walled carbon nanotube (sc-SWCNT) TFTs in combination with the highly effective gate-controlling ability of solid-state electrolyte thin films as the dielectrics. A systematic investigation was conducted on the impact of printed silver, evaporated silver, and evaporated aluminum (Al) gate electrodes on the threshold voltage of flexible printed bottom-gate and top-gate SWCNT TFTs. The results indicate that the SWCNT TFTs with Al gate electrodes exhibit enhancement-mode characteristics with excellent electrical properties, such as the negative threshold voltages (−0.6 V), high I_on/I_off (up to 10⁶), low subthreshold swing (61.4 mV · dec⁻¹), and small hysteresis. It is attributed to either the formation of lower work function thin films (Al₂O₃) at the electrode/dielectric layer interfaces through the natural oxidation of the Al bottom-gate electrodes or the dipole reaction of the Al top-gate electrodes from X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS) data. In addition, 3D complementary metal-oxide-semiconductor (CMOS) inverters with common gate electrodes were constructed using the resulting enhancement-mode P-type SWCNT TFTs and matched N-type SWCNT TFTs, which shows high voltage gain (34), rail-to-rail output and high noise margins (80.04%, V_DD = −1 V) as well good mechanical flexibility at low operation voltages. It demonstrates that SWCNT TFTs have great advantages for building large-scale 3D flexible integrated circuits.

Communication is crucial to the performance of distributed training. Today’s solutions tightly couple the control and data planes and lack flexibility, generality, and performance. In this study, we present SDCC, a software-defined collective communication framework for distributed training. SDCC is based on the principle of modern systems design to effectively decouple the control plane from the data plane. SDCC abstracts the operations for collective communication in distributed training with dataflow operations and unifies computing and communication with a single dataflow graph. The abstraction, together with the unification, is powerful: it enables users to easily express new and existing collective communication algorithms and optimizations, simplifies the integration with different computing engines (e.g., PyTorch and TensorFlow) and network transports (e.g., Linux TCP and kernel bypass), and allows the system to improve performance by exploiting parallelism exposed by the dataflow graph. We further demonstrate the benefits of SDCC in four use cases.

In this paper, a resilient tracking control scheme with cooperative collision avoidance performance is studied for the fixed-wing unmanned aerial vehicle (UAV) leader-follower formation in the presence of actuator failures and external disturbances. Firstly, based on the control objectives of UAV formation tracking and collision avoidance, the transformation tracking errors are obtained using the prescribed performance control technique. Next, a fault detection mechanism is introduced to determine if there is the actuator fault. Subsequently, the event-triggered resilient fault observers are designed based on a dynamic event-triggered mechanism to estimate actuator faults. Furthermore, the prescribed performance functions and the H_∞ performance index are employed to ensure the UAV formation collision-free and mitigate the impact of disturbances. Moreover, the resilient controller is designed to minimize the effect of the perturbations for the control gain and the fault observer gain on the system. The stability of the system is also proven through the Lyapunov stability analysis, and the controller gains are calculated by solving the linear matrix inequality. Finally, the validity of the proposed control strategy is demonstrated by the simulation analysis.