Abstract:Artificial Intelligence of Things(AIoT), as a deep integration of artificial intelligence and IoT technologies, has rapidly emerged as an important development direction for the new generation of information technology. To fully explore the potential of AIoT technology, this paper focuses on the application and development of AIoT technology in the field of intelligent connected vehicles. It delves into the integrated system architecture of AIoT and intelligent connected vehicles, systematically reviews the latest technological applications of AIoT in this field, and provides strategic recommendations for leveraging AIoT technology to promote the advancement and development of intelligent connected vehicle technology.

Abstract:Narrow Band Internet of Things(NB-IoT), as a low-power wide area network technology, is specially designed to connect a large number of low-power devices. The low-orbit satellite IoT based on this technology has lower transmission loss and delay, and can achieve seamless coverage of the earth through constellations. However, low-orbit satellites are highly dynamic and face QoS requirements from different users. These factors greatly affect the throughput performance of existing resource scheduling algorithms. In response to these challenges, this paper proposes a high-throughput NB-IoT low-orbit satellite IoT resource scheduling algorithm by comprehensively considering satellite channel characteristics, reliability and delay requirements between different users, and differential Doppler caused by high satellite dynamics in a scenario where a large number of IoT users request wireless resources and time-frequency resources are limited. Simulation results show that compared with existing methods, the resource scheduling algorithm proposed in this paper shows significant performance improvement in system throughput.

Abstract:Aiming at the traffic surge problem caused by massive smart device access in Power Internet of Things(PIoT), a resource scheduling strategy of Mobile Edge Computing(MEC) with delay and energy consumption equalization is proposed. Considering the channel conditions, the safety temperature protection mechanism of electric equipment and the energy consumption of equipment, the energy consumption model and thermal power consumption constraints on the equipment side are constructed based on the Landaer principle. Under the premise of ensuring queue stability, the long-term average time energy consumption of the system is minimized by jointly optimizing the task offloading decision, transmission power and computational resource allocation. To solve this stochastic optimization problem, Lyapunov theory is introduced to transform the problem into a deterministic optimization problem for each time slot. Simulation results show that this strategy is able to reduce the system energy consumption relative to the baseline scheme and achieve an equilibrium between energy consumption and delay.

Abstract:Wireless Sensor Network(WSN) in the power system can sense and collect the status of the working equipment and environmental data in real time, which is an important technology to promote the development of smart grid. Aiming at the special requirements of network survival time, transmission delay, and transmission packet loss rate of WSN in substation scenarios, a WSN routing scheme based on reinforcement learning is proposed. The sending process of packets in WSN is abstracted as a Markov Decision Process(MDP), the rewards are reasonably set according to the optimization objective, and the optimal routing solution method based on Q-learning is given. Simulation results and numerical analysis show that the proposed scheme outperforms the benchmark scheme in terms of network survival time, transmission delay, and packet loss rate.

Abstract:In pedestrian positioning methods, the strapdown inertial navigation system requires processing data from the Inertial Measurement Unit(IMU) sensors, and the position of the pedestrian is obtained after algorithmic processing, thus placing high demands on the real-time performance and low power consumption of the chip. Since most pedestrian positioning algorithms are developed based on floating-point sensor data, the terminal device is generally required to handle floating-point data. The fifth-generation Reduced Instruction Set Computer(RISC-V) architecture, as an open-source architecture, can save on architectural licensing fees and has a wide range of applications in the field of the Internet of Things. Moreover, its floating-point(F) and vector(V) high-performance extension instructions can well meet the real-time requirements of pedestrian positioning algorithms. In response to the specific performance requirements of the pedestrian positioning system, a System on Chip (SoC) for pedestrian positioning based on a floating-point core vector processor optimized RISC-V architecture is proposed and verified in actual systems. A performance comparison analysis with several quasi-32-bit architecture RISC-V processors and standard processor schemes of algorithm-specific IPs (locate_IP) generated by High-Level Synthesis(HLS) components shows that the design has achieved a 34-fold improvement in performance and a 5.6-fold improvement in energy efficiency, meeting the requirements of micro terminals.

Abstract:The function characteristics, main indicators, working principle and typical system compositions of the spaceborne microwave radiometer are briefly introduced. The development level and application status of current domestic and foreign spaceborne terahertz band polarization grid, frequency selective surface, feed horn, receiver front-end etc, are highlighted by combining with the key components of quasi-optical feed system and receiver, as well as the application requirements on key performance specifications such as sensitivity. The gaps between key specifications are compared. The technical difficulties in product design and development of terahertz frequency are analyzed. In view of the development demand of spaceborne microwave radiometer of China, the development trend and application demand of key terahertz components are prospected, providing reference for the development of spaceborne passive remote sensing in China.

Abstract:In order to improve the efficiency of quantitative analysis of ash and volatile content in coal and reduce pollution, a method for quantitative analysis of coal ash and volatile content based on THz Time Domain Spectroscopy(THz-TDS) is proposed. In this paper, the relationship between terahertz absorption characteristics and ash content in coal is studied. The results show that the effective spectrum range of coal is 0.2~2.2 THz, and there is no obvious absorption peak in 0.2~2.2 THz; the ash content is the main factor affecting the absorption characteristics of the terahertz band. The effects of preprocessing methods, Support Vector Machine(SVM) model and Partial Least Squares(PLS) model on the prediction effect are compared. The results show that Savitzky-Golay smoothing and Moving Average Filter(MAF) smoothing do not improve the prediction effect of external validation sets, and the prediction effect of SVM model on ash and volatile content is better than that of PLS model. The correlation coefficients(R_p) and Root Mean Square Error of Prediction(RMSEP) of the external validation set of ash and volatile of SVM models are 0.933, 3.223, 0.724 and 5.772, respectively. The terahertz technology combined with SVM model can predict ash and volatile content in coal, and the analysis time can be shortened to be less than 10 minutes, which has improved the analysis efficiency.

Abstract:The traditional satellite transparent relay mode causes significant delays in the new satellite-ground network. In order to improve the service capability for ground users, this paper proposes a caching scheme on both the Low-Earth Orbit(LEO) satellite and the ground content server, and models the transmission throughput problem of the satellite-ground network considering co-frequency interference among LEO satellites, ground content servers, and ground users. The improved Particle Swarm Optimization(PSO) algorithm and the Supporting Hyperplane Optimization Toolkit(SHOT) solver are employed to solve the problem. The experimental results reveal that the SHOT solver can obtain a smoother result curve, and there is only about 2% fluctuation compared to the optimization PSO algorithm and the SHOT solver. Under the constraint of an 8 dB signal-to-noise ratio threshold and a maximum power of 20 W, the proposed approach can achieve a transmission rate of 45 Mbps and 37 Mbps, respectively, with interference from 2 satellites or 3 ground content servers. Furthermore, the study analyzes the running time of the two algorithms for various numbers of low-earth orbit satellites, ground content servers, and ground users. The optimization PSO algorithm is approximately 10 s faster than the SHOT solver, particularly when the number of the three categories is set to 4, in the worst-case scenario. The results indicate that heuristic algorithms are more suitable for modeling future complex satellite-ground networks and finding non-convex and nonlinear global solutions. They also perform better in terms of solving speed for high-dimensional problems.

Abstract:In the scenario of integrated terrestrial and space information networks, the integration of satellite communication with terrestrial 5G is an inevitable trend. For Orthogonal Frequency Division Multiplexing(OFDM), a key technology of the 5G air-interface protocol, how to efficiently serve the Low Earth Orbit(LEO) satellite communication systems with limited frequency band resources has become a hotspot. In view of the high dynamics of LEO satellites, system channel characteristics, service variability, and most Doppler frequency shifts, a dynamic resource allocation strategy for OFDM in LEO satellite communication is proposed. Firstly, based on the 3GPP standard and the maximization of spectral efficiency, the subcarrier spacing is selected, and the transmission performance of the channel is ensured by eliminating inferior sub-channels before subcarrier allocation, and the number of cycles during allocation is reduced by clustering in multiples; then, the subcarriers are greedily allocated according to user demand and channel characteristics; finally, the power allocated to a single user is applied according to the proportional water-filling principle. Simulation results show that the algorithm can effectively adapt to the LEO satellite scenario, reduce the complexity of the algorithm, and improve the system capacity while still ensuring the fairness of user demand and transmission rate.

Abstract:Meridian Project, a detailed investigation of the characteristics of field-aligned irregularities in the F region of the ionosphere in low latitude areas in China was conducted. During this process, a rare V-shaped structure of irregularities was identified. Further mapping of the fan-shaped diagram and analysis of its time-frequency characteristics in conjunction with ionosonde data were performed. The analysis results were compared with the airglow images of the corresponding period, and the results show that this V-shaped structure of irregularities is caused by the modulation of the background electric field of the ionosphere by gravity waves, leading to changes in its dynamic state.

Abstract:Compared with inorganic material photodetectors, photodetectors prepared with organic semiconductor materials have the advantages of simple fabrication process, easy integration, good flexibility, good ductility, and stable performance. However, the External Quantum Efficiency(EQE) and responsivity are usually low due to the thin absorber layer. Therefore, how to maximize the absorptivity of organic thin-film absorber layers with different optical structures has been extensively studied. In this study, a high-response organic photodetector based on a light-management structure was successfully fabricated. The experimental results show that the dark current is as low as 3.2 nA at a bias of -10 V. For the organic absorbing thin layer, good photocurrent responses were obtained at wavelengths from 260 to 980 nm, and a responsivity of 0.03 A/W was especially obtained at 850 nm. Compared with the pristine device, the organic photodetector with the light-management structure significantly increases the responsivity by 530%, an order-of-magnitude increase in specific detectivity, and a 200% increase in overall quantum efficiency. The above experimental results prove that the optical enhancement structure is important to this thin-film absorber photodetector, and its performance can be further improved to be comparable to traditional thick-film absorber photodetectors.

Abstract:Considering that most existing end-to-end Autoencoders(AE) are only suitable for point-to-point communication scenarios, this paper proposes a dynamic collaborative communication system based on AE, extending the AE based on deep learning to multi-point communication systems. Three neural network subsystems are constructed, each for learning the optimal encoding, transmission, and decoding at the transmitter, relay node, and receiver, respectively, with joint training of the three to achieve the best transmission performance of the multi-point communication system. Among them, the transmitter and receiver use one-dimensional convolutional layers for signal feature extraction and learning, while the relay node supports two classic relay cooperation methods, Amplify-and-Forward (AF) and Decode-and-Forward(DF), by introducing dense layers and one-dimensional convolutional layers. Simulation experiments show that under the conditions of additive white Gaussian noise and Rayleigh fading channels, the proposed model, using two different cooperation methods, has better error performance than a single point-to-point communication system, verifying the feasibility and effectiveness of the system scheme. In addition, the system supports dynamic node topologies, and without the need for additional training, this system supports real-time changes in the number of relay nodes.

Abstract:Aiming at the problem that it is difficult to meet the real-time requirements with the increase of data volume in the distributed data fusion algorithm of netted radar, the track association algorithm based on statistical double-threshold method in the data fusion process is studied, and a multi-threaded optimization idea based on Open Multi-Processing(OpenMP) is proposed. The operation speed of the internal algorithm is improved by OpenMP parallel calculation of the correlation distance between radar tracks, and the external data transmission speed is accelerated by using three threads to separate the data receiving, fusion and sending processes, thus improving the processing speed of the overall fusion process. Taking the large capacity target scenario as the test case, the processing time and optimization acceleration ratio are evaluated. The simulation results show that the proposed parallel optimization method can effectively improve the computing speed.

Abstract:When there is multipath propagation, the spatial spectrum direction-finding performance of circular arrays will be severely degraded. To address this, an algorithm based on the central symmetric array for smooth spatial spectrum estimation on a moving platform is proposed. This algorithm utilizes the spatial translation of the array to obtain multiple translated covariance matrices; at the same time, it leverages the symmetry of the central symmetric array to process the received data in reverse, obtaining the covariance matrix of the virtual array data. Subsequently, by stacking all covariance matrices, a new full-rank covariance matrix can be obtained, which achieves de-correlation processing and completes the estimation of the signal's direction of arrival. Simulation experiments have verified the effectiveness of this method and it has significant value for engineering applications.

Abstract:In response to the existing challenges of difficult detection and potential leakage in wafer level vacuum packaging, a Pirani gauge design and processing method that is compatible with silicon micro-device processes and can be processed in parallel within the same cavity is proposed for vacuum degree detection after wafer-level vacuum packaging. The Pirani gauge structure is processed using SOI silicon wafers, and the device is packaged at the wafer level through gold-silicon bonding. At the same time, the longitudinal electrode lead-out method of Through Silicon-Vias(TSV) is adopted to improve the gas sealing issue. Test results show that the temperature coefficient of the Pirani gauge resistance in the linear range is 1.58 Ω/℃, the detection sensitivity range is about 1~100 Pa, and the sensitivity reaches 61.67 Ω/ln(Pa). The proposed Pirani gauge can be processed in parallel with silicon micro-devices, providing a simple and feasible solution for in-wafer testing of the vacuum degree in wafer-level vacuum packaging cavities.

Abstract:As the main-stream technology to fabricate the deep-submicron T-gates of high-frequency GaN HEMT(High Electron Mobility Transistor) in industry, electron beam lithography faces the problems of low efficiency, insufficient yield, and high cost. In this paper, an 80 nm T-gate GaN HEMT with pure optical exposure has been successfully manufactured for the first time on a 6-inch industrial production line using integrated side wall technology, and the performance parameters of the device are comprehensively characterized and analyzed. The device displays a maximum output current per unit (millimeter) gate width of 993 mA, a peak transconductance of per unit (millimeter) gate width 385 mS, a threshold voltage of -3.25 V, an off-state breakdown voltage exceeding 80 V, and a f_T/f_max of 64/175 GHz. When operated at 28 V, the saturated output power, the associated power gain, and the power added efficiency of the device at 16 GHz are 26.95 dBm(4.9 W per millimeter), 11.08 dB, and 49.78% respectively; while at 30 GHz, these data are 26.15 dBm(4.1 W per millimeter), 8.8 dB, and 44% respectively. The results show that the integrated sidewall technology has a good application prospect in deep-submicron GaN HEMT manufacturing.