Electronics — Open Access Journal

In practical array systems, the gain-phase errors among antennas degrade the performance of direction finding significantly. In this paper, a novel sparse system model for direction of arrival (DOA) estimation in the scenario with gain-phase errors is proposed by exploiting the signal sparsity in the spatial domain. In contrast to the existing sparse-based methods using the grids to construct the dictionary matrix, a novel gridless method based on atomic norm and convex optimization is proposed, where the gain-phase errors are described by a diagonal matrix. With the Schur complement, a semidefinite programming is formulated from the optimization problem, and can be solved efficiently. With the gain-phase errors, the corresponding Cram’er-Rao lower bound (CRLB) of direction finding is derived as an estimation benchmark. Simulation results show that the proposed method performs better than the state-of-the-art methods in the scenario with correlated signals and gain-phase errors. Full article

Digital holography represents a novel media which promises to revolutionize the way the users interacts with content. This paper presents an in-depth review of the state-of-the-art algorithms for advanced processing and rendering of computer-generated holography. Open-access holographic data are selected and characterized as references for the experimental analysis. The design of a tool for digital hologram rendering and quality evaluation is presented and implemented as an open-source reference software, with the aim to encourage the approach to the holography research area, and simplify the rendering and quality evaluation tasks. Exploration studies focused on the reproducibility of the results are reported, showing a practical application of the proposed architecture for standardization activities. A final discussion on the results obtained is reported, also highlighting the future developments of the reconstruction software that is made publicly available with this work. Full article

Traditional bandgap reference (BGR) is sensitive to process variation and is not suitable for mass production. Consequently, a stacked piece-wise compensated bandgap reference (SPWBGR) with low beta bipolar is proposed, designed and fabricated in the 0.18 μm high-voltage (HV) BCD process. Two stacked BGR (SBGR) cores make up the proposed BGR circuit. Through setting the target reference voltage near the output voltage of SBGR cores, the feedback resistor ratio is reduced and the base current side-effect is significantly decreased. Notably, the SBGR core is implemented by the low beta npn bipolar and it relaxes the requirement for the high beta bipolar. The two SBGR cores are almost identical except for the temperature slope and feedback ratio. The two cores have different zero temperature coefficient (TC) points, one is set at −5 °C, and the other is set at 60 °C, named as SBGRA and SBGRB, respectively. The SBGRA and SBGRB output the same voltage at their zero TC point. The higher voltage of SBGRA and SBGRB is the output voltage. Through the process of tracking the maximum value of different SBGR cores, the proposed SPWBGR achieves 2.6 ppm/°C TC from −40 to 100 °C. As a result, the average TC for five random samples is 5.3 ppm/°C. The line regulation is 2 mV/V from 4.5 to 5.5 V power supply. The current consumption is 6.8 µA. The active area of the proposed BGR is 0.075 mm². Full article

In this paper, we propose two data augmentation schemes for deep learning architecture that can be used to directly estimate user location in an indoor environment using mobile phone tracking and electronic fingerprints based on reference points and access points. Using a pretrained model, the deep learning approach can significantly reduce data collection time, while the runtime is also significantly reduced. Numerical results indicate that an augmented training database containing seven days’ worth of measurements is sufficient to generate acceptable performance using a pretrained model. Experimental results find that the proposed augmentation schemes can achieve a test accuracy of 89.73% and an average location error that is as low as 2.54 m. Therefore, the proposed schemes demonstrate the feasibility of data augmentation using a deep neural network (DNN)-based indoor localization system that lowers the complexity required for use on mobile devices. Full article

We propose a scale-invariant deep neural network model based on wavelets for single image super-resolution (SISR). The wavelet approximation images and their corresponding wavelet sub-bands across all predefined scale factors are combined to form a big training data set. Then, mappings are determined between the wavelet sub-band images and their corresponding approximation images. Finally, the gradient clipping process is used to boost the training speed of the algorithm. Furthermore, stationary wavelet transform (SWT) is used instead of a discrete wavelet transform (DWT), due to its up-scaling property. In this way, we can preserve more information about the images. In the proposed model, the high-resolution image is recovered with detailed features, due to redundancy (across the scale) property of wavelets. Experimental results show that the proposed model outperforms state-of-the algorithms in terms of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Full article

The last few decades have witnessed the rapid development of networked control systems due to their significant advantages and they have been applied to variant industrial areas such as unmanned surface vehicles, unmanned space vehicles, smart grids, wastewater treatment processes, Internet-based teleoperation, intelligent transportation systems and so on [...] Full article

The protection of sensitive loads against voltage drop is a concern for the power system. A fast fault current limiter and circuit breaker can be a solution for rapid voltage recovery of sensitive loads. This paper proposes a compound type of current limiter and circuit breaker (CLCB) which can limit fault current and fast break to adjust voltage sags at the protected buses. In addition, it can act as a circuit breaker to open the faulty line. The proposed CLCB is based on a series L-C resonance, which contains a resonant transformer and a series capacitor bank. Moreover, the CLCB includes two anti-parallel power electronic switches (a diode and an IGBT) connected in series with bus couplers. In order to perform an analysis of CLCB performance, the proposed structure was simulated using MATLAB. In addition, an experimental prototype was built, tested, and the experimental results were reported. Comparisons show that experimental results were in fair agreement with the simulation results and confirm CLCB’s ability to act as a fault current limiter and a circuit breaker. Full article

For multiple-antenna systems, the technologies of joint symbol and channel parameter estimation have been developed in recent works. However, existing technologies have a number of problems, such as performance degradation and the large cost of prior information. In this paper, a tensor space-time coding scheme in multiple-antenna systems was considered. This scheme allowed spreading, multiplexing, and allocating information symbols associated with multiple transmitted data streams. We showed that the received signal was formulated as a third-order tensor satisfying a Tucker-2 model, and then a robust semi-blind receiver was developed based on the optimized Levenberg–Marquardt (LM) algorithm. Under the assumption that the instantaneous channel state information (CSI) is unknown at the receiving end, the proposed semi-blind receiver jointly estimates the information symbol and channel parameters efficiently. The proposed receiver had a better estimation performance compared with existing semi-blind receivers, and still performed well when the channel became strongly correlated. Moreover, the proposed semi-blind receiver could be extended to the multi-user massive multiple-input multiple-output (MIMO) system for joint symbol and channel estimation. Computer simulation results were shown to demonstrate the effectiveness of the proposed receiver. Full article

With the development of engineering technology, the distributed design-based Branch-Trimming Robot (BTR) has been used to ensure the power supply security of transmission lines. However, it remains difficult to combine distributed BTRs with a wireless sensor network to build an efficient multi-robot system. To achieve this combination, a dynamic network topology control method was proposed, combining the motion characteristics of robots with the structure of a distributed wireless sensor network. In addition, a topology-updating mechanism based on node signal strength was adopted as well. To achieve efficient data transmission for distributed multi-robot systems, the present study focused on the design of a distributed network model and a dynamic network topology control strategy. Several simulation and test scenarios were implemented, and the changes of network performance under different parameters were studied. Furthermore, the real scene-based dynamic topology control method considers the relationship between network performance and antenna layout. Full article

Cloud computing is becoming a powerful parallel data processing method, and it can be adopted by many network service providers to build a service framework. Although cloud computing is able to efficiently process a large amount of data, it can be attacked easily due to its massively distributed cluster nodes. In this paper, we propose a secure and high-integrity YARN framework (SHIYF), which establishes a close relationship between speculative execution and the security of Yet Another Resource Negotiator (YARN, MapReduce 2.0). SHIYF computes and compares the MD5 hashes of the intermediate and final results in the MapReduce process by launching the speculative executions in a certain ratio, which is able to find actual and potentially malicious nodes in the Hadoop cluster. The prototype of SHIYF is implemented based on Hadoop 2.8.0. In this paper, theoretical derivations and experiments show that SHIYF not only guarantees the security and high integrity of the MapReduce process but also successfully locates the malicious nodes and the potential malicious ones in Hadoop, while increasing overhead slightly. Furthermore, the malicious node detection ratio is more than 87%. Full article

In this paper, an efficient implementation of the four-step current commutation technique for controlling bidirectional power switches in a Matrix Converter (MC) is proposed. This strategy is based on the enhanced pulse width modulation peripheral included in the $C2000$ Delfino 32-bit microcontroller of Texas Instruments. By tuning the algorithmic parameters contained in this module, the four-step commutation process is carried out on the Microcontroller Unit (MCU) without overloading the full complex processor and avoiding the use of additional special hardware such as Field-Programmable Gate Arrays (FPGA) or Complex Programmable Logic Devices (CPLD) when controlling the MC. The algorithm is implemented on the TMS320F28379D MCU and operationally validated on an MC prototype, where the functionality of the proposal is demonstrated. Full article

As digital data have increased exponentially due to an increasing number of information channels that create and distribute the data, distributed in-memory systems were introduced to process big data in real-time. However, when the load is concentrated on a specific node in a distributed in-memory environment, the data access performance is degraded, resulting in an overall degradation in the processing performance. In this paper, we propose a new load balancing scheme that performs data migration or replication according to the loading status in heterogeneous distributed in-memory environments. The proposed scheme replicates hot data when the hot data occurs on the node where a load occurs. If the load of the node increases in the absence of hot data, the data is migrated through a hash space adjustment. In addition, when nodes are added or removed, data distribution is performed by adjusting the hash space with the adjacent nodes. The clients store the metadata of the hot data and reduce the access of the load balancer through periodic synchronization. It is confirmed through various performance evaluations that the proposed load balancing scheme improves the overall load balancing performance. Full article

This work presents fence shaping for dipole antenna operating at 5G high-band frequencies. A via fence is employed around the dipole to suppress back radiation. By varying the geometric shape of the fence, the dipole’s radiation characteristics can be controlled, which adds an additional degree of freedom to the design. This was investigated by studying different fence shapes, namely rectangular-, U-, and V-shaped fences. The wide bandwidth (higher than 6.5 GHz) centered around 28 GHz, and the stable radiation performance from 24 GHz to 32 GHz made the proposed structure capable of supporting multiple 5G frequency bands and the fence shaping help modulate the gain and HPBW of the dipole. All fabricated prototypes attained front-to-back radiation ratio (F/B) higher than 36 dB, with good gain/HPBW performances of 14.1 dBi/103.7°, 13.5dBi/118°, and 12.6 dBi/133° from the V-fence, U-fence, and rectangular fence 4 × 1 arrays, respectively. Full article

The original user relay (UR) selection scheme of non-orthogonal multiple access-based cooperative opportunistic multicast scheme, which realizes inter-group cooperation between two multicast groups, ignores the distribution trend of candidate UR in the cell and adopts fixed efficient relay selection range (ERSR) to select UR. It results in high UR selection ratio. Then the coverage efficiency, defined as the ratio of successfully received users to URs, is low. To tackle this problem, a range-division user relay (RDUR) selection scheme is proposed in this paper. Firstly, it divides the circular coverage range of base station into several continuous annular areas (AAs). Secondly, different ERSRs are assigned to unsuccessfully received users in different AAs. Under different ERSR assignments, the performances of UR selection ratio and coverage ratio are analyzed. Lastly, the radius set of ERSR that optimizes system coverage efficiency is used to perform UR selection. From simulation results, with different radius sets, analytical results of UR selection ratio and coverage ratio match well with their simulated ones. It is proved that ERSR allocation affects UR selection ratio and coverage ratio. With RDUR scheme, coverage efficiency increases by at least 14% and capacity efficiency has also been improved. Full article

Lane changing systems have consistently received attention in the fields of vehicular communication and autonomous vehicles. In this paper, we propose a lane change system that combines deep reinforcement learning and vehicular communication. A host vehicle, trying to change lanes, receives the state information of the host vehicle and a remote vehicle that are both equipped with vehicular communication devices. A deep deterministic policy gradient learning algorithm in the host vehicle determines the high-level action of the host vehicle from the state information. The proposed system learns straight-line driving and collision avoidance actions without vehicle dynamics knowledge. Finally, we consider the update period for the state information from the host and remote vehicles. Full article

A thermal fatigue life prediction model of microelectronic chips based on thermal fatigue tests and solder/substrate interfacial singularity analysis from finite element method (FEM) analysis is established in this paper. To save the calculation of interfacial singular parameters of new chips for life prediction, and improve the accuracy of prediction results in actual applications, a hybrid genetic algorithm–artificial neural network (GA–ANN) strategy is utilized. The proposed algorithm combines the local searching ability of the gradient-based back propagation (BP) strategy with the global searching ability of a genetic algorithm. A series of combinations of the dimensions and thermal mechanical properties of the solder and the corresponding singularity parameters at the failure interface are used to train the proposed GA-BP network. The results of the network, together with the established life prediction model, are used to predict the thermal fatigue lives of new chips. The comparison between the network results and thermal fatigue lives recorded in experiments shows that the GA-BP strategy is a successful prediction technique. Full article

The purpose of this study is to provide an energy verification method for the nozzle of the SC200 proton therapy facility to ensure safe redundancy of treatment. This paper first introduces the composition of the energy selection system of the SC200 proton therapy facility. Secondly, according to IEC60601 standard, the energy verification requirement that correspond to 1 mm error in water is presented. The allowable difference between the measured magnetic field and the reference are calculated based on the energy verification requirements to select the field resolution of the Hall probe. To ensure accuracy and stability, two Hall probes are mounted on the dipole to monitor the magnetic field strength to verify the proton beam energy in real time. In addition, the test results of the residual field of the dipole show that the probe system meets the accuracy requirements of energy verification. Furthermore, the maximum width of the slit of the energy selection system in accordance with the IEC standard at the corresponding energy is calculated and compared with the actual position of the movable slit to verify the momentum divergence of the proton beam. Finally, we present an energy verification method. Full article

The emergence of Vehicular Ad Hoc Networks (VANETs) is expected to be an important step toward achieving safety and efficiency in intelligent transportation systems (ITS). One important requirement of safety applications is that vehicles are able to communicate with neighboring vehicles, with very low latency and packet loss. The high mobility, unreliable channel quality and high message rates make this a challenging problem for VANETs. There have been significant research activities in recent years in the development of congestion control algorithms that ensure reliable delivery of safety messages in vehicle-to-vehicle (V2V) communication. In this paper, we present a comprehensive survey of congestion control approaches for VANET. We identify the relevant parameters and performance metrics that can be used to evaluate these approaches and analyze each approach based a number of factors such as the type of traffic, whether it is proactive or reactive, and the mechanism for controlling congestion. We conclude this paper with some additional considerations for designing V2V communication protocols and interesting and open research problems and directions for future work. Full article

The transportation network promotes key human development links such as social production, population movement and resource exchange. As cities continue to expand, transportation networks become increasingly complex. A bad traffic network design will affect the quality of urban development and cause regional economic losses. How to plan transportation routes and allocate transportation resources is an important issue in today’s society. This study uses the network reliability method to solve traffic network problems. Network reliability refers to the probability of a successful connection between the source and sink nodes in the network. There are many systems in the world that use network architecture; therefore, network reliability is widely used in various practical problems and cases. In the past, some scholars have used network reliability to solve traffic service network problems. However, the processing of time is not detailed enough to fully express the real user’s time requirements and does not consider that the route traffic will affect the reliability of the entire network. This study improves on past network reliability methods by using a fuzzy system and a time window to construct a network model. Using the concept of fuzzy systems, according to past experience, data or expert predictions to define the degree of flow, time and reliability, can also determine the relationship between these factors. The time window can be adjusted according to the time limit in reality, reaching the limit of the complete expression time. In addition, the network reliability algorithm used in this study is a direct algorithm. Compared with the past indirect algorithms, the computation time is greatly reduced and complex problems can be solved more efficiently. Full article