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Industrial Internet of Things (IIoT) is an emerging area that fifth-generation (5G) mobile communication system penetrates industrial manufacturing applications. The indoor factory has larger space and there are a lot of metal machine tools distributed in it, which makes its radio propagation characteristics and corresponding channel models significantly different from those of the indoor office and indoor hotspot. To support the design and the evaluation of the IIoT techniques, the 3rd Generation Partnership Project (3GPP) released the first 5G IIoT standard model in October 2019. In this article, we give a detailed explanation of this IIoT model and compare it with other indoor models. First, we introduce the standardization of 3GPP IIoT channel model and its motivation. Second, four IIoT subscenarios, which are classified according to the clutter density and antenna height, are described. Third, the potential frequency bands of 5G IIoT are summarized. Fourth, the models of channel parameters, including the path loss and the line-of-sight (LOS) probability, the root mean-square (RMS) delay spread, and the angular spread, are given. Among them, the models of path loss and LOS probability take the antenna height and clutter density into consideration. The model of RMS delay spread changes from frequency-dependent to volume-dependent in order to catch the size variation of factories. Finally, two newly added key channel characteristics, dual mobility and absolute time of arrival, which help to describe the robot movement and positioning, are also presented.

Terahertz (THz) communication has been envisioned as a key enabling technology for sixth-generation (6G). In this paper, we present an extensive THz channel measurement campaign for 6G wireless communications from 220 GHz to 330 GHz. Furthermore, the path loss is analyzed and modeled by using two single-frequency path loss models and a multiple-frequencies path loss model. It is found that at most frequency points, the measured path loss is larger than that in the free space. But at around 310 GHz, the propagation attenuation is relatively weaker compared to that in the free space. Also, the frequency dependence of path loss is observed and the frequency exponent of the multiple-frequencies path loss model is 2.1. Moreover, the cellular performance of THz communication systems is investigated by using the obtained path loss model. Simulation results indicate that the current inter-site distance (ISD) for the indoor scenario is too small for THz communications. Furthermore, the tremendous capacity gain can be obtained by using THz bands compared to using microwave bands and millimeter wave bands. Generally, this work can give an insight into the design and optimization of THz communication systems for 6G.

In this brief, a millimeter-wave (mm-Wave) wideband frequency quadrupler is demonstrated in a 55-nm CMOS technology. It cascades two injection-locked frequency doublers (ILFD). Each of them consists of an oscillator gain stage realized by an injection-locked oscillator (ILO) and a frequency doubler implemented by a push-push pair. A tail feedback loop is proposed and applied in the second ILFD. It effectively boosts the injection current for the second ILFD. Therefore, both the operating bandwidth and output power (Pout) of the circuit are prominently improved. In addition, transformer-based high-order resonators are used to reduce the phase variation of their impedance around 0° and hence extend the locking range of ILOs. According to the measurement results, a frequency range of 30.8 ~ 40 GHz is achieved. The maximum Pout is up to -7.1 dBm without additional buffers. The circuit also attains a wide 3-dB frequency bandwidth of Pout, which is from 32 to 38.4 GHz. The harmonic rejection ratios of the frequency quadrupler are 16.5 ~ 25.9 dBc at the second-order harmonic and 31 ~ 45 dBc at the fundamental and third-order harmonics over the entire operating bandwidth. The core area occupies only 0.24 mm2.

This paper presents an empirical study of the uplink and downlink azimuth angle of arrival (AoA) in an urban micro (UMi) scenario at 28 GHz. At present, most UMi measurements are conducted in the downlink and then the uplink situation is inferred assuming channel reciprocity. Although the channel correlation coefficient of the uplink and downlink can be as high as 0.8, this does not mean that they are the same. Only a real uplink measurement can accurately describe its channel conditions, and this is what this study does. A receiver equipped with a rotatable horn antenna is mounted at the base station and the user terminal, respectively, in simulating the uplink and downlink. To improve the angular resolution, we extract the multipath components (MPCs) using the space-alternating generalized expectation-maximization algorithm. Also, a spatial lobe approach is used to cluster the MPCs in the power angular spectrum. By matching MPCs with objects in the environment, we find that direct propagation and first-order reflections are dominant in line-of-sight and non-line-of-sight cases. By comparing our measurement with those in standard channel models, we verify that the AoA of clusters follows a Gaussian distribution in the uplink and downlink. In addition, a two-dimensional Gaussian distribution for ray AoA and power is established to reflect their correlation.

Vehicle-to-vehicle (V2V) wireless communications have many envisioned applications for ensuring traffic safety and for addressing traffic congestion. However, developing suitable communication systems and standards for this purpose requires developers to have accurate models for the V2V propagation channel. Likewise, the dynamic evolution of multipath components (MPCs) in V2V channels has not been well modeled in existing models. In this paper, we propose a geometry-based stochastic channel model for a lightly built-up urban environment and then parametrize the model from measurements. The MPCs are extracted based on a high-resolution parameter estimation; they are tracked and clustered through a joint algorithm. The identified clusters are classified as line-of-sight, reflections from static scatterers, reflections from mobile scatterers, multiple-bounce reflections, and diffuse scattering. Specifically, the multiple-bounce reflections are modeled as twin clusters that follow the COST 273/COST2100 approach. The paper gives a full parameterization of the channel model and supplies a step-by-step implementation recipe. We verify the model by comparing two second-order statistics, i.e., the root-mean-square (RMS) delay spread and the angular spreads of arrival/departure derived from the channel model, to the results obtained directly from the measurements. Furthermore, we also identify several key factors that strongly impact the synthetic channel performance.

As the backbone of social development, college students’ level of physical exercise has always been the focus of research by experts and scholars. Most of the research methods are on the strength of literature data, questionnaire survey, mathematical statistics and comparative analysis. Based on the classification of college students and the influence and flow law of inter-class population, this paper establishes a differential equation system. By analyzing the existence and stability of the equilibrium of this system and the possible fold or backward bifurcations at the equilibrium, the quantitative analysis of college students’ physical exercise trends on campus is carried out. This paper aims to improve the participation of college students in physical exercise by maximizing the number of students in the third categories. The results of theoretical proof, sensitivity analysis and numerical simulation show that in the initial stage, promoting peer-to-peer communication is the most effective measure. Secondly, when the effect of peer-to-peer interaction reaches saturation point, the way to improve physical education can achieve significant results. To fundamentally improve the enthusiasm of college students to participate in sports activities, we should start from the level of consciousness and enhance students’ awareness of physical exercise from an early age.

Discriminating between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, or LOS identification , is important for a variety of purposes in wireless systems, including localization and channel modeling. LOS identification is especially challenging in vehicle-to-vehicle (V2V) networks since a variety of physical effects that occur at different spatial/temporal scales can affect the presence of LOS. This paper investigates machine learning techniques for LOS identification in V2V networks using an extensive set of measurement data and then develops robust and efficient identification solutions. Our approach exploits several static and time-varying features of the channel impulse response (CIR), which are shown to be effective. Specifically, we develop a fast identification solution that can be trained by using the power angular spectrum. Moreover, based on the measurement data, we also compare three different machine learning methods, i.e., support vector machine, random forest, and artificial neural network, in terms of their ability to train and generate the classifier. The results of our experiments conducted under various V2V environments, which were then validated using $K$ -fold cross-validation, show that our techniques can distinguish the LOS/NLOS conditions with an error rate as low as 1%. In addition, we investigate the impact of different training and validating strategies on the identification accuracy.

Understanding the physicochemical characteristics of oil-based cuttings (OBCs) is an important foundation for subsequent treatment and management. The macro- and microscopic properties of white oil-based cuttings (WOBCs) and diesel-based cuttings (DBCs) after the different pretreatment steps have been assessed using scanning electron microscopy. The organic and inorganic compositions of OBCs have been analyzed using X-ray diffraction, Fourier-transform infrared spectrometry, and gas chromatography-mass spectrometry. Inorganic matter (SiO2, BaSO4, and CaCO3), alkanes, aromatic compounds, and water were the main components of OBCs. The organic content (26.14%) and alkane content of the WOBCs were higher than that of the DBCs, whereas for the inorganic content (70.87%), the reverse was true. The macro- and micromorphologies of OBCs were quite different because their oil and water contents were different. The oil contents of OBCs decreased in the order A1 (14.64%) > A3 (12.67%) > A2 (11.06%) and B1 (9.19%) > B3 (8.94%) > B2 (4.66%); the water contents decreased in the order A1 (2.99%) > A3 (2.19%) > A2 (1.09%) and B1 (2.30%) > B3 (1.87%) > B2 (1.09%). Moreover, a skid-mounted treatment technology for OBCs was proposed. The results can be a scientific guidance for the treatment and management of OBCs.

This paper investigates the capability of millimeter-wave (mmWave) channel sounders with phased arrays to perform super-resolution parameter estimation, i.e., determine the parameters of multipath components (MPC), such as direction of arrival and delay, with resolution better than the Fourier resolution of the setup. We analyze the question both generally, and with respect to a particular novel multi-beam mmWave channel sounder that is capable of performing multiple-input-multiple-output (MIMO) measurements in dynamic environments. We firstly propose a novel two-step calibration procedure that provides higher-accuracy calibration data that are required for Rimax or SAGE. Secondly, we investigate the impact of center misalignment and residual phase noise on the performance of the parameter estimator. Finally we experimentally verify the calibration results and demonstrate the capability of our sounder to perform super-resolution parameter estimation.

The 3.5 GHz and 28 GHz bands are both very important for the fifth-generation (5 G) wireless communication system. To model their propagation characteristics and study their channel properties, we conduct measurements at these two bands in indoor and outdoor scenarios. The measured bandwidths at 3.5 and 28 GHz are 100 and 400 MHz, respectively. To make a fair comparison, the measurement results at 28 GHz are divided into four groups with bandwidths from 100 to 400 MHz. This is also helpful to study the effect of bandwidth on the channel properties, especially numbers of clusters and their growth rate. We choose the Saleh-Valenzuela (S-V) model to analyze the wireless channel. Its cluster-based property is very suitable to describe the power delay profiles (PDPs) in our measurement. To maintain the time continuity of multipath components (MPCs) during the clustering, we propose a new heuristic cluster algorithm. Based on the clustering results, we obtain the channel parameters, i.e., the number of clusters, inter-cluster interval, intra-cluster root mean square (RMS) delay spread, cluster decay factor, and ray decay factor. From the comparative study, we can find that the rays suffer a larger attenuation at 28 GHz than at 3.5 GHz. Increasing bandwidth can increase the ray decay factor. But the effects of frequency on the cluster decay rate are different in indoor and outdoor scenarios. The cluster decay rate is smaller at 28 GHz in the indoor scenario.

With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high data rates and low latency for future services. A wireless propagation channel is the transmission medium to transfer information between the transmitter and the receiver. Moreover, channel properties determine the ultimate performance limit of wireless communication systems. Thus, conducting channel research is a prerequisite to designing 6G wireless communication systems. In this paper, we first introduce several emerging technologies and applications for 6G, such as terahertz communication, industrial Internet of Things, space-air-ground integrated network, and machine learning, and point out the developing trends of 6G channel models. Then, we give a review of channel measurements and models for the technologies and applications. Finally, the outlook for 6G channel measurements and models is discussed.

Machine learning has recently drawn much attention for a variety of applications, thanks to its good performance in identification, recognition, and regression problems. One such important application is V2V communication propagation channel research. In this article, the challenges and opportunities of machine-learning-based data processing techniques for evaluation of V2V channel measurements are presented. This article reviews some state-of-the-art applications including identification of channel line-of-sight situations, tracking of MPCs, and MPC clustering. The data obtained with these methods form, inter alia, the basis for accurate channel models. Furthermore, some challenges of machine-learning-based data processing for V2V channel research are discussed as basis for future studies.

In this work, a silicon-on-insulator (SOI) lateral diffused MOSFET (LDMOS) incorporated with sidewall field plate (SEP) is presented and investigated using three-dimensional numeric simulation. A new additional electric field peak is formed, due to the compound field plate established along the n-drift region. The lateral surface electric field can be modulated, which enhances the breakdown voltage. Meanwhile, the doping concentration of n-drift region is increased, which decreases the specific on-resistance. Compared with the superjunction LDMOS, a 23.7% increase in the breakdown voltage and a 21.7% decrease in the specific on-resistance are obtained in the SFP-LDMOS device.

In this paper, a new silicon-on-insulator superjunction lateral double-diffused MOSFET (SOI SJLDMOS) with a p-trench layer and stepped buried oxide, is investigated using 3D numerical simulation. The p-trench layer and stepped buried oxide distinguish it from a conventional SOI SJLDMOS. The etched buried oxide layer, with its stepped buried -oxide structure, which facilitates a more even electric field distribution via the electric field modulation effect, increases the breakdown-voltage (BV). Furthermore, the p-trench layer improves the doping concentration through compensation depletion, which further decreases the specific on-resistance (Ron,sp). The simulation indicates that the new device has a higher BV (increased by 29%) than the conventional SOI SJLDMOS. At the same time, Ron,sp decreases by 20% for the on-state for a given drift-region length.

Environmental modeling errors have significant influence on the accuracy of ray tracing (RT) based channel modeling method. The aim of this paper is to provide reference for determining the appropriate accuracy of indoor databases to achieve prediction results within tolerance. Therefore in this paper, we discuss the influence of modeling errors on the RT-based channel modeling accuracy for millimeter-wave frequency bands. Different from the previous work, our discussion mainly foucus on the indoor environments and try to analyze the relationship between the channel parameters including received power, delay spread (DS), angle spreads (AS) and the types of scatterers. Simulation results show the RT results are more sensitive to the geometric errors caused by the room boundary in the line-of-sight (LOS) case while indoor scatterers have a greater impact in the non-LOS (NLOS) case. Additionally, AS is more sensitive to geometric errors of environment than DS. These results have guiding significance for channel modeling and simulation work using RT.

Radio wave propagation in a waveguide-like structure scenario performs a specific path loss characteristic which is termed as waveguide effect. In this paper, we analyze the path loss characteristics in a waveguide-like structure scenario based on channel measurements at 28 GHz. First, three different modeling methods, including the waveguide approach, ray-tracing approach, and empirical approach, are compared and validated with the measurement results. This study suggests that the empirical dual-slope channel model can give a more accurate prediction of path loss with minimum root mean square error (RMSE). Secondly, the influence of the geometry position of antennas on path loss is investigated by using the dual-slope path loss model. Comparative analysis results reveal that a stronger waveguide effect exists when placing the antenna close to the wall and when having antenna height difference, horizontal measurements at different line-of-sight distances confirm the analysis that waveguide effect exists after the breakpoint.

In this paper, we propose a novel 3D scenario information based channel modeling method with deep learning for Vehicular-to-infrastructure (V2I) communications. Specifically, the vehicular scanning sensors are utilized to capture the point cloud information of 3D scenario directly, and then the channel characteristics are generated and mapped with the 3D scenario information by deep learning network. Benefited from the above modeling framework, the complexity of environment reconstruction and geometric calculation can be reduced greatly. The simulation results show that the prediction precision of reflection point by deep learning has significant impact on the modeling accuracy. By some efficient scenario information extraction operations, the proposed method can realize more than 95% channel modeling accuracy with much lower complexity.

Injectors are key pieces of equipment for chemigation systems, and their hydraulic performance has a significant effect on chemigation systems and crops. In order to investigate the influence of different working parameters on hydraulic performance for a water-powered proportional injector (PI), three key parameters of inlet and injection flow rate were researched using a one-factor experimental design method. The regression equations between different factors and response variables were established through a response surface method based on one-factor experimental results. Lastly, a mathematical model of the actual injection ratio was established. Some experiments under different, randomly selected parameter combinations were carried out to verify the prediction precision of the mathematical mode. The results showed that the injection flow rate increased first within the differential pressure of 0.05 to 0.10 MPa and then tended towards stability with increasing differential pressure. The injection flow rate decreased by increasing the viscosity and the change in the injection flow rate was small enough when the viscosity was greater than 500 mPa&middot, s. The impact factors, in order of significance, for inlet flow rate were differential pressure, viscosity of injection liquid and setting injection ratio. The impact factors, in order of significance, for injection flow rate were viscosity of injection liquid, setting injection ratio and differential pressure. The regressive model for predicting the actual injection ratio was validated using an experiment and the relative deviation between calculated value and tested value was less than 5.98%, which indicated that the mathematical model had high credibility.

The aim of this study is to improve the water distribution uniformity of a vertical impact sprinkler and explore the design method of the drive spoon blades. The width of straight blades (h1), the width of curved blades (h2) and number of blades (s) were chosen as the experiential variables. The suitable ranges of three variables for response surface method were determined initially by one-factor experimental design method, and 17 different drive spoons were designed according to response surface methodology. The results showed that in the one-factor experimental condition, the CU (Christiansen’s uniformity coefficient) values first increased and decreased slightly when h1 exceeded 3 mm with the increase of h1 within the variation range of the experimental factor. The CU values firstly increased and then decreased with the increase of h2. The CU values decreased rapidly when s was less than 3 or greater than 6. The relationship between CU values and h1, h2 and s was established using response surface methodology. The p-values for h1, h2 and s were 0.0359, 0.0092, 0.0212, and all of the selected factors were significant on CU. The order of parameters affecting CU were h2, h1 and s. The ideal parameters for the drive spoon blades were h1 = 6 mm, h2 = 4 mm, and s = 3. CU was greatly improved after the optimization of structure for the drive spoon blades, which increased to 87.96% from 73.12%. After optimization, the application rates within 1 to 5 m were improved and increased from 10% to 15% with an average of 10.7% under different operating pressures. The maximum application rates decreased from 9.3, 9.3, 9.4 and 8.4 mm·h−1 to 8.5, 8.4, 8.5 and 7.9 mm·h−1 with operating pressures of 300, 400, 500 and 600 kPa, respectively. The maximum application rates in the overlap area were decreased from 18, 16, 16 and 15 mm·h−1 to 16, 14, 14 and 12 mm·h−1 with operating pressures of 300, 400, 500 and 600 kPa, respectively.

Investigations of stabilized/solidified sediment (S/S sediment) by simulated field-construction processes (crushing and filling) are fundamental to evaluating the potential reuse as fill materials. A series of tests were conducted on the samples prepared from S/S sediment grains (SG), which was obtained by crushing the cement treated sediment. By sampling the SG with different field-curing durations (t1: 28, 35, 56 and 98 days) and measuring them by unconfined compressive strength (UCS) tests, the effect of t1 on the UCS was investigated. By continually curing the samples prepared from the SG with 28 field-curing days in laboratory for an additional 7, 28, 35 and 70 days (t2) and subjecting them to UCS and tank leaching tests with different ambient (leachate) pH values (1, 4, 7, 10 and 14), the effect of t2 and ambient pH was evaluated. Increasing t1 and t2 was found to significantly influence the strength of SG, which highlights the importance of an appropriate curing period. The releases of the metals (As, Cr, Cu, Zn, Pb, Ni, and Hg) in the SG exhibited a strongly pH-dependence but less correlation with t2. Neutral conditions (pH = 7) offered the best immobilization capacity for Cu; As, Cr, Ni and Zn exhibited the lowest release at pH = 10; the release of Pb decreased moderately with increasing pH. The S/S sediment complied with the acceptance criteria in terms of metal release and can be regarded as an environmentally friendly fill material. The results highlight the technical feasibility of stabilized sediment recycling in aquatic environment projects.

The development of 5G promotes the interconnection of all things. And Industrial Internet of Things (IIoT) have attracted much attention because of its broad application value. In this paper, we present measurements that were conducted at 4.9 GHz and 28 GHz for comparing the channel delay spread in an indoor industrial scenario. Based on the measured data, the delay spread is compared at different frequencies. It can be found that the root mean square (RMS) delay spread (DS) is well fitted by a lognormal distribution. Besides, the mean RMS DS at 28 GHz is much smaller than that at 4.9 GHz. Compared with 3GPP standard, we find that the mean RMS DS in the indoor industrial scenario is much larger than that in the traditional indoor office scenario. At last, the effects of the TX-RX distance and antenna heights on RMS DS are investigated. By modeling DS as a function of the TX-RX distance, it is found that in the line-of-sight (LOS) scenario, RMS DS increases linearly with the TX-RX distance, both at 4.9 GHz and 28 GHz. By setting different antenna heights, it is found that in non-line-of-sight (NLOS), the mean RMS DS in the clutter-elevated scenario is 12 ns smaller than that in the clutter-embedded scenario. These results can provide insights into the design of IIoT systems.

In this paper, a Gamma Beta Mixture Model (GBMM) is proposed to cluster channel multipath components (MPCs) where the gamma distribution is utilized to fit the delay data and angle data is fitted with beta distribution. We utilize the expectation-maximization (EM) algorithm to get the optimal GBMM parameters. Specially, in the M step of the EM algorithm, the Newton-Raphson method is utilized to optimize the GBMM parameters since we could not get closed solutions. To verify the clustering effect, an outdoor-to-indoor (O2I) measurement activity at 3.5 GHz was conducted. Simulation results based on real channel measurement data indicate that, compared with Gaussian mixture model (GMM), GBMM has better clustering performance.

To design fifth-generation (5G) millimeter-wave (mm-wave) vehicle-to-vehicle (V2V) communication systems for the future intelligent transportation system (ITS), the knowledge of channel characteristics in various vehicular communication environments is essential. This paper present a channel measurement in a common scene, a typical underground garage entrance at 28 GHz, and analyze the channel characteristics, including path loss, shadow fading, and root mean square (RMS) delay spread (DS). Statistical results of these channel characteristics are presented. We compare the channel characteristics based on our measurement with those of the existing results. Furthermore, we investigate the change trend of the RMS DS along the garage entrance, and find that the special structure of the garage entrance has a apparent effect on the RMS DS. These results are helpful to design the physical layer for the future V2V communication systems.

The industrial Internet of Things (IIoT) has benefited from the fifth-generation (5G) wireless network and is providing much-needed impetus to stimulate economic growth. Because of a very wide frequency range of 5G wireless network, the microwave and millimeter wavebands will constitute hybrid wireless communication systems, thus it is essential to have a thorough knowledge of the propagation characteristics in industrial scenarios at different frequencies. In this paper, we provide a comparative study of channel characteristics, i.e., the path loss and Ricean K-factor, at 4.9 and 28 GHz in indoor factory environments based on channel measurements. The analysis results consistently indicate that rich reflection paths occur in industrial scenarios, relative to indoor office environments. Also, severer attenuation and lower multipath richness occur at 28 GHz. Meanwhile, the impact of antenna height on the propagation channel is studied. These results are helpful for the frequency band selection and antenna height design of IIoT systems.

The millimeter-wave (mm-wave) band is of great importance for the future wireless communication systems. Studies on millimeter-wave channels are of great importance to mmwave wireless technologies. In this paper, we investigate the 3-D clustering phenomenon of mm-wave propagation at 28 GHz in a conference room. The results including cluster propagation mechanisms, the relationship between the clusters and the physical environment, and intra-cluster statistics are presented. Results show that the cluster propagation mechanisms are influenced by the room geometry. The last hop of sub-paths in the same cluster may locate on different objects existing in the environment. Besides, cluster statistics including intra-cluster delay spread (DS), angle spread (AS), and sub-paths number are discussed. Their logarithms fit normal distributions well. These results could help extend and justify current research on mm-wave channels. Moreover, a ray-tracing (RT) tool is used to emulate the measurements and similarity results are presented and analyzed. Excellent agreements between the measurement and simulation verify the feasibility and accuracy of RT simulation for studying the cluster characteristics.

Fifth-generation (5G) wireless networks are expected to operate at both microwave and millimeter-wave (mmWave) frequency bands, including frequencies in the range of 24 to 86 GHz. Radio propagation models are used to help engineers design, deploy, and compare candidate wireless technologies, and have a profound impact on the decisions of almost every aspect of wireless communications. This paper provides a comprehensive overview of the channel models that will likely be used in the design of 5G radio systems. We start with a discussion on the framework of channel models, which consists of classical models of path loss versus distance, large-scale, and small-scale fading models, and multiple-input multiple-output channel models. Then, key differences between mmWave and microwave channel models are presented, and two popular mmWave channel models are discussed: the 3rd Generation Partnership Project model, which is adopted by the International Telecommunication Union, and the NYUSIM model, which was developed from several years of field measurements in New York City. Examples on how to apply the channel models are then given for several diverse applications demonstrating the wide impact of the models and their parameter values, where the performance comparisons of the channel models are done with promising hybrid beamforming approaches, including leveraging coordinated multipoint transmission. These results show that the answers to channel performance metrics, such as spectrum efficiency, coverage, hardware/signal processing requirements, etc., are extremely sensitive to the choice of channel models.

Applying fertilizer through drip irrigation system is a very important method to save fertilizer and labour. Three manifold layouts (water supply in one end for transversal drip tapes (M1), water supply in both ends for transversal drip tapes (M2) and water supply in one end for longitudinal drip tapes (M3)) and four different fertilizer solution concentrations (50.00 g L−1 (C1), 66.67 g L−1 (C2), 100 g L−1 (C3) and 200 g L−1 (C4)) were selected to investigated the effect of the manifold and concentration on water fertigation uniformity. Results showed that the emitter at the extreme end of the manifold needed more time to clean the rudimental fertilizer in the drip tapes. The minimal flushing time increased from 8 to 13, 4 to 7 and 7 to 12 min with increasing the fertilizer concentration from C1 to C4 for M1, M2 and M3, respectively. The drip irrigation system needed more time for flushing to reduce the risk of emitter clogging when a higher fertilizer solution concentration was applied. In order of performance, M2 had the highest water and fertilizer uniformity, followed by M3 and lastly by M1. The fertilizer solution concentration had no significant effect on water distribution. However, it had a significant effect on fertilizer distribution. The mass of the applied fertilizer for the drip tapes close to the inlet increased with increasing fertilizer solution concentration from C1 to C4, which indicated that higher fertilizer solution concentration can result in lower fertilizer distribution uniformity. There was a significant effect of the manifold layout on water uniformity. The fertilizer concentration and the interaction between manifold layout and concentration had no significant effect on the water uniformity. Similarly, both the manifold layout and concentration had a significant effect on fertilizer uniformity. The interaction between manifold layout and concentration had a significant effect on the Christiansen’s uniformity (CU) and distribution uniformity (DU) for fertilizer, whilst, a significant effect on emission uniformity (EU) was not found. The manifold layout and fertilizer solution concentration should therefore be considered in the design and operation of fertigation system.

Pervaporation membranes made from polyethersulfone (PESU), polyphenylsulfone (PPSU), polytrimethylphenylethersulfone (T-PESU) and hydrophilic PESU-co-Pluronic (H-PESU) polymers were evaluated for dehydration of ethanol and methanol. Fundamental characteristics of pore structure, free volume, d-spacing, water contact angle, water and ethanol uptakes were investigated and correlated with their dehydration performance. The H-PESU membrane shows the best ethanol dehydration performance due to its synergetic combination of the strengths from both rigid hydrophobic PESU and flexible hydrophilic Pluronic moieties. It has the highest water permeability of 0.322 mg m−1 h−1 kPa−1 which is 2–6 times higher than other three membranes because the hydrophilic Pluronic moiety may form special water transport channels. It also has a comparable mole-based selectivity of 685 due to the rigid hydrophobic PESU moiety that prevents the membrane from uncontrolled swelling. Long-term tests evidence the operating stability of both H-PESU and PESU membranes. In addition, the methanol dehydration performance of these membranes is superior to the other reported polymeric membranes. The water in the permeate can be concentrated to 86.8%. These promising preliminary results suggest that these polyarylether (PAE) membranes have great potential for ethanol and methanol dehydration.

The proportional injector is commonly used in agricultural chemigation due to its relatively high injection ratio. A major challenge with the proportional injector is related to its dependence on differential pressure, which is significantly influenced by changes in the viscosity, and setting injection ratio. A series of experiments were conducted to investigate the influence of differential pressures, solution viscosities, and setting injection ratios on the inlet and injection flow rates of a D25RE2 proportional injector. A mathematical model was developed to represent the hydraulic performance of this proportional injector. Finally, the mathematical model was verified using four different kinds of chemicals (humic acid, urea ammonium nitrate 32% N, fosthiazate, and colza oil). The inlet flow rate increased significantly with increasing differential pressure and decreased with increasing setting injection ratio. Results showed that the highest operating differential pressure should not be greater than 0.15 MPa for the D25RE2 proportional injector. The inlet flow rate gradually decreased with increasing viscosity, and a quadratic function relationship was derived between the inlet flow rate and the viscosity. The injection flow rate decreased with increasing viscosity. However, the viscosity had a slight influence on the injection flow rate when it was lower than 20 mPa·s. Mathematical models for calculating the inlet and injection flow rates with the influence of viscosity were developed, respectively. The coefficient of determination and the root mean square error (RMSE) for inlet flow rate calculation model were 0.8316 and 143.36 kg h-1, respectively. The coefficient of determination and the RMSE for the injection flow rate calculation model were 0.9706 and 0.9520 kg h-1, respectively. The calculating formula of inlet flow rate had a satisfactory accuracy under low differential pressure and high setting injection ratio. The calculating formula of the injection flow rate had a good accuracy, which is useful for calculating the injection flow rate when injected with different kinds of solutions. The average deviations between calculated and experimental injection flow rates with injection ratios of 0.2%, 1.2%, and 2% were obtained as 4.96%, 4.66%, and 4.1% respectively, which indicated that the average deviations decreased with increasing setting injection ratio. Results from this study are useful for both designers and users to effectively manage agricultural chemigation system with the proportional injector. Keywords: Agriculture, Chemigation, Proportional injector, Hydraulic performance.

The removal of boron compounds from aqueous systems is receiving worldwide attention because boron contaminations in various water sources are rising in recent years. Boron toxicities to living beings and harmfulness to semi-conductor manufacturing are increasingly accessed and recognized by researchers. A wide range of technologies has been unveiled for boron removal. Among them, membrane technologies for boron removal have come to the scientific spotlight. Especially, some emerging membrane processes were devised recently, e.g. forward osmosis (FO), polymer enhanced ultrafiltration (PEUF), membrane adsorptive filtration (MAF), membrane distillation (MD), etc. Most of them were demonstrated with many competitive edges compared to the traditional methods. This review will present a comprehensive summary of the recent advances in membrane-based deboronation technologies from the perspectives of membrane materials, membrane fabrication and system design. Comparisons between various membrane processes and prospects of each technology will be covered. The information may provide inspiration for future researchers and pave the way to develop effective and efficient deboronation technologies for the years to come.

The decontamination of selenium (Se) and arsenic (As) from aqueous environments has been an emerging area for membrane technology. They are difficult to be removed because of various oxidation states, range of toxicity and solubility. In this work, three water stable zirconium metal-organic framework (MOF) UiO-66 nanoparticles with different diameters, i.e., 30, 100 and 500 nm, have been synthesized and incorporated into the selective layer to form thin-film nanocomposite (TFN) membranes. These membranes were tailored to remove the Se and As concurrently. Comparing to the thin-film composite (TFC) membranes, the TFN membranes exhibit higher pure water permeability (PWP) and rejections for both pollutants due to their smaller pore size and higher hydrophilicity. In addition, the TFN membrane comprising 30 nm UiO-66 has the best performance among the three TFN membranes. The effects of particle loading have also been investigated for the 30 nm UiO-66 TFN membranes. The TFN membrane containing 0.15 wt% UiO-66 has the highest PWP of 11.5 LMH/bar and remarkable rejections of 96.5%, 97.4% and 98.6% toward SeO 3 2- , SeO 4 2- and HAsO 4 2- , respectively. Higher rejections are also achieved in the concurrent removal of Se and As. Additionally, the TFN membrane exhibits robust long term stability. To our best knowledge, this is the first work to study the particle size and loading effects of UiO-66 particles in the selective layer of TFN membranes for Se and As removal. The results achieved in this work may provide promising insights for the development of next generation NF membranes with superior performance.

Thin film composite membranes (TFC) consisting of an ultra-thin polyamide layer made from interfacial polymerization remain to be of paramount importance for seawater desalination. Incorporation of nanoparticles into the polyamide layer has produced thin film nanocomposite (TFN) membranes with better performance than traditional TFC membranes. However, challenges of defect formation with the introduction of nanoparticles need careful adjustments in order to surpass the trade-off relationship between permeability and selectivity. Here, we explored the influential effects of nanoparticles, solvent and surfactant treatments on the desalination performance of TFN membranes under 55 bar using 35,000 ppm NaCl as the feed at 25 °C. TFN membranes with various loadings of polyhedral oligomeric silsesquioxane (POSS) and TiO2-SiO2 core-shell nanoparticles were fabricated. Surfactant treatment was performed in two different ways: membrane soaking and in-tank addition. Unexpectedly, the latter endows the membrane with an improved rejection without sacrificing its flux possibly due to the formation of a surfactant monolayer to heal defects in TFN membranes. The newly developed TFN-T membrane with the aid of synergic effects from nanoparticles, ethanol and surfactant post-treatments shows comparable performance to most commercial membranes. This work may provide useful insights to overcome the trade-off relationship between permeability and selectivity of TFN membranes for seawater desalination.

The service life and stability of the large cannon sprinklers depends on the stress distribution that occurs on the drive spoon caused by the impact force of the driving water jet. A simple theory of the forces caused by the impact of the water jet on the drive spoon was developed, and a three-dimensional (3D) model numerical simulation using computational fluid dynamics (CFD) was constructed. An experiment was carried out to verify the accuracy of the simple momentum-based theory and the numerical CFD simulations. The results showed a large deviation between the simulated and measured values under low pressure conditions, with a maximum deviation of 15.98%. However, the simulations had good accuracy under high pressure conditions. The difference between simple theory and experimental values also decreased with increasing working pressure when considering both horizontal and vertical components. The simple theory was adjusted by the use of correction factors that were regressed with working pressure using experimental data. The coefficient of determination of the correction factor expressions for both the horizontal and vertical components were 0.9799 and 0.9289 respectively. After adjustment of the simple theory, the calculated values of the vertical and horizontal impact forces were compared to the experimental values and had a difference

Construction of PVDF hollow fiber membranes with antifouling lumen surfaces is of great interest and significance for many industrial applications because the inside-out filtration mode allows good control over module hydrodynamics. For the first time, a zwitterionic polymer was immobilized on the lumen surface of a PVDF hollow fiber membrane via thermal-induced graft copolymerization with an objective to render the PVDF membrane antifouling. The graft copolymerization consists of two steps: ozone-assisted surface pre-activation and grafting of sulfobetaine methacrylate (SBMA). The grafting density and chain length were systematically optimized by manipulating the operational parameters, e.g. ozone treatment and grafting duration. The resultant membranes were studied with respect to their structure, morphology, ultrafiltration (UF) performance, while their fouling behaviors were evaluated by flux recovery ratio and the resistance-in-series model. In comparison to the pristine one, the composite membranes exhibited superior fouling resistance for a 2-h filtration of a 2.0 wt% bovine serum albumin (BSA) solution. Especially, the irreversible fouling-induced resistance was prominently reduced from 53% to 15% due to the outstanding hydration capacity of the polySBMA polymer. Consequently, the flux recovery ratio ( FRR ) increased significantly from 47% to 85%, suggesting the promising prospect of the zwitterion-grafted PVDF hollow fiber membranes for their antifouling properties. Most importantly, the improvement in antifouling was achieved without sacrificing flux or rejection efficiency. This work may provide useful insights about lumen surface nano-structuring of the inner-selective hollow fiber membranes.

This paper analyzes channel characteristics of millimeter-wave (mm-wave) at 39 GHz in indoor environments based on channel measurements in a conference room and a lobby. Statistical results of channel large-scale fading characteristics including path loss (PL), shadow fading (SF) and small-scale fading characteristics like K-factor, root mean square (RMS) delay spread (DS) and RMS angular spread (AS) are presented. Furthermore, effects of different environments on the channel characteristics are investigated. In addition, differences between our measurement-based channel model parameters and those of the 3GPP channel model are discussed. The comparative analysis results reveal that channel characteristics are highly related with the measured environments; a complex environment with abundant reflectors has large RMS DS and RMS AS but small K-factor due to rich scattering.

[EN] The venturi tube is a special kind of pipe which has been widely applied in many fields. Cavitation is one of the most important research issues for the Venturi tube. Hence, three key structural parameters (contraction angle, diffusion angle and contraction ratio) were selected to investigate the influence of different factors on cavitation characteristics, using the computational fluid dynamics (CFD) method. A series of experiments for measuring the relationship between differential pressure and flow rate were carried out to verify the accuracy of the simulation method. Results showed that the simulation results had a high accuracy and the numerical method was feasible. The average vapor volume fraction of cross-section from the throat in the axial direction increased with increasing contraction angle. The cavity length increased with increasing contraction angle. The average volume fraction in the diffusion section rapidly decreased with increasing diffusion angle. The diffusion angle had no significant effect on the cavitation characteristics in the throat section and had a significant influence in the diffusion section. The average vapor volume fraction increased with decreasing contraction ratio. The contraction ratio had no significant effect on the cavity length under the same differential pressure. The average vapor volume fraction increased with decreasing contraction ratio. However, the variation in the throat section was less than the diffusion section. Under the same inlet and outlet pressure, the cavity lengths for different contraction ratios were basically the same, which indicated that the contraction ratio had no significant effect on the cavity length., This work was supported by the National Natural Science Foundation of China (51679109; 51609104), Natural Science Research Project of Jiangsu Higher Education Institutions (19KJB470014), Special Scientific Research Fund of Agriculture Public Welfare Profession of China (Grant No. 201503130), the Natural Science Foundation of Jiangsu Province (BK20170555).

Generally, propagation channels show significantly different characteristics for line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. Due to their good performance in classification problems, support vector machines (SVM) have been widely used for NLOS identification of propagation channels. In this paper, we investigate the impact of different kernel functions on the accuracy of SVM-based NLOS identification and validate the performance based on measured channel data. We find that a Gaussian kernel reduces the mis-identification rate by a factor 4 compared to a linear kernel, and also outperforms polynomial and sigmoid kernels.

With stringent regulations regarding the toxic ions selenium and arsenic on wastewater discharge, various industries such as coal mining and power generation are demanding more efficient and effective treatment methods to remove these two ions. Since the performance of commercially available thin film composite nanofiltration (NF) membranes reported so far has a great room for improvement, a thin-film nanocomposite (TFN) NF membrane comprising polyhedral oligomeric silsesquioxane (POSS) with high efficiency was developed for the concurrent removal of selenium and arsenic from aqueous solutions. The resultant NF membrane has a mean effective pore diameter of 0.65 nm, a molecular weight cutoff of 302 Da, and superior pure water permeability of 5.4 LMH/bar with notably high rejections of SeO32–, SeO42–, and HAsO42– toward 93.9%, 96.5%, and 97.4%, respectively. The TFN membranes also exhibit slightly higher rejection performance when a mixed ion solution separation test was conducted. To the best of our knowl...

In this paper, we propose an analytical model for the variable drift region width (VDRW) silicon-on-insulator lateral double-diffused MOS (SOI LDMOS) device. Using the proposed model, for example, the breakdown voltage 375 V of VDRW SOI LDMOS is obtained with a 18- $\mu \text{m}$ drift region length, while the average value of the surface electric field can reach 20.8 V/ $\mu \text{m}$ . A 3-D device simulator, Sentaurus, is used to investigate the performance of the VDRW structure. By analyzing the simulation results and the analytical values, it is proven that the proposed model can effectively optimize the doping profile and accurately forecast the breakdown voltage.

Nanofiltration (NF) membranes have been used previously for the recovery of dyes, salts, and water from textile wastewaters with high salinity. However, commercially available NF membranes have a high rejection for divalent salts (i.e., Na2SO4), substantially reducing the salt recovery and membrane flux when treating textile wastewater containing Na2SO4. In this study, a tight ultrafiltration membrane (UH004, Microdyn-Nadir) was proposed to fractionate the dye and Na2SO4 in the textile wastewater. The UH004 membrane with a molecular weight cutoff of 4700 Da provided complete passage of monovalent salts, with little rejection of Na2SO4. This significantly increases the filtrate flux that can be achieved with high-salinity wastewater since osmotic pressure and concentration polarization effects are minimized. Furthermore, the retention behavior of four different dyes was evaluated to determine the efficiency of this membrane process. This tight ultrafiltration membrane offered the high retention for direct dyes (i.e., direct red 80, direct red 23, and Congo red) and reactive blue 2. For instance, the UH004 membrane yielded >98.9% rejection for all of the dyes at a pressure of 4 bar even in the presence of 60 g L−1 Na2SO4. Subsequently, an ultrafiltration-diafiltration process was designed to separate a dye/Na2SO4 aqueous mixture with 98% desalination efficiency and greater than 97% dye recovery after 5 diavolumes. These results clearly demonstrate that tight ultrafiltration membranes can be a stand-alone alternative to NF membranes for the effective fractionation of dye and Na2SO4 in the direct treatment of high-salinity textile wastewater.

Two hyperbranched polymers, hyperbranched polyglycidol (HPG) and 2, 3-Dihydroxypropyl-hyperbranched polyethylenimine (Diol-HPEI), were synthesized and studied as polychelatogens for boron reclamation via a hybrid ultrafiltration process, with the objectives of evaluating the key factors for polymer–boron chelation and improving boron rejection efficiency. Their chemical structures were unveiled by FTIR and XPS analyses whilst molecular weights were carefully tailored in order to be fully retained by a commercial ultrafiltration (UF) membrane. The chelation capacity of the two polymers was compared under different operating conditions i.e., chelating temperature, polymer loading and pH. It appears that Diol-HPEI prominently outperforms HPG because the tertiary amine group may be more competent than the ether group in terms of their protonation capability. Eventually, a rejection of 66–91% was achieved with a Diol-HPEI polymer loading of 100 g per g boron in the pH range of 6.9–9.0. Besides, the effects of interfering ions, i.e., Na+, Mg2+, Cl− and SO 4 2 - on polymer–boron interactions were examined in the Diol-HPEI/boron solution at the neutral condition. Results reveal that divalent cations may exert more negative influence on boron rejection owing to the competition between them and boron to form complexes with chelating polymers. These findings may provide useful insights in design of efficient boron-chelating polymers.

Pervaporation has been regarded as a promising separation technology in separating azeotropic mixtures, solutions with similar boiling points, thermally sensitive compounds, organic–organic mixtures as well as in removing dilute organics from aqueous solutions. As the pervaporation membrane is one of the crucial factors in determining the overall efficiency of the separation process, this article reviews the research and development (R&D) of polymeric pervaporation membranes from the perspective of membrane fabrication procedures and materials.

The Lakange porphyry Cu–Mo deposit within the Gangdese metallogenic belt of Tibet is located in the southern–central part of the eastern Lhasa block, in the Tibetan Tethyan tectonic domain. This deposit is one of the largest identified by a joint Qinghai–Tibetan Plateau geological survey project undertaken in recent years. Here, we present the results of the systematic logging of drillholes and provide new petrological, zircon U–Pb age, and molybdenite Re–Os age data for the deposit. The ore-bearing porphyritic granodiorite contains elevated concentrations of silica and alkali elements but low concentrations of MgO and CaO. It is metaluminous to weakly peraluminous and has A/CNK values of 0.90–1.01. The samples contain low total REE concentrations and show light REE/heavy REE (LREE/HREE) ratios of 17.51–19.77 and (La/Yb)N values of 29.65–41.05. The intrusion is enriched in the large-ion lithophile elements (LILE) and depleted in the HREE and high field-strength elements (HFSE). The ore-bearing porphyritic granodiorite yielded a Miocene zircon U–Pb crystallization age of 13.58 ± 0.42 Ma, whereas the mineralization within the Lakange deposit yielded Miocene molybdenite Re–Os ages of 13.20 ± 0.20 and 13.64 ± 0.21, with a weighted mean of 13.38 ± 0.15 Ma and an isochron age of 13.12 ± 0.44 Ma. This indicates that the crystallization and mineralization of the Lakange porphyry were contemporaneous. The ore-bearing porphyritic granodiorite yielded zircon eHf(t) values between −3.99 and 4.49 (mean, −0.14) and two-stage model ages between 1349 and 808 Myr (mean, 1103 Myr). The molybdenite within the deposit contains 343.6–835.7 ppm Re (mean, 557.8 ppm). These data indicate that the mineralized porphyritic granodiorite within the Lakange deposit is adakitic and formed from parental magmas derived mainly from juvenile crustal material that partly mixed with older continental crust during the evolution of the magmas. The Lakange porphyry Cu–Mo deposit and numerous associated porphyry–skarn deposits in the eastern Gangdese porphyry copper belt (17–13 Ma) formed in an extensional tectonic setting during the India–Asia continental collision.

Nanofiltration (NF) membranes, especially loose NF membranes, trigger a growing interest for the fractionation of concentrated organic matters/salt mixtures in addition to the production of pure water. This study presents an in-depth characterization of two superhydrophilic loose NF membranes (Sepro NF 6 and 2A, Ultura). The physical characterization included the determination of the molecular weight cut-off (MWCO), pore size distribution, membrane morphology, surface charge, roughness and hydrophilicity. This was combined with a chemical characterization, i.e., by Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS), to determine the intrinsic membrane properties. The chemical characterization demonstrates that both Sepro NF membranes are poly(piperazineamide) based, showing the modification chemistry for the top layer through XPS measurement. Specifically, Sepro NF 6 and NF 2A membranes were found to have a superhydrophilic surface (contact angle for Sepro NF 6: 14.3±0.9°; that for Sepro NF 2A: 21.7±1.4°) with a low roughness, offering a potential advantage over conventional NF membranes in minimizing membrane fouling. Sepro NF 6 and NF 2A membranes had a mean effective pore size of 0.64±0.03 nm and 0.52±0.01 nm (corresponding to MWCOs of 862±80 Da and 493±53 Da), respectively. In terms of filtration performance, Sepro NF 6 showed a high permeability of 16.7 L m −2 h −1 bar −1 with 88.9% salt transmission for 0.01 mol L −1 NaCl solution, and a slightly lower permeability and salt transmission was obtained for Sepro NF 2A, which is desired for an effective fractionation of target organic matter/salt mixtures.

Artificial joint replacement is an effective surgical method for treating end-stage degenerative joint diseases, but peripheral bacterial infection of prosthesis can compromise the effect of the surgery. Herein, antibacterial effects of titanium dioxide nanotubes (TNTs) coated with polyhexamethylene guanidine (PHMG) were examined via in vitro and in vivo experiments. TNTs with a pore diameter 46.4 ± 5.9 nm and length of 300-500 nm for the slice and 650-800 nm for the rod were fabricated by anodization. Then, 3.46 ± 0.40 mg and 1.27 ± 0.28 mg of PHMG were coated onto the TNT slice and rod, respectively. In vitro studies of the release of PHMG showed that the antibacterial agent was released in two stages: initial burst release and relatively slow release. In vitro and in vivo antibacterial studies showed that the PHMG-loaded TNTs (PHMG-TNTs) had excellent antibacterial abilities to prevent bacterial infections. Clinical pathological analysis of rabbit femurs indicated that the implanted PHMG-TNTs had no apparent pathological changes. Real-time quantitative reverse transcription polymerase chain reaction analysis of the femur tissues around the implants showed that the expression of osteogenic-related genes, including runt-related transcription factor 2, osteocalcin, alkaline phosphatase, bone sialoprotein, bone morphogenetic protein 2 and vascular endothelial growth factor A, was significantly upregulated in the PHMG-TNT implanted group as compared to the other groups. Overall, these findings provide a promising approach for the fabrication of antibacterial and bone biocompatible titanium-based implants in orthopedics.

Summary Data-independent acquisition mass spectrometry (DIA-MS) is a powerful technique that enables relatively deep proteomic profiling with superior quantification reproducibility. DIA data mining predominantly relies on a spectral library of sufficient proteome coverage that, in most cases, is built on data-dependent acquisition-based analysis of the same sample. To expand the proteome coverage for a pre-determined protein family, we report herein on the construction of a hybrid spectral library that supplements a DIA experiment-derived library with a protein family-targeted virtual library predicted by deep learning. Leveraging this DIA hybrid library substantially deepens the coverage of three transmembrane protein families (G protein-coupled receptors, ion channels, and transporters) in mouse brain tissues with increases in protein identification of 37%–87% and peptide identification of 58%–161%. Moreover, of the 412 novel GPCR peptides exclusively identified with the DIA hybrid library strategy, 53.6% were validated as present in mouse brain tissues based on orthogonal experimental measurement., Graphical Abstract, Highlights • A virtual library is built for a selected protein family using deep learning models • The hybrid library strategy vastly deepens the coverage for the targeted protein family • About 53.6% of novel GPCR peptides identified with the DIA hybrid library are validated • Extend the strategy to deep mapping of multiple transmembrane protein families, Analytical Chemistry; Biological Sciences; Classification of Proteins; Proteomics

This article presents a wideband millimeter-wave power amplifier (PA) with a capacitive stability enhancement technique. It is composed of three differential cascode stages to attain high-power gain and large output power. To ensure the stabilization of the amplifier, a robust technique based on a series base capacitor is proposed and applied in each stage. Each capacitor creates a low-frequency zero to adjust the phase and amplitude responses of the differential cascode structure. As a result, the phase margin of the loop gain is increased remarkably. By adjusting the series base capacitors, the low-frequency zeros and gains of the three stages can be optimized. Therefore, the operating bandwidth is also extended. Meanwhile, a transformer-based four-path power combination network with a large current capacity is developed to further enlarge the output power. The circuit is demonstrated in a commercial $0.13~\mu \text{m}$ SiGe BiCMOS process. According to the measurement results, the PA obtains a saturated output power ( ${P}_{\text {Sat}}$ ) of 18.5 dBm and output referred 1-dB compression point ( ${\mathrm{ OP}}_{1\,\text {dB}}$ ) of 16.32 dBm at 77 GHz. The tested small-signal gain is 26.7 dB at 77 GHz. Its 3 dB gain bandwidth is beyond 21.5 GHz, which ranges from 68.5 to 90 GHz. The ${P}_{\text {Sat}}$ variation is less than 0.57 dB at the frequency range from 70 to 85 GHz. The measurement also shows the PA with the proposed technique is unconditionally stable over the entire frequency band. The chip area is only 0.684 $\text {mm}^{2}$ .

Millimeter-wave channel models are fundamental for evaluating the performance of technologies for 5G. In this paper, we present two kinds of millimeter-wave channel measurements, fixed point measurements and virtual measurements, in an indoor open office. A correlation sounder with a bandwidth of 600 MHz is used to carry out these measurements. Then, channel parameters, e.g., the path loss, shadow fading, root mean square (RMS) delay spread (DS), K-factor, delay-cluster number and angular spread, are extracted and modelled. These extracted models will enable the generation of an impulse response for the indoor hotspot environment. Differences between our measurement-based channel model parameters and the International Telecommunication Union (ITU) channel model are discussed. The impact of differences on capacity are investigated by simulations. We find that the ITU channel model is optimistic about capacity. These results can help researchers to use millimeter-wave channel models for indoor office scenarios when evaluating 5G performance.

This paper presents the wideband channel characteristics of 28 GHz in urban microcell (UMi) scenario based the measurement in Beijing. Both the omnidirectional-antenna-based measurement and the horn-antenna-based measurement are performed with bandwidth up to 800 MHz. The standard deviation of shadow fading ($\sigma_{SF}$) is studied and is compared with that value in standard protocol. Unlike traditional method, the $\sigma_{SF}$ is calculated with data captured in each single route in this paper. It is found that in a specific environment, the standard model obtained by traditional method overestimate the $\sigma_{SF}$ of this frequency band to a large extent both in line of sight (LOS) environment and non line of sight (NLOS) environment. In addition, the 3-Dimensional angle information is estimated with the space alternating generalized expectation-maximization (SAGE) algorithm. The angle spread of arrival (ASA) and the angle spread of departure (ASD) are investigated and the cluster characteristics at different rotation measurement sites are analysed. It is found that dimension of parameter space that used in clustering algorithm has a great impact on the clustering result of the recognizable multipaths.