A 4H-SiC trench IGBT with controllable hole-extracting path for low loss

A novel 4H-Si C trench insulated gate bipolar transistor(IGBT)with a controllable hole-extracting(CHE)path is proposed and investigated in this paper.The CHE path is controlled by metal semiconductor gate(MES gate)and metal oxide semiconductor gate(MOS gate)in the p-shield region.The grounded p-shield region can significantly suppress the high electric field around gate oxide in Si C devices,but it weakens the conductivity modulation in the Si C trench IGBT by rapidly sweeping out holes.This effect can be eliminated by introducing the CHE path.The CHE path is pinched off by the high gate bias voltage at on-state to maintain high conductivity modulation and obtain a comparatively low on-state voltage(VON).During the turn-off transient,the CHE path is formed,which contributes to a decreased turn-off loss(EOFF).Based on numerical simulation,the EOFFof the proposed IGBT is reduced by 89%compared with the conventional IGBT at the same VONand the VONof the proposed IGBT is reduced by 50%compared to the grounded p-shield IGBT at the same EOFF.In addition,the average power reduction for the proposed device can be 51.0%to 81.7%and 58.2%to 72.1%with its counterparts at a wide frequency range of 500 Hz to 10 k Hz,revealing a great improvement of frequency characteristics.

Robust Fingerprint Construction Based on Multiple Path Loss Model (M-PLM) for Indoor Localization

A robust radio map is essential in implementing a fingerprint-based indoor positioning system(IPS).However,the offline site survey to manually construct the radio map is time-consuming and labour-intensive.Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys.This paper presents a novel fingerprint interpolator using a multi-path loss model(MPLM)to create the virtual fingerprints from the collected sample data based on different signal paths from different access points(APs).Based on the historical signal data,the poor signal paths are identified using their standard deviations.The proposed method reduces the positioning errors by smoothing out the wireless signal fluctuations and stabilizing the signals for those poor signal paths.By consideringmultipath signal propagations from different APs,the inherent noise from these signal paths can be alleviated.Firstly,locations of the signal data with standard deviations higher than the threshold are identified.The new fingerprints are then generated at these locations based on the proposed M-PLM interpolation function to replace the old fingerprints.The proposed technique interpolates virtual fingerprints based on good signal paths with more stable signals to improve the positioning performance.Experimental results show that the proposed scheme enhances the positioning accuracy by up to 44%compared to the conventional interpolation techniques such as the Inverse DistanceWeighting,Kriging,and single Path LossModel.As a result,we can overcome the site survey problems for IPS by building an accurate radio map with more reliable signals to improve indoor positioning performance.

Statistical Model of Path Loss for Railway 5G Marshalling Yard Scenario

The railway mobile communication system is undergoing a smooth transition from the Global System for Mobile Communications-Railway(GSM-R)to the Railway 5G.In this paper,an empirical path loss model based on a large amount of measured data is established to predict the path loss in the Railway 5G marshalling yard scenario.According to the different characteristics of base station directional antennas,the antenna gain is verified.Then we propose the position of the breakpoint in the antenna propagation area,and based on the breakpoint segmentation,a large-scale statistical model for marshalling yards is established.

Channel Measurement and Path Loss Modeling from 220 GHz to 330 GHz for 6G Wireless Communications

Terahertz(THz)communication has been envisioned as a key enabling technology for sixthgeneration(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 multiplefrequencies 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.

Investigating path loss characteristics of UWB signals in vacancy indoor environment based on time-domain technique

The path loss analysis model based on 5 rays in vacancy indoor environment is proposed. The relationship between multipath overlapping and the path loss is analyzed mathematically. Time-domain technique is introduced to compute reflection coefficient in a very short time interval. A 5 rays path loss calculation method, which is satisfactory accurate, is developed. 5 typical environments are involved to analyze and generalize the common path loss characteristics in vacancy indoor environment. The simulation result shows that the path loss can be characterized as 3 zones with different path loss exponent as distance between transmitter and receiver increasing.

Intelligent Reflecting Surfaces Enabled Cognitive Internet of Things Based on Practical Pathloss Model

In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by sharing the spectrum with the primary network,the interference is introduced by the IoT devices to the primary access point(PAP)which profits from the IoT devices by pricing the interference power charged by them.A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers,but each reflected signal can be aligned with its own desired direction.Moreover,two transmission policies of the secondary network are investigated without/with a successive interference cancellation(SIC)technique.The signal-to-interference plus noise ratio(SINR)balancing is considered to overcome the nearfar effect of the IoT devices so as to allocate the resource fairly among them.We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks.For the proposed game,the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing.Numerical results are demonstrated to validate the performance of the theoretical derivations.

Efficient Routing Protection Algorithm in Large-Scale Networks

With an increasing urgent demand for fast recovery routing mechanisms in large-scale networks,minimizing network disruption caused by network failure has become critical.However,a large number of relevant studies have shown that network failures occur on the Internet inevitably and frequently.The current routing protocols deployed on the Internet adopt the reconvergence mechanism to cope with network failures.During the reconvergence process,the packets may be lost because of inconsistent routing information,which reduces the network’s availability greatly and affects the Internet service provider’s(ISP’s)service quality and reputation seriously.Therefore,improving network availability has become an urgent problem.As such,the Internet Engineering Task Force suggests the use of downstream path criterion(DC)to address all single-link failure scenarios.However,existing methods for implementing DC schemes are time consuming,require a large amount of router CPU resources,and may deteriorate router capability.Thus,the computation overhead introduced by existing DC schemes is significant,especially in large-scale networks.Therefore,this study proposes an efficient intra-domain routing protection algorithm(ERPA)in large-scale networks.Theoretical analysis indicates that the time complexity of ERPA is less than that of constructing a shortest path tree.Experimental results show that ERPA can reduce the computation overhead significantly compared with the existing algorithms while offering the same network availability as DC.

Path loss modelling and comparison based on the radio propagation measurement at 3.5GHz

Wideband IMT-Advanced mobile communication systems tend to operate in the high frequency bands due to a relatively large capacity available. Thus, Measurement and modelling methods of radio propaga- tion eharaeteristics are proposed for the field test of Chinese 4th generation （4G） trial system. The mea- surement system is established for 3.5GHz based on the sophistieated measurement instruments and the virtual instrument teehnology. The characteristic parameters of radio propagation sueh as path loss （PL） exponent and shadow fading standard deviation are extracted from measurement data, which result in the path loss model finally. The comparisons with other existing international models results validate our mea- surement in terms of path loss model. Based on the analysis of the existing extension model assumed for the microwave frequency at 3.5GHz, we find that the Stanford University Interim （SUI） model fits very well with the measurement result in the hotspot scenario, while the COST 231 model is closer to the mea- surement result in the suburban scenario. This result provides a measurement-based channel referenee for the development of the future IMT-Advanced systems in China.

Maximum Inner Product Method for Extracting the Path-Loss Parameters in Primary Transformer Substations

In order to deploy short-range wireless communication devices in the primary transformer substation, a Maximum Inner Product(MIP) Method is proposed to extract the path-loss parameters in 110 kV and 220 kV primary transformer substations. The maximum inner product of the testing data is calculated to find out the loss index n and the standard deviation σ, and then the pathloss models can be set up. By comparing the MIP with Minimum Mean Square estimation(MMSE) and Cumulative Sum(CUSUM), MIP can match the measured values best. In order to apply the MIP path-loss model, under the initial signal to noise ratio(SNR) at 5 dB and 10 dB, a ZigBee simulation system is constructed to validate the situation that bit error rate(BER) varies with distance. And the ZigBee devices with 5 units are tested in a 220 kV primary transformer substation. The result of the test proves that the path-loss model is accurate.

Path Loss Modeling: A Machine Learning Based Approach Using Support Vector Regression and Radial Basis Function Models

Path loss prediction models are vital for accurate signal propagation in wireless channels. Empirical and deterministic models used in path loss predictions have not produced optimal results. In this paper, we introduced machine learning algorithms to path loss predictions because it offers a flexible network architecture and extensive data can be used. We introduced support vector regression (SVR) and radial basis function (RBF) models to path loss predictions in the investigated environments. The SVR model was able to process several input parameters without introducing complexity to the network architecture. The RBF on its part provides a good function approximation. Hyperparameter tuning of the machine learning models was carried out in order to achieve optimal results. The performances of the SVR and RBF models were compared and result validated using the root-mean squared error (RMSE). The two machine learning algorithms were also compared with the Cost-231, SUI, Egli, Freespace, Cost-231 W-I models. The analytical models overpredicted path loss. Overall, the machine learning models predicted path loss with greater accuracy than the empirical models. The SVR model performed best across all the indices with RMSE values of 1.378 dB, 1.4523 dB, 2.1568 dB in rural, suburban and urban settings respectively and should therefore be adopted for signal propagation in the investigated environments and beyond.

Modified Ceiling Bounce Model for Computing Path Loss and Delay Spread in Indoor Optical Wireless Systems

This paper proposes modifications to the tradional Ceiling Bounce Model and uses it to characterize diffuse indoor optical wireless channel by analyzing the effect of transceiver position on signal propagation properties. The modified approach uses a combination of the tradional ceiling bounce method and a statistical approach. The effects of different transmitter-receiver separations and height of the ceiling on path loss and delay spread are studied in detail.

Characterization and Modeling of Large-Scale Fading for Radio Propagation in Rwanda

Radio links are extensively used for voice and data communications at long distance. We analyze the radio propagation parameters that affect the received signal level on radio links in Rwanda and we determine the best path loss model for prediction of the received signal level. Various models of propagation and the mathematical expressions of path loss are described here in order to come to the prediction of those propagation effects. By analyzing data collected for two links of MTN Rwanda: Gahengeri-Kibungo and Gahengeri-Jali, we find that the best predicting model is the normal distribution.

Propagation Path Loss Models at 28 GHz Using K-Nearest Neighbor Algorithm

In this paper,we develop and apply K-Nearest Neighbor algorithm to propagation pathloss regression.The path loss models present the dependency of attenuation value on distance using machine learning algorithms based on the experimental data.The algorithm is performed by choosing k nearest points and training dataset to find the optimal k value.The proposed method is applied to impove and adjust pathloss model at 28 GHz in Keangnam area,Hanoi,Vietnam.The experiments in both line-of-sight and non-line-of-sight scenarios used many combinations of transmit and receive antennas at different transmit antenna heights and random locations of receive antenna have been carried out using Wireless Insite Software.The results have been compared with 3GPP and NYU Wireless Path Loss Models in order to verify the performance of the proposed approach.

基于RFID的医疗设备远程管理系统设计

为提高医院内设备定位精度,设计基于RFID的医疗设备远程管理系统。通过阅读器、电子标签和处理器组成RFID节点,引入AS3992芯片作为核心芯片,实现数据处理和编码,执行远程指令。采用自由空间传播模型计算路径损耗产生值,通过三角定位数学方法计算待定标签位置,采用RFID定位方法确定标签的最近邻居,实现医疗设备的远程定位。实验结果表明,在没有障碍物的情况下,所提系统设备定位误差少于1 m,在有障碍物的情况下,定位误差在2 m左右,证明所提出系统定位准确性较高,满足系统的设计需求。

全产业链视角下江苏省推进节粮减损的现实困境与纾解对策

粮食安全关乎国运民生,然而当前粮食损失和浪费问题严峻,维护粮食安全必须坚持开源与节流并重。在全产业链视角下,剖析了江苏省粮食产业存在着由于自然灾害和病虫害增加、绿色储粮标准化和物流现代化水平有待提高、粮食过度加工、节粮意识淡化等原因导致的粮食损失与浪费问题,探讨了生产源头、仓储物流、加工利用、宣传教育等各环节节粮减损的具体实施路径,提出加强标准体系建设、科技创新引领、强化应急管理、凝聚实施合力等对策建议。

极低频电流场透地通信路径损耗建模与分析

针对水平方向地电极电流场无线强穿透信息传输需求,研究了基于极低频水平双电极电流场信道传输特性。考虑到电极半径、电极入土深度、电极间距、发射信号频率和信号传输距离等参数对透地(Through-The-Earth,TTE)通信传输性能的影响,建立了地电极电流场TTE通信路径损耗模型,分析了各参数对路径损耗的影响,确定了信号传输最佳工作参数。根据选定参数搭建了极低频电流场TTE通信系统,在200 m和400 m通信距离下测试了3~10 Hz信号的路径损耗,通过试验数据与仿真结果对比分析验证了模型的准确性。

采动含水层生态功能修复:概念内涵、理论与技术框架

针对我国保水采煤研究现状及煤矿区采损生态修复的技术需求,提出应开展采动含水层生态功能修复研究,并将其纳入绿色开采技术体系中。在充分阐述采动含水层生态功能修复概念与内涵的基础上,构建了以采动含水层失水流动规律及水径流阻隔关键技术为主的理论与技术框架,分析了当前相关研究进展与未来攻关方向。含水层的损伤失水与生态功能退化本质源于采煤引起的岩层运动与裂隙发育,应在充分掌握含水层失水机制与规律的基础上对其开展生态功能修复理论与技术研究。深入揭示含水层失水路径分布与水流动力耗散规律,将失水流量集中分布的采动影响区作为重点修复的靶区,合理运用“边采边修”、“采后再修”等方式实施水流通道封堵与修复。同时,应充分利用采动岩体裂隙自修复机制及其引起的含水层自恢复效应,开展采动含水层生态功能引导修复研究与实践;基于水-气-岩相互作用产生化学沉淀促进导水裂隙自修复的降渗机理,提出了向含水层下方裂隙岩体中灌注可与地下水产生化学沉淀的修复试剂,以诱导沉淀物在裂隙中吸附-固结并封堵通道的含水层生态功能修复技术路径。在此基础上,阐述了利用铁/钙质化学沉淀进行导水裂隙修复降渗的研究现状,提出未来应重点研究形成利于不同类型导水通道高效封堵的化学沉淀诱导生成对策。研究可望为西北部生态脆弱矿区煤炭开采地下水保护与生态修复提供参考。

基于手机信令HMM轨迹映射的交通方式识别算法

为解决手机信令数据稀疏性限制和重构轨迹特征提取与融合能力不足问题,提出一种出行轨迹重构与多源特征融合的交通方式精准识别算法。构建刻画基站信号传播路径损耗与信号强度的无线信号损耗模型,利用隐马尔可夫模型(hidden markov model,HMM)将手机信令轨迹由基站序列重构为路段节点序列,提出基于无线信号传播隐马尔可夫模型(wireless signal propagation hidden markov model,WP-HMM)的出行轨迹重构方法,用以描述信号强度与距离作用关系。基于出行重构后的轨迹,结合路段类型特征,提出了时空标准化相似性度量算法,以融合导航轨迹特征,并构建了基于随机森林(random forest,RF)的交通方式识别算法。实证分析表明:通过出行轨迹的重构,模型的平均识别精度提高了8%以上,且对新样本具有优异的泛化能力;相较于现有方法,时空标准化相似性度量算法能更准确捕捉轨迹间的移动模式;在不同环境下的轨迹识别中,模型在郊区区域的表现显著高于城区。所提算法在大规模手机信令数据的出行方式识别领域具有重要的应用价值。

蜂窝车联网侧行链路信道测量与分析

蜂窝车联网侧行链路接口(PC5)采用终端到终端直接通信的形式,因其通信延迟低、传输容量大和传输可靠性高的特点而具备广阔的科研和工程前景。为了实测蜂窝车联网侧行链路信道特性,使用具有PC5接口的车载板卡在城市道路进行了通信测量工作,并依据测量结果从信道特征对PC5接口信道进行了分析。分析了通信收包时延随距离和信噪比变化的特征,将实测参考信号接收功率值与自由空间和双射线两种路径损耗经验模型及对数距离和双斜率两种路径损耗拟合模型的预测值进行了对比,并引入了四种相关性分析算法,从数值偏移量、线性相关程度和几何形态相似度等角度分析了模型预测值与实测数据的关联性,最终验证了双斜率路径损耗模型最适合表征PC5接口通信信道在城市环境下的衰落特征,基于该模型测算得到的路径损耗指数和阴影衰落方差也进一步说明此模型能够更好地结合实验环境表征信道特性。