Unified Bandwidth Scheduling in Centralized Fixed Access Network(C-FAN)

Time Division Multiplexing-Passive Optical Networks(TDM-PONs)play a vital role in Fiberto-the-Home(FTTH)deployments.To improve the service quality of home networks,FTTH is expanding to the Fiber-to-the-Room(FTTR)scenario,where fibers are deployed to connect individual rooms(i.e.,Fiber In-premises Network(FIN)in the ITU-T G.9940 standard).In this scenario,a point-to-multipoint(P2MP)fiber network is deployed as FTTR FIN to offer gigabit access to each room,which forms a two-tier cascaded network together with the FTTH segment.To optimize the capacity utilization of the cascaded network and reduce the overall system cost,a centralized architecture,known as Centralized Fixed Access Network(C-FAN),has been introduced.C-FAN centralizes the medium access control(MAC)modules of both the FTTH and FTTR networks at the FTTH’s Optical Line Terminal(OLT)for unified control and management of the cascaded network.We develop a unified bandwidth scheduling protocol by extending the ITU-T PON standard for both the upstream and downstream directions of C-FAN.We also propose a unified dynamic bandwidth allocation(UDBA)algorithm for efficient bandwidth allocation for multiple traffic flows in the two-tier cascaded network.Simulations are conducted to evaluate the performance of the proposed control protocol and the UDBA algorithm.The results show that,in comparison to the conventional DBA algorithm,the UDBA algorithm can utilize upstream bandwidth more efficiently to reduce packet delay and loss,without adversely impacting downstream transmission performance.

Achieving Ultra-Broad Microwave Absorption Bandwidth Around Millimeter-Wave Atmospheric Window Through an Intentional Manipulation on Multi-Magnetic Resonance Behavior

The utilization of electromagnetic waves is rapidly advancing into the millimeter-wave frequency range,posing increasingly severe challenges in terms of electromagnetic pollution prevention and radar stealth.However,existing millimeter-wave absorbers are still inadequate in addressing these issues due to their monotonous magnetic resonance pattern.In this work,rare-earth La^(3+)and non-magnetic Zr^(4+)ions are simultaneously incorporated into M-type barium ferrite(BaM)to intentionally manipulate the multi-magnetic resonance behavior.By leveraging the contrary impact of La^(3+)and Zr^(4+)ions on magnetocrystalline anisotropy field,the restrictive relationship between intensity and frequency of the multi-magnetic resonance is successfully eliminated.The magnetic resonance peak-differentiating and imitating results confirm that significant multi-magnetic resonance phenomenon emerges around 35 GHz due to the reinforced exchange coupling effect between Fe^(3+)and Fe^(2+)ions.Additionally,Mosbauer spectra analysis,first-principle calculations,and least square fitting collectively identify that additional La^(3+)doping leads to a profound rearrangement of Zr^(4+)occupation and thus makes the portion of polarization/conduction loss increase gradually.As a consequence,the La^(3+)-Zr^(4+)co-doped BaM achieves an ultra-broad bandwidth of 12.5+GHz covering from 27.5 to 40+GHz,which holds remarkable potential for millimeter-wave absorbers around the atmospheric window of 35 GHz.

Prediction of Bandwidth of Metamaterial Antenna Using Pearson Kernel-Based Techniques

The use of metamaterial enhances the performance of a specific class of antennas known as metamaterial antennas.The radiation cost and quality factor of the antenna are influenced by the size of the antenna.Metamaterial antennas allow for the circumvention of the bandwidth restriction for small antennas.Antenna parameters have recently been predicted using machine learning algorithms in existing literature.Machine learning can take the place of the manual process of experimenting to find the ideal simulated antenna parameters.The accuracy of the prediction will be primarily dependent on the model that is used.In this paper,a novel method for forecasting the bandwidth of the metamaterial antenna is proposed,based on using the Pearson Kernel as a standard kernel.Along with these new approaches,this paper suggests a unique hypersphere-based normalization to normalize the values of the dataset attributes and a dimensionality reduction method based on the Pearson kernel to reduce the dimension.A novel algorithm for optimizing the parameters of Convolutional Neural Network(CNN)based on improved Bat Algorithm-based Optimization with Pearson Mutation(BAO-PM)is also presented in this work.The prediction results of the proposed work are better when compared to the existing models in the literature.

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Robust high frequency seismic bandwidth extension with a deep neural network trained using synthetic data

Geophysicists interpreting seismic reflection data aim for the highest resolution possible as this facilitates the interpretation and discrimination of subtle geological features.Various deterministic methods based on Wiener filtering exist to increase the temporal frequency bandwidth and compress the seismic wavelet in a process called spectral shaping.Auto-encoder neural networks with convolutional layers have been applied to this problem,with encouraging results,but the problem of generalization to unseen data remains.Most published works have used supervised learning with training data constructed from field seismic data or synthetic seismic data generated based on measured well logs or based on seismic wavefield modelling.This leads to satisfactory results on datasets similar to the training data but requires re-training of the networks for unseen data with different characteristics.In this work seek to improve the generalization,not by experimenting with network architecture(we use a conventional U-net with some small modifications),but by adopting a different approach to creating the training data for the supervised learning process.Although the network is important,at this stage of development we see more improvement in prediction results by altering the design of the training data than by architectural changes.The approach we take is to create synthetic training data consisting of simple geometric shapes convolved with a seismic wavelet.We created a very diverse training dataset consisting of 9000 seismic images with between 5 and 300 seismic events resembling seismic reflections that have geophysically motived perturbations in terms of shape and character.The 2D U-net we have trained can boost robustly and recursively the dominant frequency by 50%.We demonstrate this on unseen field data with different bandwidths and signal-to-noise ratios.Additionally,this 2D U-net can handle non-stationary wavelets and overlapping events of different bandwidth without creating excessive ringing.It is also robust in the presence of noise.The significance of this result is that it simplifies the effort of bandwidth extension and demonstrates the usefulness of auto-encoder neural network for geophysical data processing.

A distributed on-demand bandwidth-constrained multicast routing protocol for wireless ad hoc networks

To meet the bandwidth requirement for the multicasting data flow in ad hoc networks, a distributed on- demand bandwidth-constrained multicast routing （BCMR） protocol for wireless ad hoc networks is proposed. With this protocol, the resource reservation table of each node will record the bandwidth requirements of data flows, which access itself, its neighbor nodes and hidden nodes, and every node calculates the remaining available bandwidth by deducting the bandwidth reserved in the resource reservation table from the total available bandwidth of the node. Moreover, the BCMR searches in a distributed manner for the paths with the shortest delay conditioned by the bandwidth constraint. Simulation results demonstrate the good performance of BCMR in terms of packet delivery reliability and the delay. BCMR can meet the requirements of real time communication and can be used in the multicast applications with low mobility in wireless ad hoc networks.

软硬件协同的RapidIO接口带宽测试方法

RapidIO是一种高性能嵌入式系统互联技术。FPGA的SRIO控制器实现了RapidIO二代协议,在工程中经常需要得到其实际带宽性能以确定其是否满足应用需求。采用FPGA的嵌入式软核,配合FPGA内部硬件电路可搭建软硬件协同SOPC测试系统。该系统既具有硬件可裁剪、可定制、扩展性强的特点,又具备软件灵活性的特点。此系统在硬件层面设计了周期采样单元、周期配置接口、锁存接口、上传接口;软件层面具备采样参数配置、采样控制、采样数据分析、结果呈现功能。通过软硬件代码的编写和验证,表明此方法可实时监测接口的带宽及抖动性能指标。

PREDICTION-BASED BANDWIDTH ALLOCATION FOR VBR TRAFFIC

A prediction based bandwidth allocation scheme for transporting MPEG VBR traffic is proposed by using the FARIMA (p,d,q) (fractional autoregressive integrated moving average) model.FARIMA (p,d,q) model is capable of capturing both the long range and short range dependence in the video traffic.A method is suggested to simplify the FARIMA model fitting procedure and hence to reduce the time of traffic modeling and prediction.The simulation experiments show that this scheme can significantly reduce the requirement of buffer size and the frame loss rate.

具有新型低损耗电极PIN光探测器的研究

基于一种具有微孔-槽结构的PIN光探测器结构,设计了一种低损耗电极并与之进行联合优化。该方法不但为制备低损耗电极提供了有效的解决方案,还进一步提升了光探测器的3 dB带宽。首先,通过优化电极衬底与厚度、引入绝缘层、增加金属材料以及在衬底中加入矩形槽结构等方式,设计了一款新型低损耗的光探测器电极,降传输损耗降至-1.15 dB。然后,将新型电极与PIN光探测器的等效电路进行联合设计优化。结果表明,与未使用该新型电极相比,光探测器的3 dB带宽提升了近32%。该新型电极的设计可以为不同结构及不同波段光探测器的性能改进提供参考。

On-demand QoS routing protocol based on energy and bandwidth requirement in Ad Hoc networks

Along with the emergence of real-time multi-media,interactive service,real-time voice and other services calling for high quality of service,there should be a good network to support those services.Most present route algo- rithms with computational complexity hardly consider the restriction of node energy,so it degrades the whole capabil- ity of network.Bandwidth guarantee is one of the most crucial factors in real-time application,and this paper brings forward a distributed on-demand QoS routing protocol based on energy and bandwidth requirement.This QoS routing protocol makes use of bandwidth calculation algorithm and analyzes its route mechanism.The simulation results veri- fy its validity.The QoS routing protocol improves the packet delivery fraction and average end-to-end delay,prolongs the network lifetime,enhances the network performance and satisfies the route requirement for ad hoc networks.

An Adaptive-Bandwidth CMOS PLL with Low Jitter and a Wide Tuning Range

This paper presents a novel adaptive-bandwidth charge pump PLL with low jitter and a wide tuning range. With an adaptive bandwidth,the proposed PLL can scale its loop dynamics proportional to the output frequency and maintain optimal performance over its entire output range. In order to improve the jitter performance of the PLL,a matching tech- nique is employed in the charge pump,and a voltage-to-voltage converter is used to achieve a low gain VCO. The experimental chip was fabricated in a 0. 35μm CMOS process. The measured results show that the PLL has perfect jitter performance within its operating range from 200MHz to 1.1GHz.

Fe_(0.02)/Ag_(x)-ZnO复合材料的合成及其光催化活性

采用水热合成法及煅烧法,制备了不同掺杂量的Fe_(0.02)/Ag_(x)-ZnO复合材料,并考察了各催化剂对RhB光催化降解活性.机理分析表明,Fe掺杂进ZnO,Fe^(3+)可以形成陷阱捕获e-,导致ZnO的导带下方形成一个Fe掺杂能级,促使缩短了ZnO的带隙,扩大了光谱响应范围;Ag的掺入促使部分电子(e^(-))跃迁到Ag单质上,减小了禁带宽度,降低了电子跃迁所需的能量,抑制了e^(-)-h^(+)的复合,Fe_(0.02)/Ag_(x)-ZnO样品的新费米能级低于Fe-ZnO和ZnO的导带能级,导致其界面处的电荷分离;进一步研究Fe_(0.02)/Ag_(x)-ZnO复合材料对染料罗丹明B(Rhodamine B,RhB)的光催化降解性能和循环使用性能.结果表明,Fe_(0.02)/Ag_(x)-ZnO复合材料可作为一种稳定、高效且可循环的光催化剂材料并用于污水处理,拓展了Fe_(0.02)/Ag_(x)-ZnO复合材料的应用.

一种改进的数字Ultra-Wide Bandwidth Radio-on-Fiber系统模型的性能分析

为了充分利用超宽带的特点,对数字光载无线系统进行了改进,并给出了系统模型.理论分析和仿真结果表明,跳时序列构造不同,系统性能(信噪比)也不同;相同构造下,激活用户数不同引起的时隙平均干扰也不同.这种改进使得数字光载无线系统降低了复杂度,提高了光纤利用率,同时也改善了系统的性能.

基于5G网络的低时延高带宽传输协议优化与可靠性分析

5G网络的低时延高带宽特性为各种应用场景提供了技术支持,现有传输协议在5G环境下仍存在时延抖动和可靠性不足的问题。分析了当前主流传输协议,总结了导致时延与带宽不稳定的关键因素,提出了一种优化的传输协议。通过对优化方案的性能分析,得出该协议能够有效降低时延抖动并提高数据传输的可靠性。

基于重复码不同质重传的URLLC最小化带宽方法

为实现5G超可靠低延迟通信(URLLC)应用场景在高服务质量(QoS)要求下的最小带宽资源分配问题,提出一种基于混合自动重传请求(HARQ)的重复码不同质传输的带宽最小化方案HTRCBM-HARQ。通过提出一种重传方式,即重复码不同质传输的HARQ,提高可靠性;通过建立时延与可靠性分析的框架,导出系统所需最小带宽公式。仿真结果表明,该算法有效提高了有限带宽资源的利用率,与现有算法对比可以节省10%~30%的带宽资源。

Two narrow bandwidth photons interfering in an electromagnetically induced transparency (EIT) system

In this paper, we have analysed in detail the quantum interference of the degenerate narrowband two-photon state by using a Mach-Zehnder interferometer, in which an electromagnetically induced transparency （EIT） medium is placed in one of two interfering beams. Our results clearly show that it is possible to coherently keep the quantum state at a single photon level in the EIT process, especially when the transparent window of the EIT medium is much larger than the bandwidth of the single photon. This shows that the EIT medium is possibly a kind of memory or repeater for the narrowband photons in the areas of quantum communication and quantum computer. This kind of experiment is feasible within the current technology.

A New Method to Determine Central Wavelength and Optimal Bandwidth for Predicting Plant Nitrogen Uptake in Winter Wheat

Plant nitrogen （N） uptake is a good indicator of crop N status. In this study, a new method was designed to determine the central wavelength, optimal bandwidth and vegetation indices for predicting plant N uptake （g N m-2） in winter wheat （Triticum aestivum L.）. The data were collected from the ground-based hyperspectral reflectance measurements in eight field experiments on winter wheat of different years, eco-sites, varieties, N rates, sowing dates, and densities. The plant N uptake index （PNUI） based on NDVI of 807 nm combined with 736 nm was selected as the optimal vegetation index, and a linear model was developed with R2 of 0.870 and RMSE of 1.546 g N m-2 for calibration, and R2 of 0.834, RMSE of 1.316 g N m-2, slope of 0.934, and intercept of 0.001 for validation. Then, the effect of the bandwidth of central wavelengths on model performance was determined based on the interaction between central wavelength and bandwidth expansion. The results indicated that the optimal bandwidth varies with the changes of the central wavelength and with the interaction between the two bands in one vegetation index. These findings are important for prediction and diagnosis of plant N uptake more precise and accurate in crop management.

Dynamic Bandwidth Allocation and Rate Coordination for DiffServ Environment

This paper presents a novel model for dynamic bandwidth allocation and rate coordination based on DiffServ and a bandwidth broker（BB）. In this model, assignment of bandwidth was made according to a periodic trace of network characteristics per application. And adjustment of transfer rate was accomplished through negotiation with applications by a bandwidth agent. This model was evaluated using network simulator 2 （NS-2）, and distinct improvements were found in respects of delay and packet loss of overall network and single flow. Finally, the model was suggested to be leveraged to multimedia applications with properties of lower delay and lower packet loss.

High efficiency and broad bandwidth grating coupler between nanophotonic waveguide and fibre

A high efficiency and broad bandwidth grating coupler between a silicon-on-insulator （SOI） nanophotonic waveguide and fibre is designed and fabricated. Coupling efficiencies of 46% and 25% at a wavelength of 1.55um are achieved by simulation and experiment, respectively. An optical 3 dB bandwidth of 45 mn from 1530 nm to 1575 nm is also obtained in experin, ent. Numerical calculation shows that a tolerance to fabrication error of 10 nm in etch depth is achievable. The measurement results indicate that the alignment error of 112 um results in less than 1 dB additional coupling loss.

Accuracy of the half-power bandwidth method with a third-order correction for estimating damping in multi-DOF systems

A third-order correction was recently suggested to improve the accuracy of the half-power bandwidth method in estimating the damping of single DOF systems.This paper analyzes the accuracy of the half-power bandwidth method with the third-order correction in damping estimation for multi-DOF linear systems.Damping ratios in a two-DOF linear system are estimated using its displacement and acceleration frequency response curves,respectively.A wide range of important parameters that characterize the shape of these response curves are taken into account.Results show that the third-order correction may greatly improve the accuracy of the half-power bandwidth method in estimating damping in a two-DOF system.In spite of this,the half-power bandwidth method may significantly overestimate the damping ratios of two-DOF systems in some cases.