利用MOBILE6.2模型预测高速公路路段综合排放因子

采用美国环保局(EPA)的MOBILE6.2模型,结合滨州市的实际情况,对滨州市的两个高速公路站,黄河大桥站和无棣站,通过车辆数目、车型进行统计分析,从而得到两个高速公路站点排放因子数据,其计算结果能为高速公路机动车污染控制提供依据,同时也提出了一种新的使用模型来计算高速公路路段排放因子的方法。

不同排放标准下大型柴油客车实测排放因子与MOBILE6预测值的对比分析

在利用先进的车载尾气检测技术(PEMS)收集了我国大型柴油客车尾气的实时排放数据的基础上,分析了不同排放标准下车辆(国Ⅰ、国Ⅱ、国Ⅲ)的CO、HC、NOx和PM排放因子与速度的关系;使用MOBILE6模型,经过模型参数校正,预测了相应车辆的排放因子,并与不同排放标准下的车辆排放实测值进行对比,从而验证了MOBILE6模型对我国大型柴油客车尾气排放预测的适用性。

基于MOBILE6.2的机动车气态污染物排放量与分担率研究

通过对太原市机动车运营特征的分析,采用修正的MOBILE6.2模式,对主要参数进行本地化修正,计算了太原市机动车排放的气态污染物排放因子,并确定了太原市分车型污染物的排放总量和分车型的排放分担率。结果表明,2011年太原市机动车CO、HC和NOx的总排放量分别为42.44×104 t、3.93×104 t和4.71×104 t。分析得出,轻型客车是主要的排放源,分别占(质量分数)82.50%、76.61%和45.40%,其原因是由于轻型客车27.5%的年增长率以及较高的排放因子共同造成的;重型车是NOx排放的第二大排放源,占NOx总排放量的36.47%。以上两种车型是太原市机动车排放污染控制的重点。

中巴车实测排放因子和MOBILE6预测值的对比分析

利用车载尾气检测(OEM)技术对在实际道路上行驶的中巴车辆进行测试,得到该车的实测排放因子;同时应用美国环保局(EPA)开发的MOBILE6模型,在对相关参数进行适当调整后计算相应的排放因子;对得到的排放因子进行比较和分析,并就MOBILE6模型在我国的适用性做出探讨。

基于MOBILE6模型的车流波状态尾气排放问题研究

车流波现象是城市交通流中一种不稳定状态。当城市快速路出现车流波现象时,车流运行的平稳性会明显降低,同时燃油消耗量和尾气排放量却随之上升。因此,对车流波状态下尾气排放进行研究是十分必要的,对于整个城市大气环境的改善意义重大,也更加有利于和谐、可持续交通的发展。

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

富康车实测尾气排放数据分析

利用OEM系统收集富康车在实际路况上的实时尾气排放数据,得出3种主要污染物NOx、CO、HC的排放因子及测试车辆的百公里耗油量,并将排放因子同MOBIEM6模型预测的排放因子进行对比,最后对OEM技术在我国的应用进行初步探讨。

6G技术中的空中接入网:进展与展望

空中接入网(aerial access network, AAN)具有抗毁性强、覆盖范围广、视距传播概率高的特点,与地面网络相结合能够缓解流量负载压力,提供全时空的连接与服务,可有效助力第六代移动通信网络(6th generation mobile networks, 6G)“万物智联”愿景的实现.因此,在分析AAN中的卫星通信和高空平台(high altitude platform station, HAPS)技术研究进展的基础上,研究了卫星通信在数据接入方面的应用以及HAPS在一体化网络架构中的作用,探究了卫星与HAPS两种技术对未来网络的影响以及进一步优化二者的潜在方法.最后,对卫星接入的数据碰撞问题和HAPS的缓存问题进行讨论分析,并从上述问题出发展望了卫星通信和HAPS技术的未来发展方向.

Asymmetrical multi-gateways based internet connectivity for MANET6

Mobile ad hoc networks (MANETs) are autonomous and infrastructureless networks that support multi-hop wireless communications among mobile hosts. Providing global internet connectivity to MANETs is a strong trend nowadays, so the mobile hosts can enjoy the tremendous services of the Internet. In this paper, we present an asymmetrical approach that uses multiple Internet Gateways to provide MANETs nodes with Internet connectivity and access to the Internet’s resources. The rational utilization of all available Internet Gateways can meet the load of MANETs balance and reduce the latency of packets communication between MANETs and the Internet; this can be concluded from the results of the simulation experiments.

MIMO-Terahertz in 6G Nano-Communications:Channel Modeling and Analysis

With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,which demands for new solutions.Terahertz(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information network.THz communication has great application prospects in military-civilian integration and coordinated development.In China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the world.Therefore,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G.This paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel model.Then,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver.Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.

A FAST SEAMLESS HANDOVER SCHEME AND ITS CDT OPTIMIZATION FOR PING-PONG TYPE OF MOVEMENT

In mobile IPv6 networks, the ping-pong type of movement brings about frequent handovers and thus increases signaling burden. This letter proposes a fast seamless handover scheme where the access router keeps the mobile node's old reservation till the offline Count Down Timer (CDT) expires in order to reduce handover signaling and delay while the mobile node returns in a very short period of time. Based upon a pois son mobility model, an simple expression for CDT optimization is given out for the scheme to achieve the best cost performance of resource reservation.

New multicast scheme based on Dynamic mobility prediction in mobile IPv6 environment

A new mobile multicast scheme called mobility prediction based mobile multicast(MPBMM) was proposed. In MPBMM, when a mobile node (MN) roams among subnets during a multicast session, MN predicts the next subnet, to which MN will attach, by the information of its position and mobility speed, consequently speeds up the handoff procedure. Simulation results show that the proposed scheme can minimize the loss of multicast packets, reduce the delay of subnet handoff, decrease the frequency of multicast tree reconfiguration, and optimize the delivery path of multicast packets. When MN moves among subnets at different speeds (from 5 to 25 ms), the maximum loss ratio of multicast packets is less than0.2%, the maximum inter-arrival time of multicast packets is 117 ms, so the proposed scheme can meet the QoS requirements of real-time services. In addition, MPBMM can support the mobility of multicast source.

A three-level mobility management scheme for hierarchical mobile IPv6 networks

Performance evaluation shows that Hierarchical Mobile IPv6 (HMIPv6) cannot outperform standard Mobile IPv6 (MIPv6) in all scenarios. Thus, adaptive protocol selection under certain circumstances is desired. Moreover, it is necessary to balance the load among different Mobility Anchor Points (MAPs). This paper proposes an efficient three-level hierarchical ar- chitecture for mobility management in HMIPv6 networks, in which a mobile node (MN) may register with either a higher/lower MAP or its home agent according to its speed and the number of connecting correspondent nodes (CNs). An admission control algorithm and a replacement algorithm are introduced to achieve load balancing between two MAP levels and among different MAPs within the same MAP level. Admission control is based on the number of CNs but not MNs that an MAP serves. In case there is no capacity for an MN, the MAP chooses an existing MN to be replaced. The replaced MN uses the MAP selection al- gorithm again to choose another mobility agent. Simulation results showed that the proposed scheme achieves better performance not only in reducing the signaling overhead, but also in load balancing among different MAPs.

A framework for end-to-end RSVP context transfer in mobile IPv6

A framework for end-to-end RSVP context transfer in Mobile IPv6(MIPv6) based on the architecture of F-HMIPv6 is proposed in this paper. The scheme provides an end-to-end RSVP context transfer for real-time applications to overcome the weakness of Context Transfer Protocol which can not meet the need of end-to-end QoS mechanisms because contexts are only transferred between Access Routers(ARs), therefore they can promptly get the same forwarding process, minimize the handover service disruption, and avoid initiating the end-to-end RSVP signaling from scratch after an MN performs handovers. It may also reduce the signaling overhead and handover latencies by adopting the F-HMIPv6architecture. The performance of the approach is compared with the re-initiating RSVP signaling to re-establish QoS states using network simulator, and the numerical results show that the scheme has the less latency and packet loss than that of the re-initiating approach.

Effects of propofol on early and late cytokines in lipopolysaccharideinduced septic shock in rats

Objective：It has been reported that the intravenous anesthetic propofol（PPF）has anti-inflammatory effects in vitro and in patients.The purpose of this study was to investigate whether PPF has anti-inflammatory effects in lipopolysaccharide（LPS）-induced septic shock by inhibiting the induction of pro-inflammatory cytokinesinterleukin-6（IL-6）and tumor necrosis factor-α（TNF-α）and high mobility group box 1（HMGB1）in rats.Methods：Thirty six male Wistar rats were randomly assigned to one of three groups（control group,PPF＋LPS group and LPS group;n=12 per group）.Control group rats received a 0.9%NaCl solution（NS）by the tail vein.The PPF＋ LPS group rats received PPF（10 mg/kg bolus,followed by infusion at 10 mg/（kg·h）through a femoral vein catheter）1 h before LPS（7.5 mg/kg）administration via the tail vein.The LPS group rats received injection of LPS（7.5 mg/kg）via the tail vein.Hemodynamic effects were recorded as well as mortality rates,and plasma cytokine concentrations（TNF-α,IL-6,HMGB1）were measured for the 24-h observation period.Results：The mean arterial pressure and heart rate of the PPF＋LPS group were more stable than those of the LPS group.The mortality at 24 h after the administration of the LPS injection was much higher in the LPS group（58.3%）compared to the PPF＋ LPS group（25.0%）.Plasma concentrations of cytokines（IL-6 and TNF-α）and HMGB1 were significantly reduced in the PPF＋LPS group compared to the LPS group（P0.05）.Conclusion：Pretreatment with PPF reduced the mortality rate of rats and attenuated the pro-inflammatory cytokine responses in an endotoxin shock model through an anti-inflammatory action inhibiting induction of HMGB1.

Cloud-Assisted Distributed Edge Brains for Multi-Cell Joint Beamforming Optimization for 6G

In 5G networks,optimization of antenna beam weights of base stations has become the key application of AI for network optimization.For 6G,higher frequency bands and much denser cells are expected,and the importance of automatic and accurate beamforming assisted by AI will become more prominent.In existing network,servers are“patched”to network equipment to act as a centralized brain for model training and inference leading to high transmission overhead,large inference latency and potential risks of data security.Decentralized architectures have been proposed to achieve flexible parameter configuration and fast local response,but it is inefficient in collecting and sharing global information among base stations.In this paper,we propose a novel solution based on a collaborative cloud edge architecture for multi-cell joint beamforming optimization.We analyze the performance and costs of the proposed solution with two other architectural solutions by simulation.Compared with the centralized solution,our solution improves prediction accuracy by 24.66%,and reduces storage cost by 83.82%.Compared with the decentralized solution,our solution improves prediction accuracy by 68.26%,and improves coverage performance by 0.4 dB.At last,the future research work is prospected.

Spatio-Temporal Cellular Network Traffic Prediction Using Multi-Task Deep Learning for AI-Enabled 6G

Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration,traffic scheduling and intrusion detection,thus potentially supporting connected intelligence of the sixth generation of mobile communications technology(6G).However,the existing studies just focus on the spatio-temporal modeling of traffic data of single network service,such as short message,call,or Internet.It is not conducive to accurate prediction of traffic data,characterised by diverse network service,spatio-temporality and supersize volume.To address this issue,a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction.Functionally,this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer(DMFS-MT).The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data,respectively,via a new combination of convolutional gated recurrent unit(ConvGRU)and 3-dimensional convolutional neural network(3D-CNN).For the latter,each task is performed for predicting service-specific traffic data based on a fully connected network.On the real-world Telecom Italia dataset,simulation results demonstrate the effectiveness of our proposal through prediction performance measure,spatial pattern comparison and statistical distribution verification.

北京市机动车主要污染物排放量测算研究

介绍了测算机动车污染物排放量的MOBILE6模型,根据北京市机动车实际构成、行驶工况和行驶里程确定了模型所需参数,应用模型对北京市2012年一季度各月机动车主要污染物排放总量进行了计算和分析.计算结果与北京市同期空气质量监测结果趋势基本一致.

A Novel Location Management Scheme based on DNS in Proxy Mobile IPv6

Proxy Mobile IPv6 (PMIPv6) is designed to provide a network-based localized mobility management protocol, but it does not handle the global mobility of hosts. In this paper, we propose a location management scheme based on Domain Name System (DNS) for PMIPv6 which can support global mobility by using DNS as a location manager. In addition, to support large numbers of mobile terminals and enhance network scalability a paging extension scheme is introduced to PMIPv6. To evaluate the proposed location management scheme, we establish an analytical model, formulate the location update cost and the paging cost, and analyze the influence of the different factors on the total signaling cost. The performance results show that our proposed scheme outperforms the basic PMIPv6 under various parameters in terms of reducing the signaling overhead and the proposed scheme reduces signaling overhead compared to the basic PMIPv6.

5G Smart Mobility Management Based Fuzzy Logic Controller Unit

In the paper,we propose a fuzzy logic controller system to be implemented for smart mobility management in the 5G wireless communication network.Mobility management is considered as a main issue for all-IP mobile networks future generation.As a network-based mobility management protocol,Internet Engineering Task Force developed the Proxy Mobile IPv6(PMIPv6)in order to support the mobility of IP devices,and many other results were presented to reduce latency handover and the amount of PMIPv6 signaling,but it is not enough for the application needs in realtime.The present paper describes an approach based on the IEEE 802.21 Media Independent Handover(MIH)standard and PMIPv6,so we present a new vertical handover algorithm for anticipating handover process efficiently.Our object is to propose a smart mobility management that contribute in 5G wireless communication system network operating functions.Two proposed dynamic thresholds were successfully made to guaranty process triggering,and a new primitive MIH is proposed for signaling a needed handover to be done.Simulation results demonstrate a significant reduction of the handover delay,packet loss,handover blocking probability and signaling overhead.Simulation results and tests are accomplished.