一种快速低开销的移动节点分布式寻路RPL路由协议

针对低功耗有损网络(Low Power and Lossy Network, LLN)中移动节点作为中继节点时,存在无线链路易断开、数据传输成功率较低和控制开销较高的问题,提出了一种快速低开销的移动节点分布式寻路RPL路由协议(Mobile Node Distributed Pathfinding RPL Routing Protocol, MNA-RPL)。首先,提出一种邻居表自适应更新机制,依据邻居表快速切换父节点;其次,提出一种父子节点双断开机制,能够有效减少数据包丢失;最后,提出一种基于速度动态管理的Trickle计时器,根据自身速度动态调整DIO广播周期。理论分析和仿真结果表明,与主流路由协议相比,该协议在数据传输和控制开销等方面的性能均有一定的提升。     

Femtosecond Laser 4D Printing of Light-Driven Intelligent Micromachines

Intelligent micromachines that respond to external light stimuli have a broad range of potential applications, such as microbots, biomedicine, and adaptive optics. However, artificial light-driven intelligent micromachines with a low actuation threshold, rapid responsiveness, and designable and precise 3D transformation capability remain unachievable to date. Here, a single-material and one-step 4D printing strategy are proposed to enable the nanomanufacturing of agile and low-threshold light-driven 3D micromachines with programmable shape-morphing characteristics. The as-developed carbon nanotube-doped composite hydrogel simultaneously enhanced the light absorption, thermal conductivity, and mechanical modulus of the crosslinked network, thus significantly increasing the light sensitivity and response speed of micromachines. Moreover, the structural design and assembly of asymmetric microscale mechanical metamaterial unit cells enable the highly efficient additive nanomanufacturing of 3D shape-morphable micromachines with large dynamic modulation and spatiotemporal controllability. Using this strategy, the world's smallest artificial beating heart with programmable light-stimulus responsiveness for the cardiac cycle is successfully printed. This 4D printing method paves the way for the construction of multifunctional intelligent micromachines for bionics, drug delivery, integrated microsystems, and other fields.     

道路交通网络节点分配优化策略研究进展

为了进一步提高城市道路交通网络的通行效率,粒子群优化和神经网络等多种智能优化算法受到越来越多的关注。近年来,深度学习技术的普及与应用大幅提升了城市交通网络的节点识别效率,而交通网络的节点调度又扩展了深度学习技术的应用。文中详细分析了交通节点调度所面临的关键问题,归纳并总结了相关网络节点分配的研究现状。在此基础上,深入研讨了城市交通网络节点调度与深度学习的应用前景,并对交通网络节点分配优化策略的未来研究方向进行了展望。     

Short packet communication in underlay cognitive network assisted by an intelligent reflecting surface

We propose short packet communication in an underlay cognitive radio network assisted by an intelligent reflecting surface (IRS) composed of multiple reconfigurable reflectors. This scheme, called the IRS protocol, operates in only one time slot (TS) using the IRS. The IRS adjusts its phases to give zero received cumulative phase at the secondary destination, thereby enhancing the end-to-end signal-to-noise ratio. The transmitting power of the secondary source is optimized to simultaneously satisfy the multi-interference constraints, hardware limitations, and performance improvement. Simulation and analysis results of the average block error rates (BLERs) show that the performance can be enhanced by installing more reconfigurable reflectors, increasing the blocklength, lowering the number of required primary receivers, or sending fewer information bits. Moreover, the proposed IRS protocol always outperforms underlay relaying protocols using two TSs for data transmission, and achieves the best average BLER at identical transmission distances between the secondary source and secondary destination. The theoretical analyses are confirmed by Monte Carlo simulations.     

Implementation of mmWave long-range backhaul for UAV-BS

Uncrewed aerial vehicles (UAVs) have become a vital element in nonterrestrial networks, especially with respect to 5G communication systems and beyond. The use of UAVs in support of 4G/5G base station (uncrewed aerial vehicle base station [UAV-BS]) has proven to be a practical solution for extending cellular network services to areas where conventional infrastructures are unavailable. In this study, we introduce a UAV-BS system that utilizes a high-capacity wireless backhaul operating in millimeter-wave frequency bands. This system can achieve a maximum throughput of 1.3 Gbps while delivering data at a rate of 300 Mbps, even at distances of 10 km. We also present the details of our testbed implementation alongside the performance results obtained from field tests.     

IP address allocation protocols in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), communication takes place between vehicles to vehicles, the vehicles to the road side units, and vice-versa. The basic purpose of these communications is to share and exchange tremendous amount of data and information. For efficient information sharing, a systematic and structured connection establishment algorithm is needed. In VANETs, each connected node of the network need to be assigned a unique address. Hence, an algorithm is needed for the proper assignment of unique address to all nodes in the network. This paper explains different types of IP address protocols in VANETs. We have also explained advantage and disadvantage of existing IP address allocation protocols in VANETs.     

终端近场通信天线研究北大核心CSCD

近场通信(NFC)已成为无线终端的标配功能,工作范围小、抗干扰性和安全性较高的特性使其被广泛应用于终端的移动支付和虚拟卡片等领域。由于近场天线产生的感应磁场会在临近的金属上耦合出反向涡流,并且金属屏蔽物覆盖会降低收发天线间的磁场耦合,紧凑终端中的电池、主板、外壳等金属元件将大幅影响NFC天线性能。本文从近场通信的历史、标准、系统结构出发,以终端NFC天线工作环境中的金属覆盖情况作为分类依据,对终端近场通信天线的研究进展进行了简要介绍。     

面向智慧能源的供需平衡数据可视化挖掘方法

为满足能源数据监测和综合分析领域的业务需要,提出面向智慧能源的供需平衡数据可视化挖掘方法。构造数据迁移与分类视图,确定每个供需平衡数据点位置坐标,并采用正交投影可视化技术将数据挖掘算法核心结构展示在视图中(支持用户对其进行相应调整);引入数据挖掘算法,提取数据可视化挖掘结果参数,实现面向智慧能源供需平衡数据的可视化挖掘。实验结果显示:智慧能源供需数据可视化挖掘结果综合评分数值范围为64.70~82.04分,充分说明该方法具备较好的可视化挖掘性能,可应用在多维典型用能场景中。     

基于深度学习的基金客服情绪安抚算法

构建基金智能客服情绪安抚算法,增加人性化设计以有效提升客户使用体验。由基于OCC模型的情绪粗粒度分类得到有负面情感的文本信息,对该文本信息进行相关处理,而后基于SVM模型进行情绪细粒度分类,得到文本的负面情绪类别并在囊括专业知识和情绪应答的基金领域知识库中匹配答案和情绪应答语句,将查询结果展示给客户。     

关于无线电技术在智能家庭系统中应用的探讨

如今,人工智能的发展成果已经走进千家万户,智能家庭的出现也使人工智能技术融入传统家电设施,并逐步实现对家电和相关设备的智能控制以及设备之间的自由联通。智能家庭成为未来家电家居的发展方向之一,而利用无线电技术实现设备间的互联和通信则是智能家庭系统的技术核心。从智能家庭产业发展现状入手,对智能家庭系统中无线电通信技术的应用进行阐述和分析,并对智能家庭的未来发展进行展望。