基于802.11bf的无线感知会话模式规划方法

实现Wi-Fi感知的802.11bf协议草案给出了具有普适性的无线感知会话工作流程，该流程虽然能够应对各种场景，但面对实际应用中任意分布的目标感知测量区域，若根据协议流程直接发起感知测量会话，会造成通信资源浪费等问题。针对该问题，首先定义了802.11bf在应用中的通感一体化性能衡量指标；其次通过多目标遗传算法提出了一种无线感知会话模式规划方法，利用该规划方法分别从通信性能和感知性能两个方面进行优化。仿真结果显示,所提方法在保证无线感知会话在应用时的感知性能指标的同时，明显提升了无线感知会话期间的通信性能指标。     

语义通信中基于深度双Q网络的多维资源联合分配算法

5G技术的不断发展，带来了网络中数据量的爆发式升高与越来越多的涉及图像视频的语义理解任务，无疑对通信、计算和缓存资源造成了极大的压力。为更好地满足视频语义理解任务的资源需求，缓解资源紧缺现象，研究了语义通信中基于深度双Q网络的多维资源联合分配算法。首先，基于车联网场景，改进了现有的联合资源分配算法，引入缓存资源构建了新的面向语义的多维资源联合分配模型；其次，针对其动态时变的特性，搭建了深度双Q网络求解最优资源分配策略；最后，仿真验证了所提多维资源联合分配算法的性能优势。     

6G车联网络面向多源感知的数据融合技术

为满足未来自动驾驶车辆全方位、高可靠的感知性能需求，6G需要对不同维度、来源、颗粒度的多源感知数据进行实时传输与全局融合处理。然而，由于激光雷达、摄像机易受环境影响，毫米波雷达分辨率有限，不同车辆多视角点云姿态估计不准确等问题，分布在车联网络中的多源感知数据难以实现精确融合，同时有限通信带宽难以支撑海量感知数据的协同共享。为此，基于通信-感知-计算融合(通感算融合)的思想，提出了一种6G车联网络面向多源感知的数据分级融合处理方法。首先车侧借助于激光雷达、毫米波雷达与摄像机之间的空间校准，实现多传感器优势互补的深度融合，之后多车自组织成簇，采用ICP算法融合多车感知数据，并通过压缩去冗处理降低通信上传开销，最后路侧在无线感知辅助下，通过两步配准方法实现多源感知数据的全局融合。通过搭建仿真平台对所提方法进行性能验证，仿真结果表明所提多源感知数据分级融合方法可在通信开销较小的前提下保证感知精度，扩展车联网络感知范围和感知维度，并能保证恶劣天气下感知可靠性。     

6G车联网络通感融合方法与性能仿真

为了满足自动驾驶、远程驾驶等未来6G车联网应用对高速率、低时延传输以及高精度感知的性能需求，业界提出将无线通信与无线感知功能进行融合，在6G车联网络中实现无线传输与感知定位极致性能的同时满足。提出了一种基于通信感知信号时频域正交体制的通信感知融合方法，采用OFDM通信信号完成对目标的探测、定位，并利用短窗化矩阵分解参数估计方法完成对探测目标的感知信息提取。同时，搭建了系统级仿真平台对不同的时频资源配比下所提方法的通信/感知性能进行了评估，分析了所提融合方法下通信感知性能间的相互影响，并给出通信感知性能折中的设计方案。     

5G车联网资源优化分配方案综述

车联网作为智慧交通发展的必要组成部分，可加快我国智慧交通基础建设，对于智慧城市建设具有重要的现实意义。汽车数量及其产生的海量数据使得通信车辆节点之间的传输冲突率大幅上升，导致通信资源、计算资源短缺等问题，因此，有效的资源分配方案可以保证车联网的通信质量，从而提高车辆通信的可靠性，降低时延。首先分析了国内外车联网对智慧交通发展现状的影响以及当前车联网发展瓶颈；然后针对智慧交通通行效率、安全性方面，分析了当前车联网的资源分配问题；接着通过总结5G技术的优点，分析了5G在车联网资源优化分配管理上的贡献；最后，在车联网通信、计算和存储资源优化分配管理的应用背景下，结合人工智能技术提出了基于5G+V2X的智慧交通发展前景。     

一种基于无线携能通信的MEC与用户匹配算法

多接入边缘计算（Multi-access Edge Computing,MEC）和无线携能通信可有效提高用户的服务质量和体验。在计算、通信和能量等资源的约束条件下,用户匹配是优化MEC任务卸载时系统效用的重要方法。针对无线携能通信的MEC网络结构,综合考虑用户的需求差异性和多元化能量供给,建立了基于计算资源、传输资源和能量资源的系统效用函数;以系统效用最大化为目标,采用基于多维背包理论的多轮拍卖,提出了一种适用于多用户和多网络边缘服务器的用户匹配算法。仿真验证了所提用户匹配算法的有效性与可靠性,结果表明所提匹配算法可优化系统资源配置,有效提高整体性能。     

中继增强的无线蜂窝多小区系统的联合调度与功率控制算法

针对采用全局频率复用的中继增强的无线蜂窝多小区系统,该文考虑多种通信模式并存的混合场景,提出了一种干扰感知的联合资源分配策略。以最大化系统总吞吐量为目标,同时考虑小区间干扰对中继节点与移动站点的影响,以及基站与中继节点各自的发射功率约束。为了降低计算复杂度,针对用户与中继节点配对问题提出了一种基于小区间干扰的调度算法;针对功率控制问题分别提出了一种基于符号规划的最优功率分配算法和一种次优的最小能耗功率分配算法。仿真结果表明,该文所提算法逼近最优资源分配,在系统吞吐量与能量效率等性能方面具有显著优势。     

机器类通信中基于NOMA短编码块传输的高可靠低迟延无线资源分配优化方案

针对机器类通信(MTC)应用场景的业务特征和服务质量(QoS)要求,该文考虑基于非正交多址(NOMA)的MTC中短分组/短编码块传输,探讨MTC中基于NOMA的高可靠低迟延无线资源优化问题。首先,上行传输是基于NOMA的MTC通信的瓶颈,考虑无线蜂窝网络中支持NOMA和高可靠低迟延性能要求,该文建立了上行无线资源优化的系统模型;然后,分析上行传输迟延,导出基于距离的链路可靠性函数;进一步,以迟延、可靠性和带宽为约束下条件,提出一种最大化中心用户和速率的无线资源分配算法,并给出算法的收敛性证明和复杂度分析;最后,实验仿真验证了所提算法的性能优势。     

面向无人机网络的通信感知一体化的高效能波形选择方法

将感知功能集成入通信设备实现通信感知一体化功能，正在成为无人机通信网络的一个关键特征。现有通信感知融合方案集中于单一波形下的设计，缺乏对无人机飞行场景和波形的适配性研究；此外，无人机感知方式集中于雷达主动探测感知，无人机网络内存在较大的感知信息共享开销。基于此，首先梳理了典型通感融合波形的算法复杂度、载荷能力以及在高动态场景下的误码率性能等指标，引入综合效能指标以表征不同波形的综合能效特征，提出了一种基于感知信息驱动的通感融合波形选择机制，并针对该选择机制中所需决策算法进行了讨论分析，设计了一种“基于先验信息辅助的Q-Learning”波形决策算法，通过结合无人机事先已训练所得“感知信息-波形”先验信息映射与应用“Q-Learning”方法对实际飞行场景进行动态学习，实现在不同场景下无人机所采取通信方案的综合效能提升。为进一步降低主动感知无人机间系统开销，基于所提波形选择机制又提出了一种信号发送端主动感知与信号接收端被动感知相结合的主被动融合感知方案。最后通过仿真证明所提波形选择机制可以显著提高综合效能，验证了“基于先验信息辅助的Q-Learning”波形决策算法性能近似于理想判决，同...     

车联网移动无线数据通信系统的设计与实现

为了提高车联网移动无线数据通信能力,实现通过无线数据通信系统对车辆监控与导航,利用RFID和GPS技术,通过对车联网无线数据通信系统的结构分析,设计了车联网移动无线数据通信系统。重点研究了车载终端总体结构、车载终端通信模块、RFID感知通信模块、移动通信平台架构、定位追踪通信模块和远程控制通信模块。应用结果表明,该移动无线数据通信系统有较好显示能力和信息处理能力,能够处理导航、信息服务、车辆信息显示与辅助控制等功能的车载终端信息通信服务的需求。     

无人机测控系统中干扰感知与频谱资源管理技术

为了提高无人机测控系统在复杂电磁环境下的适应性、安全性和可靠性,解决多站多机同空域工作时面临的动态频谱资源管理问题,提出了一种基于干扰感知和频谱资源管理技术的无人机测控系统。该系统将通信侦察技术与认知无线电频谱感知技术相结合,为上/下行链路提供全频带干扰识别以及动态频谱资源管理。搭建了干扰感知和频谱资源管理系统无线测试平台,测试结果表明,当上/下行链路存在干扰信号且链路质量较差时,系统能自适应调整链路的频谱资源,可有效避开干扰信号对系统的影响,提升了无人机测控系统的生存能力和使用效能。     

A prioritized resource allocation algorithm for multiple wireless body area networks

This paper presents a prioritized resource allocation algorithm to share the limited communication channel resource among multiple wireless body area networks. The proposed algorithm is designed based on an active superframe interleaving scheme, one of the coexistence mechanisms in the IEEE 802.15.6 standard. It is the first study to consider the resource allocation method among wireless body area networks within a communication range. The traffic source of each wireless body area network is parameterized using the traffic specification, and required service rate for each wireless body area networks can be derived. The prioritized resource allocation algorithm employs this information to allocate the channel resource based on the wireless body area networks’ service priority. The simulation results verified that the traffic specification and the wireless body area network service priority based resource allocation are able to increase quality of service satisfaction, particularly for health and medical services.     

基于改进遗传算法的C-RAN网络动态无线资源分配

针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究.首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比.实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17％.     

基于正交时频空间调制的通信感知一体化系统的公平性功率分配方案

通信感知一体化（integrated sensing and communication，ISAC）通过实现通信和雷达感知的资源共享，在人机交互、车联网（vehicle-to-everything，V2X）、遥感和环境检测等应用场景中很有前景。为解决高移动性的车联网中通信和雷达感知所需的频率资源的冲突，基于正交时频空间（orthogonal time frequency space， OTFS）调制提出了 OTFS-ISAC 系统，基站通过接收车辆反射的回波，获得车辆运动参数，从而建立车辆运动的移动拓扑模型。此外，针对多车辆移动场景，提出了保证用户公平性的非正交多址接入OTFS-ISAC系统设计和功率分配算法。仿真结果表明，相比于无雷达感知辅助的非正交多址OTFS系统，基于OTFS-ISAC的非正交多址接入系统实现了25%的信息速率提升。     

双层网络中一种新的接入控制机制

在由宏小区和家庭小区构成的双层网络中,合理的进行资源分配可有效的控制干扰和优化容量.本文通过建立双层网络的下行干扰模型,分析了不同的资源分配方案和接入机制下的网络性能,提出了接入机制的优化算法,在保证用户通信概率要求的前提下对系统容量进行了优化.仿真结果表明,本文的接入控制机制在保证用户中断概率的条件下,提高了家庭基站允许的最大发射功率,优化了系统容量.     

Mechanism-based resource allocation for multimedia transmission over spectrum agile wireless networks

We propose to add a new dimension to existing wireless multimedia systems by enabling autonomous stations to dynamically compete for communication resources through adjustment of their internal strategies and sharing their private information. We focus on emerging spectrum agile wireless networks, where developing an efficient strategy for managing available communication resources is of high importance. The proposed dynamic resource management approach for wireless multimedia changes the passive way stations are currently adapting their joint source-channel coding strategies according to available wireless resources. Each wireless station can play the resource management game by adapting its multimedia transmission strategy depending on the experienced channel conditions and user requirements. The resource allocation game is coordinated by a network moderator, which deploys mechanism-based resource management to determine the amount of transmission time to be allocated to various users on different frequency bands such that certain global system metrics are optimized. Subsequently, the moderator charges the various users based on the amount of resources it has allocated to them, in order to discourage them from being dishonest about their resource requirements. We investigate and quantify both the users' and the system performance when different cross-layer strategies, and hence users' levels of smartness, are deployed by wireless stations. Our simulations show that mechanism-based resource management outperforms conventional techniques such as air-fair time and equal time resource allocation in terms of the obtained system utility. They also provide insights that can guide the design of emerging spectrum agile network protocols and applications     

Bandwidth utilization efficiency enhancement for OFDM‐based WSN

Normally IEEE 802.16 (WiMAX) is used for mainly downlink traffic applications. However in the upper tier of 2‐tier (WiMAX‐WiFi) wireless sensor network, the uplink bandwidth faces bottlenecks for high throughput. In this paper, a solution has been proposed for this limitation of uplink bandwidth allocation through the use of queuing theoretic performance modeling. A Markov‐modulated Poisson process traffic model has been formed for orthogonal frequency division multiple access‐based transmission along with discrete time Markov chain system model for queuing. A downlink traffic pattern has been defined for wireless sensor network nodes. Analytical methods are used to estimate the performance parameters like throughput, delay, and probability of packet drop for resource allocation. An algorithm is formulated to find out minimum resource requirement for downlink and to transfer rest of the resources to uplink bandwidth allocation, for throughput enhancement. Uplink frame utilization is determined through another discrete time Markov chain model for adaptive triggering between the proposed maximum and the normal downlink to uplink ratio operations, for efficient distribution of bandwidth resources. Algorithm and simulation results prove outstanding improvement in the uplink throughput around 50%, without degrading the downlink throughput.     

Joint downlink and uplink resource allocation for multi-carrier SWIPT system

A multi-carrier simultaneous wireless information and power transfer (SWIPT) communication system including one base station (BS) and one user was investigated,where both uplink and downlink adopt orthogonal frequency division multiplexing (OFDM).In the downlink,the BS transmited information and power to the user simultaneously.In the uplink,the user transmited information to the BS by using the power harvested from the BS in the downlink.The weighted sum of the downlink and uplink achievable rates by jointly optimizing subcarrier allocation and power allocation of the uplink and downlink were aimed to maximized.An optimal algorithm to solve the joint resource allocation problem was proposed,which was based on the Lagrange duality method and the ellipsoid method.Finally,the result shows the performances of the proposed algorithm by computer simulations.     

Energy-efficient resource allocation model for device-to-device communication in 5G wireless personal area networks

In general, there are several many devices that can overload the network and reduce performance. Devices can minimize interference and optimize bandwidth usage by using directional antennas and by avoiding overlapping communication ranges. In addition, devices need to carefully manage their use of resources, such as bandwidth and energy. Bandwidth is limited in wireless personal area networks (WPANs), so devices need to carefully select which data to send and receive. In this paper, an intelligent performance analysis of energy-efficient resource optimization model has been proposed for device-to-device (D2D) communication in fifth-generation (5G) WPAN. The proposed energy-efficient resource allocation in D2D communication is important because it helps reduce energy consumption and extend the lifespan of devices that are communicating with each other. By allocating resources in an efficient manner, communication between two devices can be optimized for maximum efficiency. This helps reduce the amount of energy needed to power the communication, as well as the amount of energy needed to power the device that is communicating with another device. Additionally, efficient resource allocation helps reduce the overall cost of communication, as the use of fewer resources results in a lower overall cost. The proposed efficient resource allocation helps reduce the environmental impact of communication, as less energy is used for communication. The proposed energy-efficient resource allocation model (EERAM) has reached 92.97% of energy allocation, 88.72% of power allocation, 87.79% of bandwidth allocation, 87.93% of spectrum allocation, 88.43% of channel allocation, 25.47% of end-to-end delay, 94.33% of network data speed, and 90.99% of network throughput.     

下行多业务OFDMA系统中基于有效容量的资源分配算法研究

该文对多业务OFDMA系统的下行链路资源分配进行了研究,侧重考虑了实时业务用户的QoS要求,建立2维马尔可夫无线信道模型,采用自适应调制技术、有效容量理论以及有效带宽理论,为实时用户分配资源;并实现了非实时业务用户、尽力而为业务用户的资源分配。仿真结果表明,所提算法保证了下行OFDMA系统吞吐量的同时,在实时业务的延时和丢包率等方面都有一定的优越性。