城市轨道交通线网资源共享规划

结合广州市城市轨道交通线网建设规划的经验,提出在城市轨道交通线网建设规划与具体线路工程可行性研究之间增加线网资源共享规划研究阶段的观点,并对开展线网资源共享规划的必要性和主要研究内容进行了阐述。

基于虚拟现实技术的安全智能无线网络资源动态分配方法研究

不同时刻使用无线网络的用户数量不同,安全智能无线网络资源分配处于动态变化中。当前资源分配方法无法适应动态变化环境,导致整个无线网络吞吐量高、资源利用率低下、整体效用差。为此,提出一种新的基于虚拟现实技术的安全智能无线网络资源动态分配方法,给出选择的虚拟现实架构,对虚拟现实架构进行分析。在对安全智能无线网络资源进行动态分配时,将增强网络吞吐量,减少延迟,保证系统稳定和用户的服务质量看作分配原则;将整体效用最大化作为目标函数,实现资源分配。通过粒子群算法对目标函数进行求解。实验结果表明,采用所提方法对安全智能无线网络资源进行动态分配,不仅能够保证网络吞吐量,而且资源利用率高,整体效用强。

基于无人机信能同传的传感器网络无线资源管理--评《下一代无线网络跨层资源管理》

随着科学技术的发展,智能控制、无线充电以及集成芯片等关键技术的不断突破和深入应用,无人机的性能越来越优越,在能源、测绘、植保、农耕、通信以及国防等领域得到广泛应用,尤其是近几年,其发展与应用在国民经济和人类社会的生产生活中扮演的角色也越来越重要。在现有科学技术发展的基础上,大力开展技术创新,提高无人机产品性能、拓展服务应用领域、推动产品检测认证以及建设健全、标准的产业管理体系和评价系统是推动我国无人机产业长久、健康发展的重要研究内容。无线电波可以同时进行能量与信息的传输,降低通信能耗,无线网络技术的应用与普及,加快了无线网络资源管理的研究与发展。

WCDMA用户业务模型分析及对无线网络资源的影响

WCDMA网已进行了三年多的建设,WCDMA网无线资源配置依然沿用集团统一模型,分析现网不同城市WCDMA网三种主要业务R99、HSDPA、HSUPA的实际模型,结合不同业务对网络资源的需求,分析实际业务发展的资源受限条件,可以指导更有效的网络规划建设和无线资源配置方案。

无线网络资源管理中接入控制对策研究

随着现代经济和社会的快速发展,信息技术得到普遍的应用。在信息技术的大力支持下,无线网络技术也迅速发展起来。无线网络资源的合理化利用给世界各国带来了极大的经济效益,而且加深了各国之间的联系,使世界成为一个日益密切的共同体。但是,无线网络技术在给人们带来便利的同时,也带来了相应的问题。尤其是网络信号差、网络连接不畅通等问题极大地影响到了人们的经济和社会生活。为了解决这些问题,实现对无线网络资源的合理有效控制,采取控制对策就显得十分必要。为了强化对无线网络资源的管理,文章对将控制对策应用到无线网络资源管理中进行了一系列的探讨。

无线网络资源管理中接入控制对策研究

在中国经济快速发展过程中,信息化技术应用的程度越来越普遍。尤其是在信息化技术的支持下,无线网络技术发展的潜力越来越显著。无线网络资源在实现合理化运用的过程中,不仅为各个国家的发展带来极大的受益,而且使各国之间的联系更为紧密,全球化进程推进更为便捷。然而,无线网络技术虽然为民众的生活带来了极多的便利之处,但是,也为发展带来了很多的不利之处,对发展的制约性作用明显。如信号接收不稳定、网络不通畅、网络服务质量下降等,这些都会给人们的生活带来了一些不利的影响。因此,为了解决这一现状,我们必须要重视对无线网络资源的控制,并且针对目前的现状提出一系列可行的对策,实现无线网络资源有效的利用。

无线网络资源可信大数据分析方法研究

在传统无线网络资源的可信大数据分析中,存在运算精度不高的问题。基于此,笔者首先运用关联规则对大数据中需要分析的数据进行挖掘,然后对挖掘出的数据集采用并行计算来确定并行关系,确定其中存在的并行关系后,对分析数据集进行空间划分,生成数据集网格,最后对生成的数据集网格进行近端算子分析,完成对大数据的分析。实验结果表明,设计方法在收敛系数和运算时间上均优于传统方法,证明该方法具有可行性。

基于小区负荷系数的节假日无线网络容量预测

每个节假日前后我国都会有大量人口的迁徙,尤其是传统春节,短期内大量人口的迁徙对移动通信网络的容量提出极大的挑战。另外,随着抖音、快手等短视频的崛起,无线流量呈爆发式增长。如何准确评估短期内不同区域的无线网络资源需求、如何确保短期内用户满意度保持稳定.

一种无线资源智能调控系统的设计与实现

随着无线网络业务尤其是数据类业务的快速发展,无线网络资源调控和优化工作面临越来越大的压力和挑战。提出并实现一种无线资源智能调控系统,从多维度对话务统计、现网资源配置参数等大数据进行分析,实现业务量精准预测,调控方案智能生成,并通过MML接口自动下发网元执行,实现无线资源的精确调度和配置。

无线通信网络多节点资源均衡配置方法

为实现缩短无线通信网络多节点平均端到端延时,在保证资源均衡分配的条件下实现高效配置,开展无线通信网络多节点资源均衡配置方法设计研究。通过无线通信网络多节点增删线性规划、多节点对应资源需求量均衡分配以及基于资源需求量的多节点布局优化重配置,提出一种全新的配置方法。应用实例证明,新的配置方法应用到无线通信网络中可有效缩短多节点平均端到端延时时间,为无线通信网络稳定运行提供有利条件。

基于空中协同无线网络资源人工智能分配算法的智慧乡村平台

随着人工智能技术的不断发展,智慧乡村建设占据着重要地位。为了加快智慧乡村平台网络建设,研究搭建无人机空中协同无线网络系统获取农业相关空中协同位置信息。同时结合资源人工智能分配算法,即以最佳位置匹配为主,经匈牙利算法实现系统的位置匹配,从而实现资源分配。结果表明,随着空中接入点最大连接数的增加,总时延有所减少。在地面感应节点数量在300个以内的情况下,总时延不超过600 ms。改进总时延从597 ms减少到402 ms,减少了195 ms。这说明系统提升性能,处理速度加快,响应时间缩短。改进方法可以有效地减少通信系统中的传输延迟,提高数据传输的效率,并且对于地面用户数量的增加和任务量的提升有很好的适应能力。研究设计的资源分配策略有利于实现无线网络资源的智能管理和优化分配,这为智慧乡村建设提供了有力支持。

CDMA无线基站设备调配方案探讨

通过对现有覆盖广大农村及交通干线的超闲宏基站设备进行相应的无线网络资源调整,一方面降低无线网投资,一方面提高无线网络的利用率。

动态无线网络资源配置系统的应用研究

采用动态无线网络资源配置系统,能大幅度提高频率利用率和吸收话务量。本文对该系统的应用领域进行了详细研究,用于解决基站建设、话务平衡、话务调度、频率利用率低等难题,供同行们参考。而且这一技术的本身也是对传统频率配置方式的一种革新,具有重要的积极意义。

Qo E-based resource allocation protocols in cognitive OFDMA network with hybrid model

A resource allocation protocol is presented in an orthogonal frequency division multiple access （OFDMA） cognitive radio （CR） network with a hybrid model which combines overlay and underlay models. Without disrupting the primary user （PU） transmissions, the overlay model allows the secondary user （SU） to utilize opportunistically the idle sub-channels; the underlay model allows the SU to occupy the same sub-channels with PU. The proposed protocols are designed for maximizing the quality of experience （QoE） of CR users and switching dynamically between the overlay and underlay models. QoE is measured by the mean opinion score （MOS） rather than simply fulfilling the physical and medium access control （MAC） layer requirements. The simulations considering the file transfer and video stream services show that the proposed resource allocation strategy is spectrum efficient.

Traffic Characteristics Based Dynamic Radio Resource Management in Heterogeneous Wireless Networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.

SDN Based Next Generation Mobile Network With Service Slicing and Trials

Software-Defined Network （SDN） empowers the evolution of Internet with the OpenFlow, Network Virtualization and Service Slicing strategies. With the fast increasing requirements of Mobile Internet services, the Internet and Mobile Networks go to the convergence. Mobile Networks can also get benefits from the SDN evolution to fulfill the 5th Generation （5G） capacity booming. The article implements SDN into Frameless Network Architecture （FNA） for 5G Mobile Network evolution with proposed Mobile-oriented OpenFlow Protocol （MOFP）. The Control Plane/User Plane （CP/UP） separation and adaptation strategy is proposed to support the User-Centric scenario in FNA. The traditional Base Station is separated with Central Processing Entity （CPE） and Antenna Element （AE） to perform the OpenFlow and Network Virtualization. The AEs are released as new resources for serving users. The mobile-oriented Service Slicing with different Quality of Service （QoS） classification is proposed and Resource Pooling based Virtualized Radio Resource Management （VRRM） is optimized for the Service Slicing strategy with resource-limited feature in Mobile Networks. The capacity gains are provided to show the merits of SDN based FNA. And the MiniNet based Trial Network with Service Slicing is implemented with experimental results.

A Novel Deep Learning Method for Application Identification in Wireless Network

In modern wireless communication network, the increased consumer demands for multi-type applications and high quality services have become a prominent trend, and put considerable pressure on the wireless network. In that case, the Quality of Experience(Qo E) has received much attention and has become a key performance measurement for the application and service. In order to meet the users' expectations, the management of the resource is crucial in wireless network, especially the Qo E based resource allocation. One of the effective way for resource allocation management is accurate application identification. In this paper, we propose a novel deep learning based method for application identification. We first analyse the requirement of managing Qo E for wireless communication, and review the limitation of the traditional identification methods. After that, a deep learning based method is proposed for automatically extracting the features and identifying the type of application. The proposed method is evaluated by using the practical wireless traffic data, and the experiments verify the effectiveness of our method.

A New Power Allocation Algorithm in Cognitive Radio Networks

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.