Centralized Quasi-Static Channel Assignment for Multi-Radio Multi-Channel Wireless Mesh Networks

Employing multiple channels in wireless multihop networks is regarded as an effective approach to increas-ing network capacity. This paper presents a centralized quasi-static channel assignment for multi-radio multi-channel Wireless Mesh Networks (WMNs). The proposed channel assignment can efficiently utilize multiple channels with only 2 radios equipped on each mesh router. In the scheme, the network end-to-end traffics are first modeled by probing data at wireless access points, and then the traffic load between each pair of neighboring routers is further estimated using an interference-aware estimation algorithm. Having knowledge of the expected link load, the scheme assigns channels to each radio with the objective of mini-mizing network interference, which as a result greatly improves network capacity. The performance evalua-tion shows that the proposed scheme is highly responsive to varying traffic conditions, and the network per-formance under the channel assignment significantly outperforms the single-radio IEEE 802.11 network as well as the 2-radio WMN with static 2 channels.

Best-retransmission count selection for environment optimization over wireless heterogeneous networks

This paper proposes an environment-aware best- retransmission count selected optimization control scheme over IEEE 802.11 multi-hop wireless networks. The proposed scheme predicts the wireless resources by using statistical channel state and provides maximum retransmission count optimization based on wireless channel environment state to improve the packet delivery success ratio. The media access control （MAC） layer selects the best-retransmission count by perceiving the types of packet loss in wireless link and using the wireless channel charac- teristics and environment information, and adjusts the packet for- warding adaptively aiming at improving the packet retransmission probability. Simulation results show that the best-retransmission count selected scheme achieves a higher packet successful delivery percentage and a lower packet collision probability than the corresponding traditional MAC transmission control protocols.

多信道无线通信网络动态数据完整性存储仿真

在多信道环境下传输数据,易受无线通信网络连接不稳定性影响,且存在多个节点竞争同一资源的情况,导致数据冲突,影响数据存储的完整性。为此,提出一种多信道无线通信网络动态数据完整性存储方法。通过计算节点发送与接收的能耗,利用层次聚类算法,结合密度对网络监测区域内全部节点分簇处理,获取感知数据集合,采用最小二乘法采集动态数据,利用优化的谱哈希算法将高维网络动态数据映射为哈希码,利用基于柯西分布的哈希映射,得到概率密度函数,根据映射值间距,实现多信道无线通信网络动态数据完整性存储。通过仿真表明,所提方法的丢包率取值一直处于2%以下,吞吐率逐渐接近于98%,资源占用率最高仅为14.6%,可以获取满意的网络动态数据完整性存储结果。

无线传感器网络的多信道信息融合方法设计

在无线传感器网络组成的物联网中,受并行通信的干扰,导致多信道信息融合效果差、时延高、信息传送能耗大。为此,提出了针对物联网中无线传感器网络的多信道信息融合方法。通过树型拓扑结构合理分配物联网中传感路由节点信道,抑制并行传感通信的干扰。根据信息熵理论,获取各传感信道信息之间的距离差,采用欧氏距离得出各信息单元的距离熵,进行归一化处理,计算出各传感信息单元属性与融合的权重,按照线性加权算法融合各部分的信息,完成多信道信息融合。仿真结果表明:所提方法的多信道信息融合时延和信息传送能耗始终低于0.69 s和59 J,证明所提方法在传感网络多信道信息融合的效果较好,能够有效降低传感信息融合时延,减小传感信息传送能耗。

基于输入通道拆分的无线通信网络对抗攻击多任务防御

在无线通信网络中,由于网络的开放性和共享性,攻击源自多个不同的源头,展现出多种多样的特征。传统的防御方法难以同时应对多种攻击模式,且在处理多模态数据时存在效率低下和准确性不足的问题。为此,研究基于输入通道拆分的无线通信网络对抗攻击多任务防御方法。利用Morlet小波变换将无线通信网络信号转换为时频图像,以输入通道拆分的方式拆分时频图像,得到RGB三个通道的时频图像。在改进注意力机制生成对抗网络内,结合多任务学习建立多防御模型。该模型内生成器通过空间注意力模块与时间注意力长短期记忆网络模块,提取RGB三个通道时频图像的时空特征,并生成对抗样本,通过判别器识别图像类型。检测到攻击时,用对抗样本替换攻击数据,实现无线通信网络的多任务对抗防御。实验证明,该方法可有效将无线通信网络信号转换成时频图像,且有效生成对抗样本,完成无线通道网络对抗攻击多任务防御。

A Monte Carlo Enhanced PSO Algorithm for Optimal QoM in Multi-Channel Wireless Networks

In wireless monitoring networks, wireless sniffers are distributed in a region to monitor the activities of users. It can be used for fault diagnosis, resource management and critical path analysis. Due to hardware limitations, wireless sniffers typically can only collect information on one channel at a time. Therefore, it is a key topic to optimize the channel selection for sniffers to maximize the information collected, so as to maximize the quality of monitoring （QoM） of the network. In this paper, a particle swarm optimization （PSO）-based solution is proposed to achieve the optimal channel selection. A 2D mapping particle coding and its moving scheme are devised. Monte Carlo method is incorporated to revise the solution and significantly improve the convergence of the algorithm. The extensive simulations demonstrate that the Monte Carlo enhanced PSO （MC-PSO） algorithm outperforms the related algorithms evidently with higher monitoring quality, lower computation complexity, and faster convergence. The practical experiment also shows the feasibility of this algorithm.

Survey of multi-channel MAC protocols for IEEE 802.11-based wireless Mesh networks

This paper reviews multi-channel media access control（MAC） protocols based on IEEE 802.11 in wireless Mesh networks（WMNs）.Several key issues in multi-channel IEEE 802.11-based WMNs are introduced and typical solutions proposed in recent years are classified and discussed in detail.The experiments are performed by network simulator version 2（NS2） to evaluate four representative algorithms compared with traditional IEEE 802.11.Simulation results indicate that using multiple channels can substantially improve the performance of WMNs in single-hop scenario and each node equipped with multiple interfaces can substantially improve the performance of WMNs in multi-hop scenario.

Maximizing Networking Capacity in Multi-Channel Multi-Radio Wireless Networks

Providing each node with one or more multi-channel radios offers a promising avenue for enhancing the network capacity by simultaneously exploiting multiple non-overlapping channels through different radio interfaces and mitigating interferences through proper channel assignment. However, it is quite challenging to effectively utilize multiple channels and/or multiple radios to maximize throughput capacity. The National Natural Science Foundation of China（NSFC） Project61128005 conducted comprehensive algorithmic-theoretic and queuing-theoretic studies of maximizing wireless networking capacity in multi-channel multi-radio（MC-MR） wireless networks under the protocol interference model and fundamentally advanced the state of the art. In addition, under the notoriously hard physical interference model, this project has taken initial algorithmic studies on maximizing the network capacity, with or without power control. We expect the new techniques and tools developed in this project will have wide applications in capacity planning, resource allocation and sharing, and protocol design for wireless networks, and will serve as the basis for future algorithm developments in wireless networks with advanced features, such as multi-input multi-output（MIMO） wireless networks.

Channel Aware Opportunistic Routing in Multi-Radio Multi-Channel Wireless Mesh Networks

Opportunistic routing （OR） involves multiple candidate forwarders to relay packets by taking advantage of the broadcast nature and multi-user diversity of the wireless medium. Compared with traditional routing （TR）, OR is more suitable for the unreliable wireless link, and can evidently improve the end to end throughput. At present, there are many achievements concerning OR in the single radio wireless network. However, the study of OR in multi-radio wireless network stays the beginning stage. To demonstrate the benefit of OR in multi-radio multi-channel network, we propose a new route metric -- multi-channel expected anypath transmission time （MEATT）, which exploits the channel diversity and resource of multiple candidate forwarders for OR. Based on the new metric, a distributed Mgorithm named Channel Aware Opportunistic Routing （CAOR） is proposed. The simulation results demonstrate that MEATT improves 1.14 and 1.53 times of the average throughput than existing expected anypath transmission time （EATT）and metric of interference and channel switching cost （MIC） respectively. The average delay of MEATT is 17% and 40% lower than those of EATT, MIC, respectively.

Cross-layer resource allocation in wireless multi-hop networks with outdated channel state information

The cross-layer resource allocation problem in wireless multi-hop networks(WMHNs)has been extensively studied in the past few years.Most of these studies assume that every node has the perfect channel state information(CSI)of other nodes.In practical settings,however,the networks are generally dynamic and CSI usually becomes outdated when it is used,due to the time-variant channel and feedback delay.To deal with this issue,we study the cross-layer resource allocation problem in dynamic WMHNs with outdated CSI under channel conditions where there is correlation between the outdated CSI and current CSI.Two major contributions are made in this work:(1)a closed-form expression of conditional average capacity is derived under the signal-to-interferenceplus-noise ratio(SINR)model;(2)a joint optimization problem of congestion control,power control,and channel allocation in the context of outdated CSI is formulated and solved in both centralized and distributed manners.Simulation results show that the network utility can be improved significantly using our proposed algorithm.

一种多射频多信道的无线传感网络终端设计

随着无线传感网络中节点数量的增加,传统的单路射频通信会出现同频干扰、数据丢失和接收速度慢等问题。为此本文设计了一种基于多射频多信道的无线传感网络终端设备。该设备采用国产微处理器与4路射频连接的分体式架构,对固定信道分配算法进行优化,采用二级星型拓扑结构使得射频同时工作期间不产生干扰,基于频分多址和时分多址相结合的通信协议来解决数据冲突问题。通过对比实验,该终端设备信息处理速率为2008.5 kb/s,系统的丢包率为0.78%,在信道利用率、数据处理速率和系统稳定性方面优于传统单信道设备。

基于融合网络的井下人员行为识别方法

井下人员行为识别是保障煤矿安全生产的重要措施。针对现有井下人员行为识别研究缺少对感知机理的研究与分析且特征提取手段单一的问题,提出一种基于融合网络的井下人员行为识别方法。该方法主要包括数据预处理、特征构建和判识网络构造3个部分。数据预处理:通过信道状态信息(CSI)商模型、子载波去直流和离散小波去噪对采集的CSI数据进行处理,以降低环境噪声、设备噪声等的影响。特征构建:将处理后的数据利用格拉姆和/差角场(GASF/GADF)转换成图像,从而保留数据的空间和时间特性。判识网络构造:根据人员动作的特点,提出一种由基于门控循环单元(GRU)的编解码网络和多尺度卷积神经网络(CNN)组成的融合网络,利用GRU保留前后数据之间的关联性,同时利用注意力机制的权重分配策略有效提取关键特征,以提高行为识别的准确率。实验结果表明:该方法对行走、摘帽子、扔东西、坐、抽烟、挥手、跑动、睡觉8种动作的平均识别准确率为97.37%,对睡觉和坐的识别准确率最高,最容易发生误判的动作是行走和跑动;使用准确率、精确率、召回率和F1分数作为评价指标,得出融合网络的性能优于CNN和GRU,人员行为识别准确率高于HAR系统、WiWave系统和Wi−Sense系统;正常速度下行走和摘帽子2种动作的平均识别精度为95.6%,高于快速动作情况下的93.6%和慢速动作情况下的92.7%;收发设备之间的距离为2 m和2.5 m时,识别准确率较高。

多路采集的高速率无线网络系统设计

针对目前工业无线网络传感节点有效负载数据传输速率慢的问题,设计了一种基于Sub-GHz技术的高速率无线监测网络系统,该系统以超低功耗器件CC1310为硬件核心,采用多路采集的方式减少系统从节点部署。在节点物理层提出了一种通过修改底层射频参数拓展CC1310芯片通信带宽的方法;在数据链路层通过简化数据帧结构、采用直接轮询访问的方式实现射频传输,在保证系统可靠性的情况下提高系统数据传输速率。测试结果表明:当设备节点外接8路传感器时,系统数据传输速率可以达到377 kbps,完全适用于工业无线实时监测系统。

多信道无线网络中优化QoM吉布斯采样信道选择算法

在无线网络中采用专用节点对用户的通信活动进行监测可实现网络的故障诊断和资源管理.由于硬件资源受限,无线节点通常在一个时刻只能工作在一个信道上,因此优化各个节点的信道选择使整个网络收集的用户信息量达到最大,即网络监测质量(QoM)达到最优是一个关键问题.文中提出一种基于吉布斯采样(Gibbs Sampler)的分布式节点信道选择算法.根据优化目标构造了能量函数,以计算各个信道的选择概率,并完成对信道的优化选择.该算法复杂度低,具有可证明的收敛性,大量实验结果表明该算法可以实现无线网络QoM最优化问题的分布式求解,而且解的质量近似达到了集中式算法的性能.

无线Mesh网络逐层信道分配策略研究

网关是整个无线Mesh网络中数据流量汇聚的中心,网关周围的链路干扰将会制约整个网络的上下行吞吐量,然而在目前已有的信道分配方案中在进行信道分配时并未充分考虑到这一特点。提出一种以网关为中心的逐层多信道分配策略,在分配信道时尽可能优先考虑降低网关附件的冲突和干扰,从而达到提高整个网络性能的目标。仿真实验表明,本文算法在提高网络吞吐量方面达到了很好的效果。

无线监测网络中多信道优化选择算法

无线监测网络中多电台监测节点通过捕捉和分析无线用户的通信数据,可以达到监测网络行为、诊断网络故障和管理网络资源的目的,而为多电台监测节点优化选择工作信道、最大化捕获数据量、获得最佳网络监测质量(quality of monitoring,QoM)是一个关键问题。文章研究了一种基于同步微扰随机近似(SPSA)的信道选择算法。该算法在迭代过程中以随机扰动策略得到目标函数的近似梯度,引导搜索过程逐步逼近最优解;适合于复杂的多维优化问题求解,收敛速度快、复杂度低。实验结果表明,该算法可以实现无线监测网络中多电台监测节点的信道优化选择,并且性能优良。

无线Mesh网络信道分配研究

针对多接口多信道无线Mesh网络,提出了一种基于链路负载和链路"潜在的"干扰度的权值的分布式静态信道分配算法。给出基于链路负载和链路"潜在的"干扰度的权值的定义和基于权值的链表的构建方法;阐述了算法的设计思想和实现步骤。仿真实验测试结果表明,该算法不但能适应业务流量分布均匀或不均匀的状态,而且能相应地提高网络吞吐量,提升网络性能。

集中式无线Mesh网络信道分配策略研究

针对无线Mesh网的部署特点,对其信道分配策略的设计难点进行了阐述,将集中式信道分配策略分为基于图论、基于网络流理论和基于网络分区的三种类型,并对上述各类方法的现状和进展进行了介绍、分析和探讨。最后对集中式信道分配策略的研究进行了总结和展望。

多信道无线Mesh网络公平带宽分配算法

针对基于IEEE802.11的无线Mesh网络(WMN)在按多跳方式转发数据时存在带宽分配不公平的问题,提出一种改进算法DBAS。通过检测子节点包含的活动终端数量,计算分配指数并发送给子节点,使其能根据分配指数调整介质访问控制层的竞争窗口参数。在子节点向父节点发送数据时,采用加权轮询调度算法进一步保证带宽分配的公平性。NS2实验结果验证该算法的有效性。

联合速率控制与功率分配的多信道无线网络跨层优化

本文基于凸优化方法,以提升网络效用与降低网络总功耗为目标,针对多无线多信道(Muhi-radio Multi-channel)的多跳无线网络提出了一种联合速率控制与功率分配的跨层优化模型,并利用对偶分解方法设计了优化模型对应的分布式算法,证明了该分布式算法收敛性.该算法通过改变本征权的取值能够在网络效用与网络功耗之间取得折衷,并能根据速率要求动态调整各条链路的注入速率与发射功率使得网络达到效用与功耗的联合最优.通过仿真实验验证了该分布式算法可有效的调节网络效用与总功耗之间的平衡.