异构无线网状网分布式接口和信道联合分配的研究*

研究了无线网状网络中分布式分配信道时,接口异构对网络容量的影响。提出了一种新颖的以射频链路为信道分配对象的接口和信道联合分配ILP模型,给出了一种自适应于网络流量变化的分布式贪婪算法。该算法以射频链路为信道分配对象,基于2-hop干扰模型,以队列长度为权的射频链路吞吐量之和最大为目标,寻找自适应流量变化的分布式分配方案。分析发现,该算法与目前已有的非接口异构的Dist. Greedy算法的时间复杂度相当,仿真结果表明本算法下的网络性能有明显提升。     

无线局域网分布式自适应信道分配

提出一种分布式自适应信道分配算法,利用全面的动态网络信息增加信道选择的正确性,引入退避机制减少信道分配中的冲突开销。在网络仿真平台NS2上对算法进行大量实验。结果表明,与传统分布式信道分配算法相比,该算法具有干扰检测率高、可靠稳定的特点,从而有效提高网络整体吞吐量。     

一种混合信道分配算法的研究与仿真

为了提高无线网状网络的链路容量,提出一种在网络中配置节点多射频多信道的混合信道分配算法.通过配置默认信道并优化默认信道的使用,该算法基于启发式信道分配策略来减小链路干扰提升链路容量.基于网络物理拓扑,该算法生成简化的网络逻辑拓扑,使得信道分配方案能够结合路由优化网络性能.对信道分配的动态调整,确保了网络容量的实时优化.仿真结果显示,本信道分配算法可以有效地提升网络性能.     

基于初始化AP的自适应信道分配算法

在高密度AP部署的网络环境中,由于ISM频带只有1、6和11三个正交信道,因此AP的工作信道不可避免的存在重叠,其重叠信道干扰对吞吐量有较大的影响。文中从基于AP上线时为其分配信道的角度出发,提出了一种集中式自适应信道分配算法DNAF（ Densest Nearest Assignment First）。在大量AP刚上线时,通过周期性广播扩展信标帧,建立动态的网络拓扑结构图,并通过AC为其进行优化信道分配。通过对信道分配算法的大量实验及仿真,结果表明,在高密度且AP邻居分布不均匀的网络环境下,与启发式算法NOFA-1及随机信道分配算法相比,该算法能有效地减小邻居间干扰,从而达到提高网络吞吐量的目的。     

OFDM系统中自适应比特和功率分配研究

提出了一种改进的OFDM系统中自适应比特功率分配算法.该算法可适用于多径频率选择性衰落信道,根据信道特征,动态地为OFDM系统的各子信道分配比特和发送功率.该算法在一定的误比特率和信息速率的情况下,使得总发送功率最小化.仿真结果表明,算法在相同误比特率的情况下比不采用自适应技术的OFDM系统节省了发送功率.     

一种新的MIMO-OFDM通信系统比特分配方案

从MIMO-OFDM系统模型出发,首先对理想信道传输矩阵进行奇异值分解,在子信道自适应调制设计中应用信道矩阵特征值把空分复用信道转化为并行子信道,将用于多载波自适应比特分配算法应用于MIMO-OFDM系统。然后以实现系统发射功率最小为原则,以降低系统比特分配算法复杂度为目标,提出了一种可变步长的子信道比特分配优化算法。仿真结果表明,这种算法不但可以实现和Campello方法相当的比特分配性能,还可以较大地降低系统的计算复杂度。     

数据广播调度自适应信道划分与分配方法

随着移动网络的不断发展,移动终端设备的计算能力与日俱增,越来越多的用户倾向于通过移动网络获取信息资源,这使得实时按需数据广播面临新的挑战：（1）数据内容和规模的多样化;（2）用户请求的实时性与需求多样性使得热点数据增加,直接导致广播数据总量的剧增;（3）用户对服务质量和水平的要求越来越高.当前的研究成果主要集中在固定信道模型和算法上,一定程度上忽略了当前数据广播调度环境的变化.固定信道存在如下问题：（1）局限于特定的网络,缺乏通用性;（2）信道大小、个数不能随着网络环境的变化而自动调整,降低了广播效率.基于以上考虑,对实时按需数据广播调度的自适应信道划分和分配进行研究,提出一种自适应信道划分与分配方法OCSM （optimized channel split method）,其根据数据请求特征的不同,实时自适应地调整信道个数和大小,从而提高系统敏感性、鲁棒性以及广播效率.该方法包括：（1）广播数据均衡聚类算法WASC （weight average and size clusteralgorithm）,其挖掘数据特征,为信道划分提供依据;（2）数据项广播优先级评定算法R×W/SL,其实时评定数据项调度优先级;（3）信道划分与分配算法CSA （channel split algorithm）.实验包括两个方面：（1）确定不同数据项大小和请求截止期分布下的信道划分策略,并分析聚类算法中聚类距离K在不同情况下的最佳取值以及最佳信道划分;（2）验证自适应信道划分与分配策略的有效性,并通过对比实验验证在不同情况下OCSM的有效性.实验结果表明：OCSM优于其他调度算法,并具有较强的自适应.     

基于粒子群算法的无线信道资源分配算法研究

为了 最大化 多媒体无线信道资源分配的网络效用,提出了一种新的基于粒子群算法的信道时间分配算法。该算法能够优化分配给网络内每个设备的时间,以便为每位网络用户 提供最优化的服务质量(QoS)。所提算法结合了多样性增加函数以及基于个体最优值的学习方法,并基于自适应粒子群算法进行了改进,在持续增强QoS的同时加快了收敛速度。在多达40个设备的千兆网络环境内对所提算法进行了测试。实验结果表明,提出的算法能够大大提升资源分配能力,尤其是在网络规模较大的情况下。     

城市车辆网络下一种基于道路划分的多信道分配算法

城市车辆网络下多信道分配问题是指在城市车辆网络中,每个节点配置多个网卡,如何调节每个网卡使其在可用的正交信道(如802.11a可用12个正交信道,802.11b/g可用3个正交信道)之间进行切换以充分利用多个信道而达到减少节点之间的干扰和提高网络吞吐量的问题.本文提出了一种适用于网络拓扑具有高度动态性的城市车辆网络的基于道路划分的多信道分配算法(mimc-road).该算法按照道路划分进行多信道分配,将一个二维网络多信道问题简化为以一维空间为主的多信道分配问题,并将基于动态网络链路的信道分配问题转化为基于静态道路的信道划分问题.模拟实验结果表明:对比传统单信道单网卡模式和fix-switch算法,mimc-road算法显著提高了车辆网络的性能.     

无线Mesh网络中基于局部信息的自适应信道分配策略

在多无线接口多信道的无线Mesh网络中,信道分配问题将影响网络的整体性能。为充分利用无线Mesh的资源优势,已提出了许多信道分配策略。然而,大部分的研究假设都隐含需要全网拓扑或者流量模型等信息,这在分布式网络中很难准确获取。为此,本文提出基于局部信息的自适应信道分配策略LICA,在仅使用局部拓扑和节点间信道使用情况等启发式信息的基础上,动态指导信道分配。模拟实验结果表明,LICA算法能显著提高信道利用效率和端到端的数据吞吐量,且具备较低的时间复杂度和良好的可扩展性。     

IEEE 802.11宽带无线局域网负载均衡优化研究*

在基于IEEE 802.11的宽带无线局域网中,随着终端STA的接入、移动和无线信道的时变性,各个接入点（AP）的负载将会产生差异,需要负载均衡优化机制平衡各个AP的差异,以达到网络资源的最大利用率。详细讨论了无线局域网中用到的几种负载均衡机制,分析了各自的优缺点,结合这些特点给出一种新的负载均衡机制。该机制能较准确地统计终端业务信息,降低切换失败风险,快速达到APs之间的负载均衡,优化提高网络整体性能。     

On spectrum sharing games

Efficient spectrum-sharing mechanisms are crucial to alleviate the bandwidth limitation in wireless networks. In this paper, we consider the following question: can free spectrum be shared efficiently? We study this problem in the context of 802.11 or WiFi networks. Each access point (AP) in a WiFi network must be assigned a channel for it to service users. There are only finitely many possible channels that can be assigned. Moreover, neighboring access points must use different channels so as to avoid interference. Currently these channels are assigned by administrators who carefully consider channel conflicts and network loads. Channel conflicts among APs operated by different entities are currently resolved in an ad hoc manner (i.e., not in a coordinated way) or not resolved at all. We view the channel assignment problem as a game, where the players are the service providers and APs are acquired sequentially. We consider the price of anarchy of this game, which is the ratio between the total coverage of the APs in the worst Nash equilibrium of the game and what the total coverage of the APs would be if the channel assignment were done optimally by a central authority. We provide bounds on the price of anarchy depending on assumptions on the underlying network and the type of bargaining allowed between service providers. The key tool in the analysis is the identification of the Nash equilibria with the solutions to a maximal coloring problem in an appropriate graph. We relate the price of anarchy of these games to the approximation factor of local optimization algorithms for the maximum k-colorable subgraph problem. We also study the speed of convergence in these games.     

Performance model for IEEE 802.11s wireless mesh network deployment design

This paper presents a performance model developed for the deployment design of IEEE 802.11s Wireless Mesh Networks (WMN). The model contains seven metrics to analyze the state of WMN, and novel mechanisms to use multiple evaluation criteria in WMN performance optimization. The model can be used with various optimization algorithms. In this work, two example algorithms for channel assignment and minimizing the number of mesh Access Points (APs) have been developed. A prototype has been implemented with Java, evaluated by optimizing a network topology with different criteria and verified with NS-2 simulations. According to the results, multirate operation, interference aware routing, and the use of multiple evaluation criteria are crucial in WMN deployment design. By channel assignment and removing useless APs, the capacity increase in the presented simulations was between 230% and 470% compared to a single channel configuration. At the same time, the coverage was kept high and the traffic distribution fair among the APs.     

Distributed channel assignment algorithms for 802.11n WLANs with heterogeneous clients

As the latest IEEE 802.11 standard, 802.11n applies several new technologies, such as multiple input multiple output (MIMO), channel bonding, and frame aggregation to greatly improve the rate, range and reliability of wireless local area networks (WLANs). In 802.11n WLANs, access points (APs) are often densely deployed to provide satisfactory coverage. Thus nearby APs should operate at non-overlapping channels to avoid mutual interference. It is challenging to assign channels in legacy 802.11a/b/g WLANs due to the limited number of channels. Channel assignment becomes more complex in 802.11n WLANs, as the channel bonding in 802.11n allows WLAN stations (APs and clients) to combine two adjacent, non-overlapping 20MHz channels together for transmission. On the other hand, IEEE 802.11n is backward compatible, such that 802.11n clients will coexist with legacy clients in 802.11n WLANs. Legacy clients may affect the performance of nearby 802.11n clients, and reduce the effectiveness of channel bonding. Based on these observations, in this paper, we study channel assignment in 802.11n WLANs with heterogeneous clients. We first present the network model, interference model, and throughput estimation model to estimate the throughput of each client. We then formulate the channel assignment problem into an optimization problem, with the objective of maximizing overall network throughput. Since the problem is NP-hard, we give a distributed channel assignment algorithm based on the throughput estimation model. We then present another channel assignment algorithm with lower complexity, and aim at minimizing interference experienced by high-rate, 802.11n clients. We have carried out extensive simulations to evaluate the proposed algorithms. Simulation results show that our algorithms can significantly improve the network throughput of 802.11n WLANs, compared with other channel assignment algorithms.     

On the wireless local area network design problem with performance guarantees

In this paper, we propose a model for the wireless local area network (WLAN) design problem with performance guarantees. This problem consists of selecting the location of the access points (APs) as well as the power and the channel of each AP. The performance guarantees we refer to are coverage and minimum bandwidth guarantees. Since this problem is -hard, we propose a tabu search algorithm to find solutions for real-size instances of the problem. Finally, numerical results are presented. The results show that good solutions can be found with the proposed algorithm in a reasonable amount of time.     

一种用户需求感知的无线接入点关联策略

在无线局域网中,接入点(access point,简称AP)的稠密部署使得AP的关联策略成为一个重要的研究问题.目前,用户与AP的关联仅依据AP的信号强度,然而,这种方法未能考虑到网络中AP的异构性,以及不同用户对资源(例如带宽、安全性、时延等)的不同需求,并且分布式的AP关联会造成网络中AP负载的不均衡.针对以上问题,基于软件定义网络(software defined network,简称SDN)技术提出一种集中式的AP关联策略模型.该模型同时考虑了网络管理员和用户的目标,对网络负载均衡和用户资源满足度同时进行优化.采用蚁群算法对模型进行求解,并通过仿真实验对算法进行验证.实验结果表明,针对随机生成的数据集,用户资源满足度可由54.5%分别提升至86.8%(重负载时)和94.1%(轻负载时),并且管理员目标(负载均衡)得到了明显的改善.     

Efficient multicasting over large-scale WLANs through controlled association

Support for efficient multicasting in WLANs can enable new services such as streaming of TV channels, radio channels, and visitor’s information. With increasing deployments of large-scale WLANs, such services can be made available to a large number of users. However, any new multicast based services must minimally impact the existing unicast services which are currently the core services offered by most WLANs. In this paper, we leverage the flexibility of associating with different access-points (APs), which occurs often due to overlapping coverage of APs, to optimize the network’s objective. Motivated by different revenue functions and network scenarios, three different optimization objectives are considered which are: maximizing the number of admitted users (MNU), balancing the load among APs (BLA), and minimizing the load of APs (MLA). We show that these problems are NP-hard and present centralized approximation algorithms and distributed approaches to solve them. These algorithms compute which AP a user should be associated with. Using simulations we evaluate their performance and compare them to a naive approach in which users associate to the AP with the best RSSI (Received Signal Strength Indicator).     

无线公交车载网络切换机制研究

为公交车乘客提供高质量的Internet服务可以让其在乘车过程中享受娱乐及工作,进而大大提高乘客的生活质量。基于此,本文针对公交车载网络的切换问题进行研究。首先提出一种改进的公交车载网络结构,进而提出一种基于数据传输速率的切换触发机制。该机制可以准确触发切换,减少切换开销,改进通信稳定性。针对公交站点存在多个访问点的切换场景,本文进一步提出一种合适的切换策略-M-Handoff。M-Handoff以负载均衡为目标进行访问点选择,同时可以保证各个已连接的公交车辆的平均吞吐率。仿真实验表明,与传统方法相比,以上机制可以较好地提高系统性能,能更好地适于公交车载通信。     

Channel measurement-based access point selection in IEEE 802.11 WLANs

With the wide deployment of IEEE 802.11 Wireless Local Area Networks, it has become common for mobile nodes (MNs) to have multiple access points (APs) to associate with. With the Received Signal Strength Indicator (RSSI)-based AP selection algorithm, which is implemented in most commercial IEEE 802.11 clients, the AP with the best signal strength is selected regardless of the candidate AP’s available throughput, resulting in unbalanced distribution of clients among the APs in the network. Several studies have shown performance improvement in not just the new MN (nMN), but also the network as a whole when the selection process considers the current load status of candidate APs. However, the proposed algorithms in these studies assume that there are no hidden terminal problems that severely affect the performance of the network. Hidden terminal problems frequently occur in wireless networks with unlicensed frequencies, like IEEE 802.11 in the 2.4 GHz band. Moreover, none of the previous studies have considered frame aggregation, a major improvement in transmission efficiency introduced and widely deployed with the IEEE 802.11n standard. In this paper, we propose a new AP selection algorithm based on the estimation of available throughput calculated with a model based on the IEEE 802.11 distributed coordination function in consideration of hidden terminal problems and frame aggregation. The proposed algorithm is evaluated through extensive simulation, and the results show that the nMN with the proposed AP selection algorithm can achieve up to 55.84% and 22.31% higher throughput compared to the traditional RSSI-based approach and the selection algorithm solely based on the network load, respectively.