异构无线网络中基于SINR和层次分析法的SAW垂直切换算法研究

B3G或者4G无线网络体系致力于集成各种异构无线接入网络,其中一个主要的设计课题是支持垂直切换的研究。该文将多属性QoS考虑在内,针对各业务特点,提出一种基于SINR(信干噪比)和层次分析法(AHP)的SAW(简单加权法)垂直切换算法(SASAW)。它综合考虑SINR的影响以及要获得同等数据速率情况下,目标网络需要的等效SINR数值、用户通信代价、网络可用带宽等来构造属性矩阵做切换判决。为了评估性能,考虑3GPP定义的4类业务,利用层次分析法中的特征向量法来决定各个QoS属性之间的权重关系,构造比较判决矩阵并检验其一致性;根据判决矩阵,利用特征根法获得权重向量;最后根据属性矩阵和权重向量,利用SAW垂直切换算法进行判决。通过对算法的通过率、丢话率、垂直切换次数、平均用户代价等的性能比较,结果表明该文提出的算法能够根据各业务特点综合考虑各属性间关系,获得优良的系统性能。     

一种基于业务切换的垂直切换判决算法

在下一代异构无线网络环境中,为满足在异构无线网络架构下采用不同切换方式的垂直切换请求,我们提出一种基于业务切换的垂直切换判决算法,并设计了一种基于业务切换的代价函数。通过数学分析和在UMTS,WLAN融合的网络环境下对该方案的切换失败率的仿真分析,证明了该方案在支持终端的移动性、保障用户业务请求满意度以及缓解网络负载压力上相比传统基于代价函数的垂直切换判决算法更具优势。     

基于改进TOPSIS的配用电通信网性能评估方法

针对传统的层次分析法的不足,研究了多指标综合评估系统中指标权重的确定问题,并提出一种基于改进TOPSIS的配用电通信网性能评估方法。该方法将SAW方法、TOPSIS方法与改进的AHP方法相结合对配用电通信网进行综合评估,并针对TOPSIS方法无法对中垂线上的数据进行处理的问题,提出了新的基于相对熵的TOPSIS方法。仿真结果表明,改进的TOPSIS方法更适合对指标敏感的配用电网络进行评估。     

基于异构网络上下文感知垂直切换判决策略的研究

为了解决车载移动终端在异构网络环境下无缝切换的问题,采用层次分析法和简单加权法,分析了垂直切换过程中目标发现、切换决策和切换执行三个关键阶段存在的问题,并提出了一种基于上下文感知的垂直切换判决策略。通过实验验证,表明了该方法能有效地改善异构网络环境中切换时延和吞吐量等方面的问题。     

异构无线网络中基于权重平衡的接入选择算法

下一代异构无线网络中,用户业务需求将会更加多样化。针对目前网络接入算法在确定判决属性权重时存在片面性问题,文章提出了一种基于权重平衡的接入选择算法,首先利用改进的层次分析法获取判决属性的主观权重,同时通过熵值法获取属性的客观权重,然后对主客观权重进行平衡处理,最后将得到的综合权重通过简单加权法对各网络进行综合评价以及确定目标接入网络。仿真结果表明,该算法能在满足用户业务需求的基础上,准确地接入最优网络,同时减小“乒乓效应”带来的影响,提高了网络的性能。     

异构无线网络的自适应垂直切换判决算法

在未来的异构环境中,网络间的垂直切换将对QoS保证产生重要影响。针对移动终端在异构网络间切换不理想的问题,提出了一种自适应的垂直切换判决算法。采用基于用户多应用的代价函数对接入网络进行评估与选择,综合考虑移动终端当前的电池电量,判断当前业务是否需要进行网络切换,使移动终端能自适应地进行切换判决。仿真结果表明,该算法可以有效地延长移动终端的工作时间,减少乒乓效应,提高系统的切换性能,改善业务的QoS。     

基于用户偏好的异构网络选择算法研究

针对当前大多数网络选择算法没有充分考虑用户基于业务的网络偏好这一问题,提出了一种基于用户偏好的异构网络选择算法。该算法充分考虑业务需求、用户偏好及网络性能差异,通过层次分析法和距离分析法分别计算用户对各候选网络的主观和客观偏好权重,根据用户策略动态确定综合权重,并由此结合各属性权重计算网络性能,选出最优网络。仿真结果表明该算法可以准确选择接入网络,并当用户在网络边缘做兵乓运动时有效减少切换次数。     

基于多网并行传输技术的海上异构网络接入算法

针对海上异构无线网络中网络接入选择算法存在干扰环境适应性不强、单网传输效率低、业务完成率低的问题,提出了一种基于多网并行传输的海上异构网络接入选择算法。该算法在满足多属性决策的基础上,采用效用函数对网络属性值进行数值标准化,再采用改进的逼近理想值排序(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)法计算出备选接入网络方案的排序,最后选择排序靠前的网络进行接入。仿真结果表明该算法相对于传统TOPSIS算法和模拟人工切换算法能有效降低接入成本,改善用户服务质量,提高业务完成率。     

基于主客观权重的异构网络选择算法

为解决在异构网络环境选择最佳的接入网络问题,提出一种结合综合赋权的异构网络选择算法。在用户端采用层次分析法判断用户偏好,在网络端采用基于指标相关性的客观赋权法判断网络客观状态,并结合基于离差极小化的综合赋权法得到最终权重,同时运用理想值近似排序法进行网络排序,接入最佳网络。基于Matlab的仿真结果表明,该方法能根据不同业务结合网络性能及用户需求选择最佳的接入网络,减少了频繁切换,提高了网络选择结果的合理性与有效性。     

基于区间标记判决的稳健垂直切换算法研究

在异构5G网络中,针对切换算法稳健性差引起的切换准确率低的问题,提出一种基于区间标记判决的稳健垂直切换算法.首先,引入中位值平均滤波法,获取更准确的网络参数.其次,基于参数波动特征分析,提出区间标记判决算法,保证候选网络筛选通过率和准确率的同时,提高区间标记判决算法的稳健性.再次,根据移动终端传输层需求,结合终端运动趋势,分别使用不同权值的效用函数获得最佳目标网络.最后,仿真结果表明,该算法能够有效提升切换触发和网络筛选的准确率,降低切换失败率和乒乓效应,提高系统吞吐量,并能够根据移动终端的需求选择最佳目标网络.     

Vertical handoff decision in 4G wireless networks using multi attribute decision making approach

Multi-interface terminal in heterogeneous wireless networks will have network access from diverse access technologies. Multiple attribute for decision making including user preference will increase the complexity of handoff process. Various approaches have been proposed to solve the complexity problem of handoff decision. In this paper, multi attribute decision making algorithms Analytic Hierarchy Process (AHP) method, Simple Additive Weighting (SAW), Total Order Preference by Similarity to the Ideal Solution (TOPSIS), and Grey Relational Analysis (GRA) methods have been proposed for handoff decision in a WiMAX–WLAN environment to facilitate user with better quality of service. AHP has been used for calculation of weights of decision parameters. Numerical results show that SAW, TOPSIS and GRA provide almost similar performance. SAW is very simple to implement but probability of error is less in GRA because values of decision attribute are directly used for ranking of alternatives. TOPSIS is sensitive to the attribute with high score.     

基于模糊逻辑的多终端协同的垂直切换决策算法

针对异构网下多终端协同的垂直切换决策问题,提出一种基于模糊逻辑和层次分析法的垂直切换决策算法,它分为2部分:切换时机的判断和虚拟终端的构建.首先采用模糊逻辑判断切换的时机,然后采用层次分析算法与简单加权求和结合的方法选择虚拟终端的最优构成方式.仿真结果表明,算法能够降低切换次数和不必要切换率,并且能够充分体现应用需求和用户偏好.     

A genetic algorithm approach for multi-attribute vertical handover decision making in wireless networks

Mobile terminals can typically connect to multiple wireless networks which offer varying levels of suitability for different classes of service. Due to the changing dynamics of network attributes and mobile users’ traffic needs, vertical handovers across heterogeneous networks become highly desirable. Multiple attribute decision making (MADM) techniques offer an efficient approach for ranking competing networks and selecting the best one according to specific quality of service parameters. In this paper, a genetic algorithm (GA) is applied to optimize network attributes’ weighting by emphasizing ranking differences among candidate networks, thereby aiding correct decision making by reducing unnecessary handovers and ranking abnormalities. The performance of the proposed GA-based vertical handover is investigated with typical MADM techniques including Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The results show that the proposed GA-based weight determination approach reduces the abnormality observed in the conventional SAW and TOPSIS techniques substantially. The results of this paper will help ensuring the application of MADM methods to more dynamic and challenging decision making problems encountered in wireless network.     

A new handoff management system for heterogeneous wireless access networks

In heterogeneous wireless access networks, each mobile terminal may frequently need to change its base station (BS); this change is called a ‘handoff’. BSs have static parameters, which are related to their radio access technologies (RATs); however, they also contain dynamic parameters such as load and signal quality. Therefore, the problem of handoff decision includes two subproblems of RAT selection and BS selection. In this paper, first a ‘heterogeneous handoff management system’ for gathering all different required parameters is proposed. Second, a RAT Selection algorithm based on analytic hierarchy process and a BS Selection algorithm based on data envelopment analysis are designed. Finally, by means of ‘weight restriction’ technique, we develop a method for studying the impact of RAT Selection parameters on the performance of the network. Simulation results indicate that RAT Selection parameters have significant impact on the bandwidth utilization, energy consumption and the whole satisfaction of the users in heterogeneous wireless access networks.Copyright © 2012 John Wiley & Sons, Ltd.     

一种LTE与WLAN间垂直切换新算法

为提高用户在异构网络中的服务质量(QoS),减少切换产生的乒乓效应,文中提出了一种LTE和WLAN网络垂直切换新算法。该算法考虑了衰落对接收信号强度(RSS)的影响,基于RSS选出目标网络,根据用户移动速度并结合代价函数选出最佳网络,代价函数中采用了层次分析法来确定时延、资费和用户偏好等参数的权重。仿真结果表明,文中所提的垂直切换算法有效降低了“乒乓效应”,并提高了通信网络的服务质量。     

Artificial Neural Network Based Vertical Handoff Algorithm for Reducing Handoff Latency

One of the most challenging topics for next generation wireless networks is vertical handoff concept since several wireless technologies are assumed to cooperate. Plenty of parameters related to user preferences, application requirements, and network conditions, such as; data rate, service cost, network latency, speed of mobile, battery level, interference ratio and etc. must be considered in vertical handoff process along with traditional RSSI information. In this study, a new artificial neural network based handoff decision algorithm is proposed in order to reduce the handoff latency of smart terminal deployed in aforementioned wireless heterogeneous infrastructures. The prominent parameters data rate, monetary cost and RSSI information are taken as inputs of the developed vertical handoff decision system. Performance results of the proposed system are also compared with those of classical Multiple Attribute Decision Making method Simple Additive Weighting, and of some other artificial intelligence based algorithms. According to the results obtained, the proposed neural network based vertical handoff decision algorithm is able to determine whether a handoff is necessary or not properly, and selects the best candidate access network considering the abovementioned parameters. The results also show that, the neural network based algorithm developed significantly reduces the handoff latency while the number of handoffs, which is another vital performance metric, is still reasonable.     

无线异构网络中带有动态权值的新型垂直切换算法

In order to enhance the quality of vertical handoff in an overlay wireless network, multiple attributes are taken into account when optimizing the vertical handoff decision including user-based and network-based QoS factors. In this paper, we develop a novel vertical handoff algorithm in an integrated 3G cellular and Wireless LAN networks. The proposed algorithm can adjust the weight of each QoS attribute dynamically as the networks change, trace the network condition and choose the optimal access point at transient regions. Simulation results show that this algorithm is able to provide accurate handoff decision, resulting in small unnecessary handoff numbers, good performance of throughput and handoff delay in heterogeneous environments.     

车辆异构网络中预测垂直切换算法

在车辆异构网络中,针对垂直切换决策时刻之后网络状态的动态变化,提高切换性能问题,提出一种基于马尔可夫过程的预测垂直切换(M-VHO)算法。算法考虑了切换决策后网络状态的动态变化对车辆终端服务质量(QoS)的影响。其基本思路是:在需要垂直切换时,利用马尔可夫过程的转移概率预测未来网络状态的变化;另外,采用模糊逻辑方法确定评价属性参数权重;最后,比较切换决策、切换执行和切换之后时刻的总收益来优化选择最佳切换网络。仿真结果证明,该算法在确保较高负载均衡的情况下,可有效改进车辆终端的平均阻塞率及丢包率,降低乒乓效应,确保了车辆终端的QoS。