一种超密集网络基站分簇管理算法

为了降低超密集网络中基站管理算法的计算复杂度并提升基站的能源使用效率,根据用户密度、网络负载量等信息,提出了一种基于分簇的动态管理基站算法.该算法首先根据用户测量报告计算出理论最小需求基站数,然后对基站进行合理的网络分簇,最终通过粒子群优化算法确定基站休眠组合.仿真结果表明,与未进行分簇的基站管理算法相比,该算法可以降低约60%的计算复杂度,并能有效降低基站能源消耗.     

超密集小峰窝网中基于干扰协调的小区分簇和功率分配算法

干扰的有效管理是超密集小蜂窝网中的一个研究难点。该文提出将超密集小蜂窝网中的小区干扰协调和分簇相结合的算法,通过分配最优的功率降低干扰,最大化系统吞吐量。根据干扰的程度,将干扰强的小蜂窝划为一个簇,同一个簇内的小蜂窝共享频谱资源,协作为用户服务,簇与簇之间实现频谱复用。仿真结果表明,该算法在网络密集部署时,有效地减小干扰,提高系统吞吐量。     

基于区域感知贝叶斯决策的5G超密集异构网络联合垂直切换技术研究

针对无线通信异构网络切换中最优接入网的选择问题,现有研究主要集中于解决在两个网络间选择切换,而对于未来5G（5th Generation）通信系统中超密集网络的切换问题研究较少.本文就研究了5G无线通信系统中超密集异构网络的选择切换.文中提出了一种基于区域感知贝叶斯决策的联合垂直切换方式,该方案通过选择超密集异构接入网络的最优切换概率从而解决超密集网络切换问题.通过对移动用户（mobile station）从宏基站进入超密集服务小区,以及在小区内和小区间移动的不同场景进行仿真分析,研究结果表明本文决策方式能够准确地选择要切换的网络,因而该方案能够适用于超密集网络的应用场景.     

超密集分簇网络中基于马尔可夫模型的移动性能建模与分析

第五代移动通信(5G)系统中,大规模MIMO天线和超密集部署网络是实现高吞吐量的两种主要方法。在超密集部署网络中,将小蜂窝的基站按照地域位置和信号强度等条件进行分簇,簇内所有的小蜂窝共用同一控制平面,实现了业务和控制的分离。基于此场景,提出了基于马尔可夫模型对移动终端在超密集分簇网络下的移动状态进行建模,推导出系统吞吐量、阻塞概率等系统性能的闭式表达式。仿真结果表明超密集分簇网络可以有效地减少移动终端不必要的切换次数,并提高系统吞吐量。     

超密集网络以用户为中心及多维协作的用户分簇算法

为了降低超密集网络中小区间的干扰,提升频谱效率,给出一种在以用户为中心的可重叠虚拟小区场景下,基于边权重和贪婪树增长(Greedy Tree Growing Algorithm,GTGA)算法的用户分簇方案.考虑到每个用户对其他用户产生干扰的同时,又受到其他用户的干扰,权重设计采用协作传输的平衡策略.针对用户分簇,改进的K-means聚类算法通过能够拟合高斯分布的权重统计量来动态调整用户分群的大小.仿真结果表明,所提算法能有效地降低复杂度,减少干扰,提高超密集网络的频谱效率.     

面向5G超密集异构网络的模糊逻辑切换算法

针对基站之间距离近、网络数量庞大的超密集网络中切换过程存在干扰以及频繁切换问题，提出了一种基于预判决的模糊逻辑切换算法。算法在计算用户接收信号的信干噪比基础上，预筛选出干扰较小的网络，计算用户在筛选出的候选网络中的停留时间，当停留时间大于门限值时对候选网络使用基于模糊逻辑的逼近理想解排序算法。通过模糊逻辑优化网络属性参数，进而使用逼近理想解排序算法对候选网络进行排序。排序过程中，使用修正后的贴近度计算方式使计算结果更加精确。仿真实验证明，该算法在超密集异构网络切换中可以有效降低切换次数，减少网络阻塞概率，有效提升用户服务质量。     

超密集网中一种基于人工蜂群的节能分簇算法

超密集网络中,密集部署的低功率基站将会加大系统的能耗,并且造成紧缺频谱资源的浪费.探寻干扰协调和系统节能的可行性方法在超密集网络架构下提出基站的休眠—唤醒—活跃机制,减小了休眠基站直接转为活跃状态的开启时间;另外,提出一种基于人工蜂群染色分簇算法,尽可能使用最少的颜色给拓扑图中的小区染色,并对簇内活跃基站进行优化功率分配.经仿真表明,休眠—唤醒—活跃机制能够提升系统的能源效率,染色分簇算法也可以改善用户的频谱效率和吞吐量.     

基于用户分簇的认知超密集网络资源分配

针对5G时代小基站的密集部署带来的复杂干扰问题,对下行的认知无线电超密集网络下的资源分配进行了研究。为减小网络干扰,提高次用户吞吐量,提出了一种改进的基于用户分簇的资源分配算法。基于基站的覆盖范围,选出用户的强干扰基站,以用户-基站干扰关系建立用户-用户干扰图,按用户受到的平均弱干扰划分优先级对用户分簇,再为簇集群预分配频段,为每个簇分配对应频段中效用最大的信道。该资源分配算法能准确反映用户间的干扰关系,保障资源分配公平性。仿真结果表明,当用户密度与基站密度均较大时,与相同场景的已有算法相比,该改进算法有较好的抗干扰能力,能有效提高次用户的吞吐量。     

超密集小区中基于二分图优先级的资源分配算法

由于在超密集网络中小基站密集的部署,用户数据量空前增加,对数据速率的要求不断提高,所以在有限的资源下如何高效地将资源分配给用户尤为重要。提出了一种小区分簇算法,根据小区簇的通信业务、通信负载量等条件将各个小区分为不同的优先级,引入二分图,以小区簇的优先级为依据建立频谱资源与小区簇之间的匹配关系,并提出一种低复杂度的贪婪算法。仿真结果表明所提算法能够有效提高系统性能,并且有效完成频谱资源的分配。     

基于区间二型模糊神经网络的垂直切换算法

在超密集异构无线网络中,针对传统垂直切换算法无法同时描述网络状态的模糊性和随机性,导致网络性能得不到有效提升的问题,提出一种基于区间二型模糊神经网络的垂直切换算法.重构了两阶段判决算法:在网络预筛选阶段,定义了历史接入率,结合当前候选网络集的数目设置阈值.根据接收信号强度和剩余可用带宽,对用户接收范围内的所有网络进行初步筛选;再在垂直切换判决阶段,将剩余候选网络的时延,丢包率以及误码率作为区间二型模糊神经网络的输入,利用前馈神经网络的结构完成模糊逻辑推理,经训练之后计算得到输出判决值,从而选择最佳接入网络.实验结果表明,该算法能在保证时间开销较低的同时,有效降低切换决策的错误概率,减少切换失败和切换次数,提升网络总吞吐量.     

Weighted Graph Based Clustering and Local Mobility Management for Dense Small Cell Network with X2 Interface

Along with the surge in mobile data, dense small cell network has become an effective method to improve system capacity and spectrum efficiency. However, because more small cells are deployed, the interference among dense small cells exacerbates. It also makes frequent handover for mobile users (UEs), which brings a great deal of signaling overhead to the core network. In order to solve the problems of interference and frequent handover, a novel clustering scheme for dense small cell network is proposed in this paper. The scheme is based on the weighted graph. First, we present a dense small cell clustering model based on X2 interface to minimize core network signaling overhead. To improve the usability of the model, we model the system as an undirected weighted graph. Then we propose the maximum benefit merging algorithm to reduce the complexity. This method enables adjacent small cells to cooperate and form virtual cellular cluster according to handover statistics information. Then we select cluster head (CH) according to certain rule in each cluster. Cluster head acts as the mobility anchor, managing the handovers between cluster members. This can reduce core network signaling overhead and the interference among small cells effectively. Compared with the 3GPP handover algorithm, the proposed clustering model in this paper can reduce the signaling overhead more than 70%. The simulation results show that the proposed clustering model can effectively cluster the dense small cell.     

Performance Enhancement of Cellular Network Using Adaptive Soft Handover Algorithm

Mobility management is the most important feature of a wireless cellular communication system. Continuation of an active call is one of the most important quality measurements in the cellular systems. Handover makes it possible for a user to travel between various networks or cells while having a seamless connection. This paper shows that, performance of cellular network can be increased with proposed adaptive soft handoff algorithm, which dynamically calculates the Soft handover margin based on the received signal strength and distance. Performance is evaluated in terms of the performance metrics active set update rate, active set size, soft handover region and probability of outage. Simulation results show that soft handover algorithm gives better performance with adaptive soft handoff margin compared to that of fixed soft handover margin in varied propagation conditions.     

A New Empirical Formula for Handover Rate in Microcellular Systems

In this paper, we propose a new empirical formula for handover rate as a function of base stations separation, standard deviation of shadow fading, path loss exponent, averaging distance, and correlation distance. The handover initiation algorithm is based on averaged signal strength measurements using relative signal strength with hysteresis margin approach. We generate the data through computer simulations for the average number of handovers referred to as handover rate, for the practical range of path loss exponent and standard deviation of shadow fading. The proposed formula provides for a practical design tool to optimize the handover initiation performance under varied propagation environments.     

Adaptive Hysteresis Using Mobility Correlation for Fast Handover

The value of hysteresis has a significant effect on the handover performance measured in terms of the handover initiation delay and the number of handovers. To determine the hysteresis value effectively, a mobility correlation among users is utilized. In this letter, a grouping algorithm and an adaptive hysteresis algorithm based on the mobility correlation are proposed. It is shown that the proposed algorithms are very efficient in reducing both the handover initiation delay and the number of handovers.     

Evaluation of handover mechanisms in shadowed low earth orbit land mobile satellite systems

This paper presents a quantitative analysis by computer simulation of the active set update (ASU) handover algorithm for a shadowed low earth orbit (LEO) land mobile satellite (LMS) environment. As a precursor to the handover analysis, the mutual visibility statistics for a 66 satellite polar and 48 satellite rosette-type constellation are presented. These results show the statistical nature of the levels of satellite diversity and mobile-to-satellite elevation angles (to the highest satellite) within each network and also indicate the influence of the channel characteristics on the handover strategy. A two-state Markov modulated channel model is assumed in the handover analysis, and this enables the assessment of increased levels of power and time hysteresis on the quality of service and network signalling load in a shadowed land mobile satellite environment. In particular, attention is given to the different modes of ASU operation for hard handover, switch diversity and soft handover.     

LTE中基于移动特性的切换优化

LTE系统对3G系统的多方面进行了全面的改进和演化,使系统性能得到了全面的提升。为了降低基础设施建设费用以及网络运营费用,运营商提出了自组织网络（SON）技术。针对移动鲁棒性优化（MRO）问题,根据该系统下用户移动性对切换优化的影响,提出了对不同移动速度用户设置不同的小区迟滞参数值,即US-MRO优化算法。分析和仿真结果表明,该切换优化算法有效地提高了用户切换成功率,使用户满意度得到提升。     

Analysis of Handover Performance in LTE Femtocells Network

Handover management is one of the main factors representing the effectiveness of every wireless network technology. Due to the special characteristics of a femtocell, unnecessary handover occurs more frequently. This issue has attracted interest in developing a new handover algorithm in femtocell network. The standard handover algorithm relies on Reference Signal Received Power or Reference Signal Received Quality (RSRQ) level. However, this technique causes an unnecessary handover and reduces the user throughput. Mobility prediction is one of a popular technique to be implemented in handover algorithm. This paper analyzes the handover performance in femtocell network by using two types of handover algorithm which are standard A2-A4-RSRQ handover algorithm and proposed prediction handover algorithm. The analysis is performed in terms of the number of handover, the number of unnecessary handover, and the user throughput. The root cause of user throughput degradation is also analyzed. The results show that the prediction handover algorithm provides better performance than the A2-A4-RSRQ handover algorithm in terms of the number of handover and user throughput.     

考虑负载均衡和用户体验的垂直切换算法

在超密集异构无线网络中,针对城区交通高峰期,大规模车载终端短时间聚集性移动引起的网络拥塞问题,该文提出一种考虑负载均衡和用户体验(LBUE)的垂直切换算法。首先,引入网络环境感知模型预测网络未来的拥塞程度,并提出一个融合自组织网络的网络架构,缓解网络拥塞。其次,定义业务适应度和负收益因子,并提出一种基于秩和比(RSR)的自适应切换判决算法,为用户筛选出当前环境下满意度最高的目标网络。实验结果表明,该算法能够有效降低终端接入网络的阻塞率和掉话率,实现网络间负载均衡并提升用户体验。     

Mobility and Handover Management for Heterogeneous Networks in LTE-Advanced

3GPP Long Term Evolution-Advanced (LTE-A) aims at enhancement of LTE performance in many respects including the system capacity and network coverage. This enhancement can be accomplished by heterogeneous networks (HetNets) where additional micro-nodes that require lower transmission power are efficiently deployed. More careful management of mobility and handover (HO) might be required in HetNets compared to homogeneous networks where all nodes require the same transmission power. In this article, we provide a technical overview of mobility and HO management for HetNets in LTE-A. Moreover, we investigate the A3-event which requires a certain criterion to be met for HO. The criterion involves the reference symbol received power/quality of user equipment (UE), hysteresis margin, and a number of offset parameters based on proper HO timing, i.e., time-to-trigger (TTT). Optimum setting of these parameters are not trivial task, and has to be determined depending on UE speed, propagation environment, system load, deployed HetNets configuration, etc. Therefore, adaptive TTT values with given hysteresis margin for the lowest ping pong rate within 2 % of radio link failure rate depending on UE speed and deployed HetNets configuration are investigated in this article.     

多网络共存下基于贝叶斯的垂直切换算法

针对目前的垂直切换技术普遍不能满足多网络下的切换问题,提出了一种改进的基于贝叶斯决策的垂直切换算法。首先根据接入终端网络的信号强度、网络负载、误码率和网络阻塞率以及用户业务对网络的实际需求偏好建立多条件相关的切换概率分布,计算出先验切换概率;然后通过贝叶斯决策算法计算出后验概率来进行判决比较,从而选取最优的接入网络。仿真结果表明,该算法不仅能有效地实现不同接入技术之间的垂直切换,从而减少不必要的切换,提高了切换成功的概率,而且还能在维持各网络平均负载达到30%~40%时减轻通信热点的阻塞情况,为用户提供更优的服务质量。