面向负载均衡的主动切换

为了解决超密集网络中用户在移动过程中由于小区间干扰和负载不均衡导致的用户服务质量下降的问题,本文研究了一种面向负载均衡的主动切换策略,设计了一种基于双门限的移动切换策略,包含小区内的切换与小区间的切换。通过优化小区内的切换门限,可以最小化系统总资源开销。通过优化小区间的切换门限,能够保证用户实时业务需求的同时均衡网络负载。通过预测用户未来大尺度信道信息,设计主动的双门限切换策略,可以有效降低切换延迟。仿真结果表明,与现有的切换策略相比,所提算法不仅提高了资源利用率,还降低了用户掉线概率与切换次数。      

小区间动态干扰协调的改进方案

对下一代移动通信系统的小区间动态干扰协调算法进行研究,通过分析干扰水平,负载状况,基站的调节能力以及用户的位置,通过负载因子变化来接纳控制,提高边缘用户的数据传输速度,保证小区用户的公平性。通过上行功率控制及接纳算法改进方案;同时对小区用户划分区域设定,提出了小区间干扰协调的改进算法(ICPF), 并进行系统仿真计算分析,结果表明和以往传统算法相比,系统性能得到有效改进,进一步提高了系统公平性并增加小区边缘用户的吞吐量。     

异构无线网络多用户多业务接入中多目标优化控制方法研究

针对多异构网络重叠覆盖、多用户多业务共存环境下,用户最大化传输速率易致网络负载不均衡的问题,提出一种基于非支配排序遗传算法的业务接入控制方法。该方法首先以传输速率最大化及网络负载最均衡为目标,以带宽资源受限为约束,构建了传输速率最大化及网络负载最均衡的双目标优化模型;然后基于多目标优化方法非支配排序遗传算法(Non-dominated Sorting Genetic AlgorithmⅡ,NSGA-Ⅱ)求解该业务接入控制问题。仿真结果表明,所提算法兼顾了用户的传输速率需求及网络间的负载均衡,取得较好的效果。     

基于累积点播概率的负载均衡算法研究

为了提高集群系统的资源利用率,降低对用户请求的拒绝率,需要对集群系统中的各个服务器节点进行负载均衡.文章在对一些主流的负载均衡算法进行了详细分析,对比了它们的优缺点,并在此基础上提出了基于累积点播概率的负载均衡算法.该算法包含三个部分:最优副本生成、贪婪的副本放置和动态贪婪副本调整.仿真实验验证了所提算法的有效性.     

时分波分无源光网络与云无线接入网联合架构中负载平衡的用户关联与资源分配策略

在时分波分无源光网络(TWDM-PON)与云无线接入网(C-RAN)的联合架构中,由于无线域的负载不均衡问题,限制了网络整体的传输效率。为了充分利用TWDM-PON与C-RAN联合架构的网络资源,并保证用户的服务质量(QoS),该文提出一种负载平衡的用户关联与资源分配算法(LBUARA)。首先根据不同用户的服务质量需求以及分布式无线射频头端(RRH)的负载对用户的影响,构建用户收益函数。进而,在保证用户服务质量的前提下,根据网络状态建立随机博弈模型,并基于多智能体Q学习提出负载均衡的用户关联和资源分配算法,从而获得最优的用户关联与资源分配方案。仿真结果表明,所提的用户关联和资源分配策略能够实现网络的负载均衡,保证用户的服务质量,并提高网络吞吐量。     

时分波分无源光网络与云无线接入网联合架构中负载平衡的用户关联与资源分配策略

在时分波分无源光网络(TWDM-PON)与云无线接入网(C-RAN)的联合架构中,由于无线域的负载不均衡问题,限制了网络整体的传输效率.为了充分利用TWDM-PON与C-RAN联合架构的网络资源,并保证用户的服务质量(QoS),该文提出一种负载平衡的用户关联与资源分配算法(LBUARA).首先根据不同用户的服务质量需求以及分布式无线射频头端(RRH)的负载对用户的影响,构建用户收益函数.进而,在保证用户服务质量的前提下,根据网络状态建立随机博弈模型,并基于多智能体Q学习提出负载均衡的用户关联和资源分配算法,从而获得最优的用户关联与资源分配方案.仿真结果表明,所提的用户关联和资源分配策略能够实现网络的负载均衡,保证用户的服务质量,并提高网络吞吐量.     

一种基于移动代理的P2P系统主动负载均衡算法

负载均衡是P2P系统的研究热点,针对现有负载均衡算法的不足,提出了一种基于移动代理的主动负载均衡算法.该算法使用移动代理收集负载信息、生成负载迁移决策,降低了系统的通信开销,而且避免了单点失效问题和"颠簸"现象.通过引入对用户请求的评估和迁移,预见性的处理负载问题,提高了系统的服务质量.     

基于工作负载预测的虚拟机整合算法

针对云计算环境下满足负载均衡、自动伸缩、绿色节能等需求时所面临的虚拟机(VM)迁移问题,该文设计一种面向云计算基础设施基于工作负载预测的整合调度算法。通过有机结合基于工作负载预测的主动控制技术和基于实际系统状态信息的被动控制技术,并采用指数平滑预测模型预测未来时刻的工作负载情况,提出虚拟机选择阶段最大未来工作负载优先和虚拟机安置阶段比较资源需求队列的虚拟机整合算法。仿真表明,该算法利用基于预测的资源整合方式减少了服务器使用量、虚拟机迁移次数和服务等级协议违例次数,有效提升了以数据中心为核心的云基础设施整体资源利用率。     

异构蜂窝网络中用户关联与基站功率的协同优化

为实现异构蜂窝网络中宏基站和小基站之间的负载均衡,提出了一种基于效用函数最大化模型的用户关联机制和基站功率控制的协同优化方案.通过迭代算法求解该协同优化问题,首先在基站功率固定的情况下求得最佳用户关联策略,然后在所得的用户关联策略基础上通过Zoutendijk可行方向法求得基站最佳功率.通过协同优化获得的用户关联策略和基站功率控制实现了基站之间的负载均衡,通过降低宏基站功率和关闭闲置小基站降低了基站的能耗.仿真实验表明,所提方案和不实施功率控制的用户关联策略相比,实现了宏基站与小基站之间的负载均衡,降低了宏基站对小基站用户的干扰,提升了小基站用户的信号干扰噪声比,用户速率中位值提高了20％.     

认知无线电网络中基于业务自适应的干扰对齐新机制探索

摘 要：本文提出了一种基于自适应干扰对齐的认知无线电网络干扰协调新方法。这种方法采用基于离线搜索的干扰对齐模式优化和基于用户业务需求的自适应最佳模式选择,通过收发两端联合设计的干扰对齐算法实现主次用户的动态信道共享;为了简便有效地构造波束成型矩阵和干扰抑制矩阵,本文还推导出了一种干扰对齐的闭式解,并且证明了其适用条件;本文还对所提方法的可达自由度做了分析,得到了一个下界。采用统计模型进行的仿真结果表明,本文提出的自适应方法相对于修正的机会干扰对齐和固定模式的干扰对齐具有明显的自由度优势,因而可以有效提高认知用户的容量。由于本文提出的方法运算复杂度不高,可望未来应用于低成本的认知终端。     

一种适用于星地网络的流量负载均衡算法

在星地网络的背景下,为了降低由于地面网络链路负载过高导致的传播时延,提出了一种适用于星地网络的负载均衡算法。算法基于网络的链路容量设置一个链路资源利用率作为阈值,当发现路径出现过载的时候分成两步进行路径的预规划：第一步,运用蚁群算法为链路过载的数据流选择其他的路径,以满足地面网内部的负载均衡;第二步,如果仍出现链路超阈值的情况,通过卸载延迟容忍数据流来执行地面与卫星网络之间的负载均衡。仿真结果表明,设定自适应的过载阈值可以有效降低链路的拥塞,与现有算法相比该算法不仅可以更加均匀地分配地面网络中的流量,而且借助卫星网络使地面网络的平均时延降低了18.3%,提高了网络的服务质量。     

NOMA-MEC系统中基于改进遗传算法的协作式计算卸载与资源管理

为平衡网络负载与充分利用网络资源,针对超密集异构的多用户和多任务边缘计算网络,在用户时延约束下,该文构造了协作式计算任务卸载与无线资源管理的联合优化问题以最小化系统能耗。问题建模时,为应对基站超密集部署导致的严重干扰问题,该文采用了频带划分机制,并引入了非正交多址技术(NOMA)以提升上行频谱利用率。鉴于该目标优化问题具备非线性混合整数的形式,根据多样性引导变异的自适应遗传算法(AGADGM),设计出了协作式计算卸载与资源分配算法。仿真结果表明,在严格满足时延约束条件下,该算法能获取较其他算法更低的系统能耗。     

Joint load balancing and interference coordination in multi-antenna heterogeneous networks

In heterogeneous networks (HetNets), it is desirable to offload users from macro cells to small cells to achieve load balancing. However, the offloaded users suffer a strong inter-tier interference. To guarantee the performance of the offloaded users, the interference from macro cells should be carefully managed. In this paper, we jointly optimize load balancing and interference coordination in multi-antenna HetNets. Different from previous works, instead of almost blank subframes (ABS) on which the macro cells waste time resource, the macro cells suppress the interference to the offloaded users by zero-forcing beamforming (ZFBF) on interference nulling subframes (INS). Considering user association cannot be conduct frequently, we derive the long-term throughput of users over Rayleigh fading channels while previous works focused on instantaneous rate. From the perspective of the spectrum efficiency and user fairness, we formulate a long-term network-wide utility maximization problem. By decomposing the problem into two subproblems, we propose an efficient joint load balancing and interference coordination strategy. Simulation results show that our proposal can achieve good system performance gains over counterparts in term of the network utility, cell edge throughput and average throughput.     

Distributed User Association with Resource Partitioning in Heterogeneous Cellular Networks

To fully utilize the resources of heterogeneous cellular networks (HCNs), an effective approach that offloads users to the underloaded small cells from overloaded macrocells is widely advocated. However, this operation often leads to a bad result that the offloaded users achieve lower signal-to-interference-plus-noise-ratio (SINR) than these users in macrocells. Thus, some appropriate interference avoidance techniques should be adopted to partially alleviate the SINR degradation. For this, we consider the resource (frequency) partitioning that turns off some fraction of such resources in a macrocell. Naturally, an optimal offloading strategy should be closely coupled with resource partitioning, and in turn the optimal partition decides the offloading performance. In this paper, we propose a distributed association strategy with joint offloading and resource partitioning for HCNs. We reveal that load balancing, by itself, is insufficient, and additional resource partitioning is required to improve system performance. Meanwhile, we also show that, compared with the best power association and range extension association, the proposed scheme provides better association performance.

     

Optimal joint utility based load balancing algorithm for heterogeneous wireless networks

The rapid development of mobile broadband services with continuously increasing traffic volumes has resulted in a number of challenges, including ubiquitous network coverage, high bandwidth, and reliable services for reasonable price, etc. To address these challenges, evolved packet system (EPS) is proposed as the evolution of the packet core network. While resource management and load balancing issues in EPS are discussed in 3GPP standardization, relatively few research works consider mechanism design for load information monitoring and evaluation. Furthermore, even though some load balancing algorithms have been proposed for integrated networks, the load balancing scheme design which achieves the optimization of joint system performance has not been extensively studied. In this paper, an inter-access system anchor based load balancing mechanism is introduced which performs load monitoring and evaluation for access gateways and networks, and an optimal load balancing algorithm is proposed for heterogeneous integrated networks. To characterize the performance of integrated networks, the concept of utility function is introduced and the comprehensive performance of integrated networks which support both single type service and multimedia service is modeled mathematically. Applying vertical handoff as an efficient mechanism for achieving load balancing, the optimal number of handoff users is obtained through solving the optimization problem. Numerical results demonstrate that load balancing between access networks can be achieved, and the optimal number of handoff users corresponding to the maximal joint network utility can be obtained.     

LTE网络中多目标优化的动态负载均衡算法

小区间动态负载均衡算法的优劣对网络性能有很大的影响,现有算法大都顾此失彼,难以保证网络关键性能指标(如呼叫阻塞率等)达到最佳。为解决这个问题,该文将负载均衡问题建模为多目标优化问题,分别对不同服务质量要求用户建模其相应目标优化函数,对有服务质量要求用户的目标函数是负载均衡指示函数和网络平均负载函数的联合优化函数,而对没有服务质量要求用户(BE用户)的目标函数是所有BE用户吞吐量的总效用函数,并将小区可用资源数和用户服务质量要求作为约束条件。另外,考虑到在实际系统中运行的计算复杂度问题,提出一种复杂度较低的分布式负载均衡算法。包括资源调度策略,用户切换条件和呼叫接入控制。仿真结果表明,该文算法可达到较好的负载均衡效果,能有效降低有服务质量要求用户的呼叫阻塞率,提高网络资源利用率。     

Semi‐distributed dynamic inter‐cell interference coordination scheme for interference avoidance in heterogeneous networks

Inter‐cell interference (ICI) is a major problem in heterogeneous networks, such as two‐tier femtocell (FC) networks, because it leads to poor cell‐edge throughput and system capacity. Dynamic ICI coordination (ICIC) schemes, which do not require prior frequency planning, must be employed for interference avoidance in such networks. In contrast to existing dynamic ICIC schemes that focus on homogeneous network scenarios, we propose a novel semi‐distributed dynamic ICIC scheme to mitigate interference in heterogeneous network scenarios. With the goal of maximizing the utility of individual users, two separate algorithms, namely the FC base station (FBS)‐level algorithm and FC management system (FMS)‐level algorithm, are employed to restrict resource usage by dominant interference‐creating cells. The distributed functionality of the FBS‐level algorithm and low computational complexity of the FMS‐level algorithm are the main advantages of the proposed scheme. Simulation results demonstrate improvement in cell‐edge performance with no impact on system capacity or user fairness, which confirms the effectiveness of the proposed scheme compared to static and semi‐static ICIC schemes.     

The offloading model for green base stations in hybrid energy networks with multiple objectives

Based on green energy prediction and storage, a novel green base station (GBS) offloading model is proposed and can be employed with multiple objectives in this paper to save energy. By predicting the value of green energy collected by GBS and updating the residual energy of each GBS, we can obtain the maximum number of users that each GBS can offload theoretically. Then, the optimum number of users should be calculated in order to achieve different network performance. Eventually, under the restrictions of the maximum number of users and the optimum number of users, we can finish offloading for traditional base station in the network. Simulation results demonstrate that through the proposed GBS offloading model, we can fulfill compromise between maximizing green energy utilization and load balancing in the offloading process, and the effect of energy saving is remarkable. Copyright © 2016 John Wiley & Sons, Ltd.     

一种OFDMA系统半静态干扰协调算法

为了解决多小区OFDMA系统边缘用户受到严重的同频干扰问题,提出了一种基于小区边缘用户数的半静态干扰协调算法SICUN。该算法用小区边缘用户数指示小区边缘业务量的大小,结合特定的频率资源优先级规划方案以确定系统中小区中心、边缘用户的可用频率资源,在此基础上进行了补偿式功率控制。仿真结果表明:SICUN能在保证小区边缘用户性能的前提下,较大地提高系统整体性能。