超密集网络中基于小区分簇的资源分配

针对超密集网络中毫微微小区(Femtocell)之间同层干扰以及毫微微小区与宏小区(Macrocell)之间跨层干扰问题,提出了一种基于小区动态分簇的资源分配算法。该算法分为两步:第一步首先采用了基于速率公平性的子信道分配算法为宏用户分配子信道,接着利用注水算法分配功率;第二步首先根据毫微微小区之间的干扰权值大小,利用遗传模拟退火算法为FAPs分簇,其次利用启发式信道分配算法为FUEs分配子信道,采用KKT条件为用户分配功率。仿真表明,该算法能够有效抑制这两种干扰,满足用户速率需求,提升网络频谱效率。     

超密集网络中基于干扰协调的资源分配算法

超密集网络中,严重的小区间干扰制约了终端用户的数据速率,针对该问题,该文提出一种基于干扰协调的资源分配方案。该方案分为两个模块：第一模块基于毫微微接入点(Femtocell Access Points, FAPs)间的干扰程度,将干扰强的FAPs分到同一簇内,同簇内的FAPs共享频带资源,通过FAPs间的协作使不同簇之间实现频谱的复用;第二模块基于最大功率和最低速率的公平性准则进行最优功率分配,动态分配资源。仿真结果表明,该算法在超密集网络场景下能够有效控制FAPs间的干扰,最大化系统吞吐量。     

宏-飞蜂窝双层网络中基于毫微微基站分组的资源分配

针对宏-飞蜂窝双层网络模型中宏小区（Macrocell）用户层和毫微微小区（Femtocell）用户层之间的跨层干扰和Femtocell之间的同层干扰,提出了一种基于毫微微基站分组的资源分配算法。该算法包括两个部分：一部分是宏基站先利用改进的差额法,设置虚拟的宏用户（MUE）,将之变为平衡的指派问题再为宏小区用户分配信道,然后用注水算法分配功率,保证宏小区用户的正常传输。另一部分是在保证宏小区用户的服务质量基础上,采用一种增强型的蚁群优化（EACO）算法,设定信息素浓度范围后对毫微微小区进行分组,避免了原始的蚁群算法有可能陷入局部最优的现象;再利用一种启发式算法和分布式功率分配算法分别对毫微微用户（FUE）进行信道和功率分配,在满足毫微微小区用户的数据速率需求下,最大化频谱效率。仿真结果表明,EACO有效地抑制了跨层干扰和同层干扰,既能保证用户的数据速率需求,又能有效提升网络频谱效率。     

基于分簇和Stackelberg博弈的D2D资源分配策略

当前,车辆密集通信场景下存在通信资源利用率低、DUE(D2D user)用户通信质量差等问题。针对上述问题,提出了一种基于分簇和Stackelberg博弈的D2D(device to device)资源分配策略,以解决DUE用户功率分配、信道匹配问题。首先,基于每个信道内DUE用户之间干扰最小原则,该模型对所有DUE用户进行分簇;然后,对于CUE(cellular user)用户与DUE用户簇,构建一对多的Stackelberg主从博弈模型,通过复用链路干扰参数和簇内干扰参数的迭代更新,优化每个DUE用户的发射功率;最后,利用匈牙利算法实现DUE用户簇与CUE用户的最佳信道匹配,最大化DUE用户的容量和。仿真结果表明,与基于价格迭代、等功率分配和高能效干扰约束的几种功率分配算法相比,所提算法能有效提升DUE用户的总容量。     

无线传感器网络中一种抗无线局域网干扰的信道分配机制

无线传感器网络(WSN)易受到与其共享信道的无线局域网(Wifi)干扰,造成通信可靠性及吞吐量下降.当具有不同优先级的多个WSN受到Wifi干扰时,如何按优先级分配信道,并兼顾整体通信可靠性及吞吐量是一个重要问题.针对该问题,作者提出了一种抗Wifi干扰的信道分配机制EasiCAP(Channel Allocation for wireless sensor networks with Priority).该机制利用基于干扰强度和活跃比率的干扰特征模型(External Interference Model,EIM)度量WSN中各信道的Wifi干扰;同时,采用以接收端为中心的模型(Internal Interference Model,IIM)度量各WSN之间的干扰.然后,各WSN根据EIM和IIM度量的结果,采用局部化贪婪信道分配算法独立、实时地选择信道,通过保持信道、切换信道及抢占信道操作实现按优先级分配信道,并尽可能降低所有网络所受干扰之和.实际测量和仿真结果表明,EasiCAP可为各WSN提供与其优先级相对应的通信可靠性和吞吐量;而且该机制下的平均通信可靠性及吞吐量也比现有方法高.此外,EasiCAP未带来过大的开销.     

Femtocell的功能及体系

Femtocell(毫微微小区)是一种改善市内覆盖的小型低成本基站,能够提供很好的深层覆盖,适用于家庭和办公室环境。文章在分析了Femtocell的优势的基础上,简单介绍了它的体系结构、接口以及其对现有移动通信网络的影响,最后提出了Femtocell面临的困难以及良好的发展前景。     

一种REB & PMDS的无线MAC协议

针对分散无线网络的媒质访问控制,提出了一种新的MAC算法;算法根据几何分布采用随机长度的突发来重复消除信道访问节点,其中每个发送节点能够在每个时隙中执行载波侦听操作或执行一个短突发或干扰发送;计算了在单次消除和重复消除中n个节点中有m个节点在消除阶段存活下来的概率以及重复消除中一个节点成为唯一获胜者的概率;并基于基本优先级向量提出了一种实现差异化服务的相对优先级机制,从而提高整个网络的信道总利用率;仿真实验结果表明,提出的协议算法相比于目前广泛采用的几种MAC协议在信道接入成功率、信道利用率和信道分配公平性方面都有明显的优势。     

混合频谱分配的三层异构网络覆盖概率分析

针对城市环境热点区域业务密集化部署带来的流量激增问题,将微微基站和毫微微基站密集部署在宏基站之上以达到分流的效果,构建了一个三层簇异构网络模型。为有效抑制层内和层间传输的严重干扰,提出了一种基于簇分类的改进共享频谱分配方案。采用泊松簇过程和泊松洞过程对基站部署进行建模,详细描述了接收端精确的干扰统计特性,基于有效性准则给出了系统覆盖概率。同时还考虑了有序FBS级联方案和无序FBS级联方案2种情况。仿真结果验证了理论分析的正确性,揭示了网络参数对网络性能的影响。与无序FBS级联方案相比,有序FBS级联方案的性能增益很大程度上取决于PBS和FBS的覆盖半径。      

基于自适应熵估计遗传算法的高级在轨系统虚拟信道调度

针对空间数据业务的多类型、大容量等特点,基于AOS(advanced orbiting system)虚拟信道复用技术,分析了AOS虚拟信道调度的多约束问题,建立了AOS虚拟信道调度模型,提出了一种基于自适应熵估计遗传算法(AEEGA)的AOS虚拟信道调度算法.该算法能够根据种群熵和个体适应度自适应调整交叉概率与变异概率,并设计了基于各进化算子的虚拟信道调度流程.实验结果表明,该算法能保证高优先级虚拟信道较低的包剩余量、丢包率和延时,并可保持较好的公平性,比自适应遗传算法的全局搜索能力更强,比动态优先级调度算法的总体满意度更高.     

异构网络下行链路层间协作功率控制算法研究

为了克服Femtocell网络的大规模部署所带来的干扰问题,采用对Femtocell基站发送功率控制的方法。针对Femtocell网络边缘Macrocell用户所受到的强下行链路跨层干扰,通过比较Femtocell用户和Macrocell用户的信干噪比(SINR)与最小SINR阈值的关系,提出了基于Femtocell用户路径损耗的Femtocell基站发送功率自适应调整算法,从而提高了Macrocell用户的通信质量。通过仿真验证,该方法使得Macrocell用户所受干扰明显降低,整体网络性能得以提升。     

Channel allocation and power control schemes for cross-tier 3GPP LTE networks to support multimedia applications

In this paper, we present the framework of a channel allocation (CA) and power control (PC) schemes for the minimization of interference in cross-tier 3GPP LTE networks that aim to support internet of multimedia things. Channel allocation scheme based on an interference graph preserving the minimum number of interfered MUEs by femtocells (IG-MIM) is proposed to mitigate interference amongst femtocells, and a game theory based power control algorithm is also proposed to reduce interference to surrounding macrocell users (MUEs). The proposed IG-MIM scheme constructs the interference graph based on a predefined threshold and allocates the subchannels to the femtocells that maintain the smallest number of interfered MUEs. For the power control, we design a payoff function based on the rewards from the achieved data rates and the penalties from the interference in regards to its adjacent femtocells. The simulation results show that the IG-MIM channel allocation significantly improves the SINR performance for the femtocell users (FUEs) being served; the game theory based power control decreases the power requirements of a femtocell and alleviates the interference to the MUEs.     

Contention based scheduling for femtocell access points in a densely deployed network environment

The proliferation of new data intensive devices has caused an enormous burden on wireless systems. A femtocell network is a promising new technology developed to meet these demands. Since each femtocell network consists of uncoordinated subnetworks that work independently, the interference between subnetworks can result in a significant degradation of the overall network capacity. In this paper, we address the interference problem between uncoordinated femtocell access points (FAPs) and propose a distributed FAP scheduling scheme in a densely deployed femtocell network where FAPs interfere with each other. In contrast to previous works that have focused on dynamic power and frequency management, our approach focuses on time sharing through FAP contention. Depending on the outcome of contention, our method selects a winning FAP to be the sole user of the next time frame. The approach operates in a fully distributed manner with help from mobile nodes (MNs). To implement this scheme, we develop a new synchronous frame structure, which uses special common control channels. Through simulations, we observe that the proposed scheme doubles the network capacity compared to the legacy non-contending scheme, and could serve as the basis for future standards on femtocell networks.     

LTE-A飞蜂窝系统干扰协调智能优化算法

在同频组网的LTE-A飞蜂窝系统中,飞蜂窝基站的密集部署会造成较为严重的同频干扰,导致网络吞吐量和用户的服务质量(Quality of Service,QoS)降低。部分频率复用(Fractional Frequency Reuse,FFR)作为常用的干扰协调方案,可以有效地提高边缘用户的服务质量。在FFR方案的基础上,通过结合遗传算法和基于模拟退火的图着色算法,提出了一种智能优化部分频率复用(Intelligence-FFR,I-FFR)算法。该算法能够动态地调整中心区域所占比例和边缘区域的频率复用因子,以增加宏小区吞吐量,降低小区边缘区域用户的中断概率。仿真结果表明,与FFR-3干扰协调算法相比,提出的I-FFR算法可使宏小区吞吐量提升15%,同时边缘区域平均用户的中断概率从85%降低到40%。     

Femtocell网络中基于联合传输的分簇与功率分配算法*

针对家庭基站(femtocell)密集部署时的下行干扰问题,提出一种基于多点协作联合传输的分簇与功率分配相结合的算法。首先根据受到的干扰程度进行分簇,将干扰强的家庭基站分到同一个簇,簇内所有家庭基站通过寻找对自身最有利的基站进行协作,将干扰信号转变有用信号,联合传输为用户提供服务,提升用户的信干噪比来保证用户性能,簇间则复用相同的频谱资源。然后通过给用户分配合适的功率使得总传输速率最大。仿真结果表示,所提算法能在抑制系统干扰的同时提高系统的吞吐量。     

基于非合作博弈的femtocell 双层网络分布式功率控制

研究在频谱共享条件下家庭基站双层网络的分布式功率控制策略.将宏基站所能承受的干扰限度视为家庭基站的可分配资源,家庭基站以竞价形式对其"购买",从而构成宏基站与家庭基站以及家庭基站用户之间的博弈模型.分析了该博弈过程中纳什均衡解的存在性和惟一性,并给出了在非合作模式下指导家庭基站用户进行理性竞争的分布式功率调整算法.最后,通过仿真实验验证了所提出算法的有效性.     

基于优先级的簇内终端直通数据转发策略

在蜂窝网络中,相同需求的用户可以建立成簇以利用终端直通(D2D)技术提高数据分发效率。然而,D2D链路质量的差异可能会成为提高资源效率的瓶颈。为了解决上述问题,在考虑链路质量差异的前提下,提出了基于优先级的D2D中继方案。该方案通过遍历链路质量矩阵自适应选取最优阈值,以优先选择可实现较高数据速率的D2D链路进行数据转发,提高了时频资源的利用率。与无优先级方案相比的仿真实验中：基于优先级的D2D中继方案消耗更少的时频资源,具有更高的资源效率,而且随着成功接收数据的用户（ACK用户）与未成功接收数据的用户（NACK用户）比值减小,优势更加明显;同时簇的大小对资源效率的改善也有一定影响。结果显示,对于簇内用户数目较少并且NACK用户多于ACK用户的情形,所提出的分级转发方案对资源效率的改善尤为明显。     

基于博弈资源分配的认知异构网络干扰协调算法

基于underlay频谱共享模式的认知异构网络可有效缓解频谱资源短缺问题,但同时会加剧网络中的干扰。针对该问题,提出了一种基于非合作博弈模型的动态频谱分配和功率控制算法进行干扰协调。首先,考虑频谱共享造成的干扰问题,引入认知用户优先等级,将问题构建为联合动态频谱分配与功率控制的频谱定价博弈模型;其次,通过两阶段动态博弈得到纳什均衡解,实现认知网络层频谱资源合理分配和发射功率控制。仿真表明,所提算法能够实现不同优先级用户频谱资源的合理分配和认知基站发射功率控制,有效抑制认知异构网络的跨层干扰和层内干扰。     

A Stackelberg game-based spectrum allocation scheme in macro/femtocell hierarchical networks

Femtocells widely deployed in a macrocell form hierarchical cell networks, which can improve indoor coverage and network capacity, and have been regarded as one of the most promising approaches. However owing to the absence of coordination between the macro and femtocells, and among femtocells, decentralized spectrum allocation between macro and femtocell users become technically challenging. In this paper, a dynamic spectrum allocation scheme based on Stackelberg game is proposed, in which macrocell base stations as leaders and femtocell base stations as followers are players, and the same spectrum is the resource that players will choose assigning to users for minimizing the affected interference among each other. The Stackelberg equilibrium is defined and proved to be existed, which is also the optimal spectrum allocation manner. Simulations were conducted to study the impact of femtocells on the macrocells regarding throughput, outage probability and spectrum efficiency. And the comparison results show that the proposed scheme might be a solution for efficiently allocating the spectrum in hierarchical cell networks, as the improvement in terms of throughput, outage probability and spectrum efficiency had been achieved.     

Research on user pairing algorithm for LTE femtocell uplink

In this article,a new simulated annealing based bit error rate pairing scheduling(SA-BPS)algorithm for LTE femtocell uplink virtual multiple input multiple output(V-MIMO)systems is proposed,which uses Round Robin(RR)criterion to decide the first user,and simulated annealing(SA)algorithm with objective function of bit error rate(BER)is suggested to decide the pairing users.The SA-BPS is considered not only to be used for inner layer user pairing within femtocell user equipments(HUEs)to increase spectrum efficiency,but also to be used for cross layer user pairing between HUEs and macrocell user equipments(MUEs)to cancel the cross layer interference from MUEs to HUEs.As a growth control coefficient is used in SA-BPS to control the growth of average BER of users in the pairing group,rapid user BER deterioration can be prevented by adopting a proper coefficient.Simulation results show that,the SA-BPS outperforms RPS,DPS,and the conventional SA algorithm in terms of BER performance,whether used for inner layer user pairing or cross layer user pairing.Also,the mode switching signal to interference ratio(SIR)threshold between inner and cross layer user pairing are obtained by simulation in three cross layer interference power distribution scenarios.