聚合干扰下小小区网络的协作传输方案及性能分析

该文针对聚合干扰下小小区网络协作传输的场景,分析了宏小区基站的物理位置服从泊松分布,且多用户预编码采用线性预编码时用户端的性能。通过基于概率密度函数的性能分析法,推导出小小区网络协作传输的中断概率、容量以及误符号率的闭合表达式,结果表明由于聚合干扰的存在,仅仅依靠小小区网络基站天线数的增加并不能持续提高用户端的性能。进一步,针对小小区网络中用户的接入问题,提出了一种基于能效最大化的用户接入方案,并对所提方案进行了性能分析和仿真验证,从结果可以看到所提小小区网络用户接入方案在提高系统能效方面要优于其他接入方案,仿真结果验证了基于能效最大化的接入方案的优越性,并验证了本文理论分析的正确性。      

毫微微小区系统中的干扰分析与节能技术利用

毫微微小区（Femtocell）基站外观与Wi-Fi接入设备相似,发射功率小,适用于家庭及办公室环境。在分析Femtocell系统的资源复用模型和接入过程的基础上,文章针对宏小区（Macrocell）和Femtocell混合网络的干扰问题,通过对随机到达的用户合理分配时频资源,提出一种功率控制方案。该方案能达到系统节能、降低干扰和提高系统性能的目的。     

LTE-A系统时域小区间干扰协诟技术标准化研究

异构网络被LTE-A系统视为一种提升单位区域频谱效率的关键技术而得到广泛关注。然而,异构网络会带来严重的小区间干扰,小区间干扰协调因此成为3GPP标准化进程研究的重点。首先总结了异构网络及小区间干扰协调技术,然后介绍了目前3GPP中讨论的小区覆盖扩展（CRE：CellRange Extension）和基于几乎空白子帧（ABS：Almost Blank Subframe）的时域小区间干扰协调技术。最后,基于动态系统级仿真平台,评估了CRE和ABS技术方案系统性能。     

基于干扰感知的上行调度算法研究

针对LTE系统中上行小区间干扰特性,提出了一种基于干扰感知的LTE上行比例公平调度算法改进方案。该方案通过小区协作方式计算协作簇内的小区调度优先级和基于干扰感知的用户调度优先级并以此进行资源调度。仿真结果表明,相对于未采用干扰感知的比例公平调度算法,该方案的两种形式都能够在保障系统吞吐量性能的前提下,有效地提高小区边缘用户性能,同时证明了干扰感知的越精确,小区边缘用户的性能越好。     

一种消除TD-SCDMA系统小区间干扰的方法

时分-同步码分多址(TD-SCDMA)系统采用的扩频码码长最大为16,当邻小区用户处于2小区边缘时会对本小区造成较大的干扰。针对上行链路提出了一种新的干扰消除方法:串行干扰消除-联合检测(SIC-JD)。该方法采用复杂低的SIC对上行链路中的小区间干扰进行消除,对于小区内干扰和残留的小区间干扰采用联合检测进行消除。3GPP case1信道下的仿真结果显示了此方法能够有效消除小区间和小区内干扰,提高接收机性能。     

LTE中频率复用改进算法研究

下一代蜂窝系统中通过频谱复用来克服小区间干扰已成为当前研究热点.针对LTE小区间干扰协调问题,重点讨论比较了几种频率复用方案,并提出一种自适应的部分频率复用优化方案和具体实现算法,仿真表明该算法能显著改善小区边缘用户的吞吐量性能和公平性参数.     

LTE系统上行小区间干扰协调技术研究

为了进一步提升LTE上行系统中小区边缘用户的吞吐量,文章对现有的软频率复用方案予以改进,提出了一种同时基于优先级的频率协调和基于用户位置的功率调整的小区间干扰协调方案,并通过系统级仿真对该方案在LTE上行系统中的性能进行了评估。仿真结果表明,此方案可以在尽量避免对扇区平均性能和小区中心用户性能造成负面影响的前提下,大幅提升小区边缘用户性能。     

一种适用于超密集网络下行链路的干扰抑制方案

在超密集网络（UDN）下行链路场景中,为了有效克服因节点间距减小、邻近节点传输损耗相差不大而产生多个强度相近的干扰源对用户性能的影响,提出了一种基于优先级以用户为中心的小区间干扰抑制方案。为了便于量化基站协作取得的带宽性能增益,采用了一种计算带宽盈亏率的定量分析指标。通过该指标,易于确定在特定UDN场景下干扰协调方案是否处于盈利状态,进而通过系统能够接受的最大损耗比优化参数配置。仿真结果表明,该干扰抑制方案能显著提升用户的信号干扰噪声比（SINR）性能,且能更好地保障用户公平性,有效地克服了用户SINR性能在基站数较多时受天线数限制的缺陷,为提升UDN网络用户性能和系统性能提供了一种解决方案。     

一种提高小区边缘用户性能的多用户子载波功率分配策略

在OFDMA系统中,小区边缘用户由于受到来自相邻小区的同频干扰,通信质量严重下降.有效地抑制小区间干扰,极大地提升无线网络性能尤其是小区边缘用户性能是5G移动通信系统的目标之一.基于速率自适应(RA)准则提出了一种提高小区边缘用户性能的子载波和功率的联合资源分配算法,该算法分为子载波分配和混合功率分配两步,在提高小区边缘用户性能的同时,最大化链路吞吐量.仿真结果表明,小区边缘用户吞吐量增益为25％以上,混合功率分配下的系统吞吐量逼近全部用户使用注水法时的系统吞吐量,并且降低了运算复杂度.     

基于部分频率复用的多小区协作方案及容量分析

针对无线蜂窝网中的小区间干扰问题,给出一种基于部分频率复用的多小区协作传输方案.该方案将小区用户划分为中心用户和边缘用户,中心用户采用频率复用因子为1的本地基站通信,边缘用户采用频率复用因子为3的多基站协作通信,并通过对多个小区的基站进行功率控制,达到抑制小区间干扰、提高系统容量的目的.数值分析表明,相对于传统多小区蜂窝系统(Traditional Multi-Cell System,TMCS)和广义分布式天线系统(Generalized Distributed Antenna System,GDAS),所提多小区协作蜂窝系统(Multi-Cell Cooperative System,MCCS)可以有效地克服小区间干扰,提高系统容量.     

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.     

Inter-femtocell interference coordination in 3D in-building scenario

With rapid development of femtocell,dense deployment of femtocells in buildings will become an important study scenario.In this scenario,there exists severe inter-femtocell interference in the same building,which is revealed by our simulations in the 3-dimention(3D) scenario.If this type of interference is not well controlled,services to indoor users are bound to be deteriorated,especially for the femtocell edge users.Motivated by this problem,femto users’ received interference model is constructed based on the scenario of 3D femtocell deployment.Then,a graph theory based in-building inter-femtocell coordination scheme is proposed,which includes three phases:establishment of femtocell interference graph,femtocell clustering and frequency resources allocation based on the proposed cluster influence circle.Finally,the simulation results confirm that the proposed scheme improves the femtocell average throughput by 22.4% and 26.2% in comparison with frequency universal reuse scheme and frequency hopping scheme respectively,and ensures the channel demodulation reliability of cell edge femto users.     

Improved Clustering and Resource Allocation for Ultra-Dense Networks

To reduce the interference among small cells of Ultra-Dense Networks(UDN),an improved Clustering-Assisted Resource Allocation(CARA)scheme is proposed in this paper.The proposed scheme is divided into three steps.First,an Interference-Limited Clustering Algorithm(ILCA)based on interference graph corresponding to the interference relationship between Femtocell Base Stations(FBSs),is proposed to group FBSs into disjoint clusters,in which a pre-threshold is set to constrain the sum of interference in each cluster,and a Cluster Head(CH)is selected for each cluster.Then,CH performs a twostage sub-channel allocation within its associated cluster,where the first stage assigns one sub-channel to each user of the cluster and the second stage assigns a second sub-channel to some users.Finally,a power allocation method is designed to maximize throughput for a given clustering and sub-channel configuration.Simulation results indicate that the proposed scheme distributes FBSs into each cluster more evenly,and significantly improves the system throughput compared with the existing schemes in the same scenario.     

基于信漏噪比的异构网络载波干扰协调技术

针对异构网络存在小区间干扰的问题,提出了一种基于频域载波聚合的干扰协调管理机制。该机制将所有小区的用户分为中心用户和边缘用户,采用可降低干扰的信漏噪比(SLNR)准则,动态调度用户和选择小区载波,并将每种小区载波选择方案对应一种调度用户分组的机制,即对小区的中心用户和边缘用户采用不同优先级,以此有效避免小区间的干扰,其中优先级采用比例公平和SLNR准则。仿真结果表明,由于在系统目标最大化时实现了频率复用增益和干扰消除增益间实现最佳的平衡,可有效取得系统流量的分流和总吞吐量的提升。     

一种面向CR-NOMA系统的动态功率分配算法

在密集小区的认知无线电非正交多址（cognitive radio non-orthogonal multiple access, CRNOMA）网络场景下,针对用户采取Underlay方式复用时信道频带利用率低的问题,提出了一种基于能效的组合用户动态功率分配算法.该算法在保证主用户服务质量前提下,基于用户之间的干扰和信干噪比,优化了组合多用户的接入方案,使信道接入用户数量最大且提高了频带利用率.同时,根据增益排序下的功率差额配比改进了剩余功率再分配方案,使空闲功率重新利用更加合理和有效.仿真结果表明,本文算法可以有效实现接入用户数量最大化的同时提高了频谱利用率.     

超密集组网下一种基于干扰增量降低的分簇算法

超密集网络(UDNs)拉近了终端与节点间的距离,使得网络频谱效率大幅度提高,扩展了系统容量,但是小区边缘用户的性能严重下降。合理规划的虚拟小区(VC)只能降低中等规模UDNs的干扰,而重叠基站下的用户的干扰需要协作用户簇的方法来解决。该文提出了一种干扰增量降低(IIR)的用户分簇算法,通过在簇间不断交换带来最大干扰的用户,最小化簇内的干扰和,最终最大化系统和速率。该算法在不提高K均值算法的复杂度的同时,不需要指定簇首,避免陷入局部最优。仿真结果表明,网络密集部署时,有效提高系统和速率,尤其是边缘用户的吞吐量。     

超密集网基于干扰公平及多维协作的虚拟小区生成算法

在超密集网络场景中,小区密度持续增加使得干扰关系更加复杂,重叠虚拟小区结构使得资源分配深度耦合,导致虚拟小区选择成为影响系统性能的因素之一.为此,针对虚拟小区边权重设计,采用联合资源分配前置化思想,提出一种综合了干扰公平功率分配、MU-MIMO配对及协作传输诸增益因素的权重方案.针对虚拟小区成簇,基于提出的权重设计准则,通过最大权重成对小区成簇算法实现虚拟小区可重叠成簇.仿真结果表明,提出的虚拟小区生成算法可在低计算复杂度的前提下保证系统性能的改善.     

Resource Allocation Based on Channel Sensing and Spatial Spectrum Reuse for Cognitive Femtocells

A cognitive femtocell is a new small cell based on a smart home base station to solve the spectrum-scarcity problem. Recently, dedicated resource allocation for cognitive femtocell to mitigate co-channel interference is extensively researched. However, the cognitive femtocell may suffer from the lack of frequency resource for its users due to high data traffic load of the macrocell. We propose a novel resource allocation and power control mechanism using spatial frequency reuse and spectrum sensing, which enables femto users in the cognitive femtocell to obtain more feasible resource. We analyze and evaluate the performance gain of the proposed scheme. Although data traffic load of the macrocell increases, the capacity of the cognitive femtocell can be maintained appropriately by the proposed resource allocation and power control scheme and it is shown that the performance is improved compared to that of the conventional scheme.

     

基于重叠分簇的联合预编码方案设计

论文提出了一种重叠簇模型,并针对该模型的特点,设计了-种联合迫零-汤姆林森-哈拉希玛预编码(ZF- THP)算法;分析了现有分簇算法存在的两个问题,并针对每个问题采用基于重叠分簇的联合预编码技术设计了两种解决方案:一是抑制簇间干扰方案;二是协同度不对称下的重叠分簇方案。仿真表明,所提方案能够很好地解决分簇存在的问题,提高传统分簇算法的系统频谱效率,并改善局部用户的公平性能。     

Control and Data Channel Resource Allocation in OFDMA Heterogeneous Networks

This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macro cells and small cells sharing the same frequency band. Dense deployment of small cells overlaid by a macro layer is considered to be one of the most promising solutions for providing hotspot coverage in future 5G networks. The focus is to devise an optimised policy for small cells’ access to the shared spectrum, in terms of their transmissions, in order to keep small cell served users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro cell users in the vicinity of small cells is provided. Both data and control channel constraints are considered, to ensure that not only the macro cell users’ data rate demands are met, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. Control channel reliability is especially important as it holds key information to successfully decode the data channel. The problem is addressed by our proposed linear binary integer programming heuristic algorithm which maximises the small cells utility while ensuring the macro users imposed constraints. To further reduce the computational complexity, we propose a progressive interference aware low complexity heuristic solution. Discussion is also presented for the implementation possibility of our proposed algorithms in a practical network. The performance of both the proposed algorithms is compared with the conventional Reuse-1 scheme under different fading conditions and small cell loads. Results show a negligible drop in small cell performance for our proposed schemes, as a trade-off for ensuring all macro users data rate demands, while Reuse-1 scheme can even lead up to 40 % outage when control region of the small cells in heavily loaded.