三小区多用户MIMO系统中干扰对齐优化算法

针对三小区多用户MIMO干扰信道系统,通过一个启发性例子,联合设计发射预编码矩阵和接收赋形矩阵,给出基于特征向量闭式解的干扰对齐优化算法,相比已有干扰对齐算法,用户端可使用更少的天线资源获得相同的自由度性能,且只需本小区内用户协作共享信道信息;并归纳出普适场景下系统配置与可达自由度之间的关系：设定每个小区中的基站配置M根天线和K个用户,用户配置N根天线,各个基站对本小区中每个用户都发送d个数据流,当M=N≥2 Kd时,所提算法总共可获得3 Kd个自由度。所提算法可以完全消除小区间干扰和用户间干扰,相比传统的正交化干扰抑制算法,系统容量得到了明显地提升。     

蜂窝网络下行链路单反馈干扰对齐算法研究

干扰是无线蜂窝网络面临的主要问题之一。蜂窝网络干扰对齐能消除干扰的影响从而提高系统信道容量。经典蜂窝网络下行链路干扰对齐算法仅优化单个用户自身信道容量,从而限制了蜂窝小区整体信道容量的提升。从提高蜂窝小区总信道容量出发,该文提出一种蜂窝网络下行链路单反馈干扰对齐算法。构建了蜂窝网络下行链路干扰对齐数学模型;在用户端以最大化用户SINR为目标构造接收矩阵;而在基站端以最大化小区总信道容量为目标构造预编码矩阵,并通过梯度投影算法来求解该优化问题。实验结果表明,相比于传统蜂窝小区下行链路干扰对齐算法,新算法可有效提高蜂窝网络下行链路信道容量。     

干扰距离最远的多用户多天线干扰对齐算法

针对多用户多天线中小区边缘用户同频干扰问题,提出了一种基于干扰距离最远准则的多用户MIMO干扰对齐优化算法,通过对等效干扰信道进行SVD分解,选择与等效干扰信道矩阵距离最大的特征子信道作为传输预编码矩阵,并分析了算法复杂度以及空间相关性对性能的影响,仿真结果显示系统频谱效率较原始算法在8天线下有31.57％的提高.     

基于机会通信的多天线蜂窝系统小区间干扰协调

通过研究有限反馈波束赋形蜂窝系统中小区间同信道干扰变化的特性,提出了一种基于机会通信的有限权值机会波束方法。该方法通过在预先设计的有限数量的赋形权值码本中随机选择赋形权值,使目标小区的干扰变化与邻小区用户调度无关,从而使干扰测量和速率预测更为准确,降低了反馈时延和干扰变化造成的中断率。理论分析和仿真均表明:采用正比公平调度的有限权值机会波束与有限反馈波束赋形具有相近的发射速率,从而系统吞吐量得到提高。     

5G移动通信中的波束分配方法

随着时代的发展,用户对无线通信的要求大大提高。5G移动技术满足了用户多样化需求的同时,也带来了小区边缘用户的信道干扰（Inter-Channel Interference,ICI）等问题。为了改善边缘用户通信质量,提高小区通信容量,文章基于多点协作传输（Coordinated Multi-Point,COMP）技术,提出了一种波束分配的方法。通过COMP中的协作波束赋形（Coordinated Beamforming,CB）技术减少边缘用户干扰,基于联合传输（Joint Processing,JP）技术,设计一种通过随机几何算法来进行波束分配的方法,该方法旨在为用户分配最近的两个波束进行服务。仿真结果证明,该方法提高了小区通信容量。     

MIMO波束成型系统的干扰对齐技术分析

干扰对齐IA(Interference Alignment)是一种新兴有效地干扰抑制技术,可以通过压缩干扰所占的信号维度,使系统获得最大自由度。文章搭建了3用户MIMO系统线性干扰对齐的应用模型,对经典干扰对齐算法、基于特征子信道的干扰对齐预编码矩阵优化方法以及分布式干扰对齐算法进行了性能分析。分析结果表明,基于特征子信道的干扰对齐预编码矩阵优化方法和经典干扰对齐算法适用于集中式通信环境,因利用了本信道信息,前者性能优于经典干扰对齐算法;分布式干扰对齐算法用于分布式环境,性能与经典干扰对齐算法逼近。     

下行MIMO广播信道中基于偏袒干扰消除的回溯干扰对齐方案

针对具有反馈时延的单小区多用户MIMO蜂窝干扰网络,采用时延度(DoD)来量化干扰对齐方案引起的信息时延,提出一种基于偏袒干扰消除的回溯干扰对齐(PIE-RIA)方案.该方案首先在中继处获取干扰符号并设计预编码矩阵,然后中继发送已编码的干扰符号至用户执行干扰消除,最后基站利用反馈的干扰信号与CSI实现多个用户的回溯干扰...     

基于延迟输出反馈的上行多小区MIMO蜂窝干扰网络自由度分析

针对具有反馈时延的上行多小区MIMO（Multiple-Input Multiple-Output）蜂窝干扰网络,提出一种基于延迟输出反馈（OF,Output Feedback）的回溯干扰重构（RIR,Retrospective Interference Reconstruction）方案.该方案首先通过在基站构造接收波束成形矩阵,将重构的OF下传至用户.然后用户对延迟的OF预编码并传输至基站,基站利用预编码信息消除小区间干扰.分析了上行任意多小区MIMO蜂窝干扰网络的RIR方案适用条件、系统和速率和可达自由度（DoF,Degrees of Freedom）,并将RIR方案与回溯干扰对齐方案和TDMA方案进行对比仿真分析,结果表明,RIR方案能获得更多自由度.     

三小区环境中基于三角分解的低复杂度干扰对齐算法

针对3小区每小区2个边缘用户的MIMO下行链路,在不改变系统自由度的前提下对联合信道进行下三角分解得到系统的等效模型;在此基础上,根据不同小区受到的干扰不同,该文提出一种线性干扰对齐算法同时消除小区间干扰和小区内干扰.该算法利用联合信道分解可以先消除一半的小区间干扰,并根据不同小区的用户设计其干扰抑制矩阵,减少了用户端接收矩阵个数及相应处理,从而降低了接收端的复杂度.仿真表明,随着数据流的增加,系统容量和能量效率都有明显的提高,在自由度相同的情况下,天线数不同对系统容量和能量效率有较大影响.     

认知MIMO干扰网络的顽健干扰对齐算法

针对重叠式认知MIMO干扰信道状态信息(CSI)非理想的问题,提出一种顽健干扰对齐算法。首先通过欧几里得球形不确定性刻画非理想CSI,以最小化用户干扰泄漏为目标,构建非理想CSI条件下发送预编码和接收干扰子空间矩阵的优化模型;然后利用矩阵范数的不等式性质,推导了最差条件下的主用户干扰温度约束;最后采用拉格朗日部分对偶及次梯度更新方法,推导出收发矩阵之间的迭代关系,并从理论上分析了顽健算法的适用条件和可达自由度范围。仿真结果表明,所提算法具有较好的顽健性,且获得的次用户网络性能优于已有算法。     

Nash bargaining solution based multi-cell and multi-user interference alignment scheme for cellular networks

In wireless cellular networks, the interference alignment （IA） is a promising technique for interference management. A new IA scheme for downlink cellular network with multi-cell and multi-user was proposed, in the proposed scheme, the interference in the networks is divided into inter-cell interference （ICI） among cells and inter-user interference （IUI） in each cell. The ICI is aligned onto a multi-dimensional subspace by multiplying the ICI alignment precoding matrix which is designed by the singular value decomposition （SVD） scheme at the base station （BS） side. The aligned ICI is eliminated by timing the interference suppression matrix which is designed by zero-forcing （ZF） scheme at the user equipment （UE） side. Meanwhile, the IUI is aligned by multiplying the IUI alignment precoding matrix which is designed based on Nash bargaining solution （NBS） in game theory. The NBS is solved by the particle swarm optimization （PSO） method. Simulations show that, compared with the traditional ZF IA scheme, the proposed scheme can obtain higher data rate and guarantee the data rate fairness of UEs with little additional complexity.     

Hybrid scheme for three-cell multi-user MIMO cellular networks

Orthogonal schemes are usually adopted for cell-edge users in a cellular network, where the spectrum is poorly utilized. A new interference alignment （IA） based space-division hybrid （IA-SDH） scheme is proposed by joint design transmit precoding matrices and beamforming matrices for a three-cell constant cellular network, where users at cell-center work with a conventional scheme while users at cell-edge utilize an IA scheme. Therefore, the cell-edge users suffer no interference and cell-center users are only affected by negligible inter-cell interference. Analysis simulation shows that more users can be served simultaneously than that of a conventional scheme in certain user distributions.     

On the beamforming design for efficient interference alignment

An efficient interference alignment (IA) scheme is developed for k-user single-input single-output frequency selective fading interference channels. The main idea is to steer the transmit beamforming matrices such that at each receiver the subspace dimensions occupied by interference-free desired streams are asymptotically the same as those occupied by all interferences. Our proposed scheme achieves a higher multiplexing gain at any given number of channel realizations in comparison with the original IA scheme, which is known to achieve the optimal multiplexing gain asymptotically.     

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。     

Joint interference alignment precoding based on the optimization algorithm on the Grassmannian manifold

To solve the interference problem between users of the multiuser MIMO system, we first transform the system sum rate maximization problem into joint optimization of interference signal power and useful signal power. On this basis, we propose a weighted interference alignment objective function, causing the system to obtain a higher sum rate by adjusting the weight with different signal-to-noise ratios. Then, we model the transmit subspace and the interference subspace on the Grassmannian manifold and propose joint interference alignment precoding based on the Grassmannian conjugacy gradient algorithm (GCGA-JIAP algorithm). In contrast to conventional interference alignment algorithms, our proposed algorithm can reduce the computational cost by transforming the constrained optimization of the complex Euclidean space into unconstrained optimization with the degenerate dimension on the Grassmannian manifold. Computer simulation shows that the proposed algorithm improves the convergence of the iterative optimization of the transmitter precoding matrix and the receiver postprocessing matrix and also improves the sum rate performance of the multiuser MIMO interference system.     

Fairness Guaranteed Cooperative Resource Allocation in Femtocell Networks

User-deployed low-power femtocell access points (FAPs) can provide better indoor coverage and higher data rates than conventional cellular networks. However, a major problem in this uncoordinated frequency reuse scenario is the inter-cell interference. In this paper, we propose a graph based distributed algorithm called fairness guaranteed cooperative resource allocation (FGCRA) to manage interference among femtocells. Since the optimal resource allocation is a NP-hard problem, which is difficult to get global optimization in femtocell networks, our proposed FGCRA algorithm provides sub-optimal resource allocation via cooperation among interfering neighbors. First, we propose a specific fairness factor obtained from two-hop interference relations, to determine the lower bound amount of subchannels that each FAP can use and guarantee the fairness among femtocells. Second, we propose scalable rules for distributed resource allocation and the solution to avoid the conflicts among interfering neighbors. Simulation results show that our proposed FGCRA significantly enhances both average user throughput and cell edge user throughput, and provides better fairness.     

异构网中基于BD的协作波束赋形算法研究

波束赋形是下一代无线蜂窝网中提高频谱效率的一项重要技术,文中在多用户波束赋形技术的研究基础上,研究了CoMP中的CB技术。针对LTE系统中的小区间干扰严重,且已有的干扰协调技术无法有效解决边缘用户频谱效率低的问题,LTE-A系统引入了多点协作传输/接收技术。该技术通过相邻小区间的联合处理或协作波束赋形,可抑制小区间干扰,提高用户的接收信号质量,使系统容量和小区边缘用户的频谱效率得到有效提高。     

Coverage probability of cellular networks using interference alignment under imperfect CSI

Interference alignment (IA) is well understood to approach the capacity of interference channels, and believed to be crucial in cellular networks in which the ability to control and exploit interference is key. However, the achievable performance of IA in cellular networks depends on the quality of channel state information (CSI) and how effective IA is in practical settings is not known. This paper studies the use of IA to mitigate inter-cell interference of cellular networks under imperfect CSI conditions. Our analysis is based on stochastic geometry where the structure of the base station (BS) locations is considered by a Poisson point process (PPP). Our main contribution is the coverage probability of the network and simulation results confirm the accuracy.     

多天线两小区蜂窝系统的低开销线性干扰对齐算法

在蜂窝系统中,由于干扰的存在,用户性能受到影响,特别是对于小区边缘用户,其通信质量较差。干扰对齐作为一种能够消除干扰、提高系统容量的技术,近年来受到广泛关注。针对多天线两小区蜂窝系统的边缘用户,本文给出了一种系统开销小、需要天线数少的线性干扰对齐算法。该算法利用发送端预编码矢量消除小区内干扰,利用接收端干扰抑制矢量消除小区间干扰。采用本文算法后,在每个小区有 个用户、基站有 根发送天线、用户有 根接收天线的情况下,只需 和 就可以实现上下行的干扰对齐,整个系统可以达到 的自由度,并且在下行链路中不需要小区间反馈,而在上行链路中只需要较小的小区间反馈。仿真结果表明,本文提出的算法能够以较小的开销实现比以往的算法更好的性能。