Stiefel流形上的单边干扰对齐预编码

干扰对齐通过在接收端重叠干扰能有效的提升干扰信道的容量。单边干扰对齐是指仅仅只有发射端参与的干扰对齐技术,它不需要接收端的参与,与双边干扰对齐技术相比可以大大的减小反馈量。本文在干扰子空间弦距离最小化的改进单边干扰对齐预编码算法方案的基础上,提出将预编码矩阵建模于Stiefel流形上,能够将有约束的最优化问题转化为无约束的最优化问题进行求解。仿真结果表明,将预编码矩阵在Stiefel流形上建模后求解与普通的最优化算法相比有更快的收敛速度和更高的和速率。      

联合信号子空间和功率分配的认知干扰对齐传输方案设计

本文针对由一条授权通信链路和多条次用户干扰信道组成的认知多输入多输出（Multiple Input Multiple Output,MIMO）系统,首先提出了基于信号子空间的认知干扰对齐迭代优化算法,并且利用单调有界理论证明了该算法可以收敛到稳定点。为了进一步提升系统的和速率性能,提出了一种联合信号子空间和功率分配的增强认知干扰对齐算法。该算法通过在每个次用户的多个数据流之间进行自适应功率分配,解决了次用户的有用信号空间中总是有残余的干扰信号的问题。数值仿真结果表明,相对于传统的认知干扰对齐算法,所提的算法能够获得较为明显的性能提升。      

多用户毫米波MIMO系统中基于信道互易性的混合模数预编码算法

本文针对多用户毫米波多输入多输出(Multiple Input Multiple Output,MIMO)系统,首次提出了分离子阵列MIMO混合模数预编码架构毫米波系统的一种模拟接收方案。将最大化和速率求解混合模数预编码的三元联合优化问题分成模拟和数字两部分求解,进一步提出了基于信道互易性的混合模数预编码算法。该算法通过最大化下行各个用户和上行各个子阵列的接收信干噪比分别求解模拟合并矢量和模拟预编码矢量;优化模拟部分后,设计发射端数字预编码器消除多用户数据流之间的干扰。数值仿真表明所提算法收敛速度快,且可获得接近最优纯数字预编码算法的性能。      

Grassmannian precoding MU-MIMO scheme

In this article, a Grassmannian precoding multiuser multiple-input multiple-output （MU-MIMO） scheme for downlink transmission is proposed. The proposed MU-MIMO scheme will perform scheduling and precoding simultaneously at the base station, to obtain both the multiuser diversity gain and the precoding gain, to maximize the system capacity. The precoding method is related to Grassmannian precoding, which extends the point-to-point single-user Grassmannian precoding to point-to-multipoint multiuser Grassmannian precoding. It provides further significant system capacity enhancement than the single user MIMO （SU-MIMO） system and also outperforms the block dia~onalization （BD） algorithm under the same simulation environment.     

一种多用户多中继MIMO通信系统迭代预编码方案

该文针对多中继MIMO通信系统多用户传输时的用户间干扰问题,提出了一种可以有效抑制多用户干扰的发射端与中继端迭代预编码的方案。该方案首先在中继端进行多中继联合的迫零预编码,然后将基站与多用户之间等效为一个点到多点的MIMO信道,采用最大化信漏噪比的预编码方法,在发射端进一步消除用户间的干扰,同时避免了噪声放大的影响,进而通过中继端预编码与发射端预编码的多次迭代,更好地保持了多中继并行传输引入空间分集所带来的性能优势,有效地抑制了用户间干扰,获得了更高的系统和容量。     

Grassmannian流形上基于高分辨率动态聚焦码本的MIMO信道预测

针对MIMO时变信道下,有限反馈发射预编码存在反馈延迟的问题,提出将多数据流空间复用传输的MIMO信道的主右奇异矩阵的列空间建模于n维复欧氏空间上p维子空间的集合Grassmannian流形Gn,p上,利用Grassmannian流形的测地线对时变信道进行跟踪预测,以补偿反馈延迟对于系统性能的影响。在此基础上,从Grassmannian流形的几何特性入手,针对Grassmannian流形的切空间提出了一种高分辨率动态聚焦的多维切空间码本。计算机仿真表明,Grassmannian流形上基于高分辨率动态聚焦码本的有限反馈预测预编码的系统性能明显优于存在反馈延迟的无记忆有限反馈预编码和采用固定码本的有限反馈预测预编码。      

Multiuser precoding techniques for a distributed broadband wireless system

In this paper we propose and asses multiuser linear precoding techniques for the downlink of distributed MIMO OFDM systems. We consider a distributed broadband wireless system where the base stations are transparently linked by optical fiber to a central unit. We further assume that both the distributed base stations and the user terminals are equipped with an antenna array. This architecture provides a high speed backhaul channel allowing an efficient joint multiuser multicell processing. The precoder is designed in two phases: first the intercell interference is removed by applying a block diagonalization algorithm. Then the system is further optimized by using a new power allocation algorithm, based on minimization of the sum of inverse signal-to-noise ratio (SNR^?1) on each user terminal over the available subcarriers. The motivation to minimize the sum of SNR^?1 instead of bit error rate is the fact that the first criterion achieves a closed-form solution, which is more interesting from practical point of view. The aim is to propose a practical distributed precoding technique to remove the intercell interference and improve the user’s fairness at the cell-edges. The performance of the proposed scheme is evaluated and compared with an iterative precoding scheme designed to minimize the bit error rate, extended to the proposed multiuser distributed scenario, considering typical pedestrian scenarios based on LTE specifications.     

Precoding and decoding design for two-way MIMO AF multiple-relay system

In this paper, a joint precoding and decoding design scheme is proposed for two-way Multiple-Input Multiple-Output (MIMO) multiple-relay system. The precoding and decoding matrices are jointly optimized based on Minimum Mean-Square-Error (MMSE) criteria under transmit power constraints. The optimization problem is solved by using a convergent iterative algorithm which includes four sub-problems. It is shown that due to the difficulty of the block diagonal nature of the relay precoding matrix, sub-problem two cannot be solved with existing methods. It is then solved by converting sub-problem two into a convex optimization problem and a simplified method is proposed to reduce the computational complexity. Simulation results show that the proposed scheme can achieve lower Bit Error Rate (BER) and larger sum rate than other schemes. Furthermore, the BER and the sum rate performance can be improved by increasing the number of antennas for the same number of relays or increasing the number of relays for the same number of antennas.     

一种多用户MIMO系统干扰对齐优化算法

干扰对齐技术可以获得干扰信道自由度的最佳值,从而有效改善系统的性能。在实际系统中干扰对齐技术通常采用迭代的方法进行预编码矩阵与干扰抑制矩阵的设计,而迭代方法都需要对发送预编码矩阵进行初始化处理。然而,目前大多数已有的研究所采用的初始化处理方法都忽略了干扰的影响。因此,在此基础上提出了一种基于新的初始化方法的优化算法,该方法在初始化预编码矩阵中既考虑了干扰信号也考虑了有用信号。首先,选取均方误差和最小化作为优化目标,然后利用正交三角（QR）分解将信道空间分为有用信号空间与干扰信号空间来进行预编码矩阵的初始化设计,经过反复迭代得到发送预编码矩阵与干扰抑制矩阵的最优解。理论分析和仿真结果表明,所提算法在收敛性、均方误差、和速率等方面都优于其他算法。     

Penalty function-based precoding for downlink multiuser MIMO systems

In this paper, a novel linear precoding scheme is proposed for downlink multiuser multiple-input multiple-output (MIMO) systems. The new algorithm uses the penalty function method to mitigate the co-channel interference and is formulated as a convex problem with general linear constraints. The constraints can be sum power, per-antenna power or per-antenna-group power constraints, hence the new algorithm is general and can be used in both single-cell and fully cooperative multi-cell scenarios. Moreover, the famous block diagonalization (BD) precoding can be considered as a special case of our method when a very large penalty factor is used. We study the optimal solution of this convex problem and propose an iterative algorithm to obtain the optimum based on the Lagrange dual method. Simulation results show that the proposed method significantly outperforms the BD method at low and moderate SNR values in terms of the weighted sum rate.     

基于人工噪声的多用户MIMO系统加密算法

当多用户MIMO系统中的用户数多于或等于发射端天线数时,现有的基于人工噪声的物理层加密算法会导致合法用户无法正常接收。为提高此时的多用户MIMO系统的安全性,该文提出一种新的基于人工噪声的多用户MIMO系统加密算法。首先,发送端对多个合法用户进行联合处理,建立多用户联合信道状态矩阵;然后,将联合信道状态矩阵进行奇异值分解,并根据最小的奇异值进行预编码,以消除人工噪声对合法用户的影响;最后,提出一种优化功率分配的方案。仿真结果表明,该算法将多用户MIMO系统的保密容量平均增加了0.1 bit/(s?Hz),从而提高多用户MIMO系统的安全性。     

最大化瑞利熵的干扰对齐优化算法

干扰对齐技术常采用迭代的方法进行预编码矩阵与干扰抑制矩阵的设计,然而目前采用的迭代方法并不能做到完全的干扰对齐。针对这种情况,提出了一种新的干扰对齐优化算法,避开了反转信道的操作。该算法在最大化信干噪比算法的基础上加入完全干扰对齐的约束条件,将系统中各用户的所有干扰对齐约束条件进行奇异值分解,最终通过瑞利熵最大化的求解方法联合迭代求解发送侧的预编码矩阵与接收侧的干扰抑制矩阵。仿真结果表明,所提优化算法在较高信噪比时不同天线数下的和速率、不同迭代次数下的和速率等方面都优于原最大信干噪比算法。     

一种低复杂度多用户MIMO预编码方法

针对多用户多输入多输出(MIMO,Multiple Input Multiple Output)系统下行链路,提出了一种基于特定矩阵结构的低复杂度线性预编码方法。该方法利用规则块对角化(RBD,Regularized Block Diagonalization)方法的预编码矩阵具有的内在结构设计预编码矩阵,通过最小化总的干扰与噪声功率之和得到预编码矩阵的最终形式。等效性证明和复杂度分析表明,该方法能够获得与规则块对角化方法相同的"和速率"性能,同时大幅度降低了运算复杂度。仿真实验结果验证了这一结论。     

双向MIMO中继网络中采用信道独立预编码的自干扰消除技术

双向中继网络在提高频谱效率的同时会引入额外的自干扰,本文针对放大转发（AF）模式下双向多输入多输出（MIMO）中继网络中的自干扰抵消问题,从消除信道估计误差引入的剩余自干扰着手,提出一种采用信道独立预编码的盲干扰抵消（BIC）方案。新方案在源节点对信息进行行空间预编码,从而构建不依赖于MIMO信道矩阵的期望信号子空间和自干扰子空间,实现未知信道状态下自干扰抵消和期望信号分离,从而消除非理想信道估计带来的剩余自干扰信号。在此基础上,以最大化有效信噪比为目标设计最佳预编码,通过推导可达和速率的闭合表达式,分析不同方案下信道估计误差对可达和速率的影响。仿真结果表明,新方案在不同的信道估计误差下,能够实现完美自干扰消除,其检测性能和容量均优于基于信道估计的自干扰消除方案。      

一种基于嵌套晶格码的MIMO中继多用户矢量预编码设计

针对多输入多输出(MIMO)中继多用户系统的多址传输问题,为了提高系统可达速率和误码率性能,该文利用嵌套晶格码具有可达加性高斯白噪声信道容量的特性,设计一种基站和中继联合预编码的方法。基站端的嵌套晶格码结合矢量扰动(VP)预编码,以控制发送信号的功率。由于矢量扰动预编码和嵌套晶格码都存在相同的模运算步骤,因此在中继端的模运算抑制噪声功率的同时消除了冗余矢量。接着实现中继联合迫整数预编码方法,这种基站/中继混合预编码技术能够控制等效噪声功率,实现对蜂窝用户的有效信号传输。更进一步地,在给出整系数矩阵和扰动矢量矩阵的计算方法后,以最大化系统可达速率为目标对基站和中继的功率实现最优分配。实验结果表明,该方案在可达速率和误码性能方面优于现有方案。     

Power allocation scheme based on sum capacity maximization for signal‐to‐leakage‐and‐noise ratio precoded multiuser multiple‐input single‐output downlink

This paper proposes a power allocation scheme to maximize the sum capacity of all users for signal‐to‐leakage‐and‐noise ratio (SLNR) precoded multiuser multiple‐input single‐output downlink. The designed scheme tries to explore the effect of the power allocation for the SLNR precoded multiuser multiple‐input single‐output system on sum capacity performance. This power allocation problem can be formulated as an optimization problem. With high signal‐to‐interference‐plus‐noise ratio assumption, it can be converted into a convex optimization problem through the geometric programming and hence can be solved efficiently. Because the assumption of high signal‐to‐interference‐plus‐noise ratio cannot be always satisfied in practice, we design a globally optimal solution algorithm based on a combination of branch and bound framework and convex relaxation techniques. Theoretically, the proposed scheme can provide optimal power allocation in sum capacity maximization. Then, we further propose a judgement‐decision algorithm to achieve a trade‐off between the optimality and computational complexity. The simulation results also show that, with the proposed scheme, the sum capacity of all the users can be improved compared with three existing power allocation schemes. Meanwhile, some meaningful conclusions about the effect of the further power allocation based on the SLNR precoding have been also acquired. The performance improvement of the maximum sum capacity power allocation scheme relates to the transmit antenna number and embodies different variation trends in allusion to the different equipped transmit antenna number as the signal‐to‐noise ratio (SNR) changes.Copyright © 2013 John Wiley & Sons, Ltd.     

MIMO干扰信道下的协作干扰对齐优化算法

干扰对齐是将来自其他发射机的干扰信号对准到同一信号子空间,从而减少对期望信号的干扰的一种传输技术,近年来得到了广泛的关注.本文为K用户多输入多输出(MIMO)干扰信道系统提出了一种协作干扰对齐优化算法.通过对信道的奇异值分解,基于矩阵弦距离,不仅选出一组最好的特征子信道来传输信号,而且还选取一组有利于有用信号远离干扰信号的预编码矩阵,这样,可以最大化减少干扰对有用信号的影响.另外,本文还根据得出的预编码矩阵来计算和优化干扰抑制矩阵.本文算法在没有用迭代的基础上来计算预编码矩阵和干扰抑制矩阵,这样不仅使整个系统的复杂度大大降低,进一步,仿真结果显示容量和能量效率较其他算法有明显改进,这也正是最近受到广泛瞩目的绿色通信所要求的.     

多小区块对角化的MMSE矢量扰动预编码

针对多小区基站协作的多输入多输出(MIMO)系统中,小区之间和用户之间的干扰对系统造成的性能降低的问题,提出了基于块对角化的最小均方误差(MMSE)矢量扰动预编码方案,实现多小区系统的性能改善。首先使用块对角化方法消除多小区间干扰;在预编码设计环节上,通过MMSE准则设计预编码矩阵,从而抑制病态信道对系统性能的影响;最后使用格基规约方法求解发射端矢量扰动信号。仿真表明,提出的算法提高了多小区矢量预编码的误码率性能,使其优于已有的块对角化及矢量扰动预编码等算法的误码率。     

基于连续干扰消除的毫米波MIMO系统混合预编码算法

该文研究多用户毫米波MIMO系统的混合模数预编码器和合并器设计。针对因信号传播漫散射造成的多用户间信号干扰问题,提出一种基于连续干扰消除(SIC)的鲁棒混合预编码算法。首先对信道矩阵进行正交分解,以消除来自已知用户信号的干扰,从而将含有非凸约束的多用户链路优化问题分解为多个单用户链路优化问题。然后采用相位提取算法逐个求解每个用户的最优传输链路,并结合最小均方误差(MMSE)准则求得多用户混合预编码矩阵。仿真结果表明,与现有的混合预编码算法相比,所提算法在强干扰环境下具有显著的性能优势。     

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。