MIMO系统中随机波束成形算法的研究

文章研究了MIMO(多输入多输出)系统中的随机波束成形(RBF)算法,仿真结果表明:随着用户数的增加,随机波束成形技术可以用最小的反馈获得相干波束成形情况下的吞吐量,并可获得MIMO系统慢衰落信道中下行链路的多用户分集增益和复用增益.     

中继辅助MIMO系统中基于有限反馈的分布式波束成形

对协作式中继辅助的多输入多输出通信系统中基于有限反馈的联合波束成形问题进行了研究.首先推导了接收信噪比的下界,并基于该下界建立联合波束成形的数学模型.其次推导了分布式波束成形的最优方案.最后针对该最优方案,设计了一个迭代算法,优化得到分布式波束成形码本,从而分布式中继站的波束成形可基于码本序号的有限反馈来进行.实验结果仿真表明,所设计的联合波束成形码本在反馈开销很小的情况下获得明显的性能增益.     

基于信道相关统计及有限反馈的多基站协作波束成型

为减少多基站协作波束成形系统中基站间的信息交换量和用户信道信息反馈量,提出一种基站联合利用有限反馈信道参数和信道空间相关矩阵估计信道矢量函数的方法;基于所估计的信道矢量函数,提出一种多基站协作扩展迫零波束成形算法。相比已有的多基站协作波束成形方案,所提算法能在反馈/回程开销和系统性能之间取得更合理的折中,计算仿真验证了所提算法的有效性。     

用于MIMO广播信道的带多波束选择的正交随机波束成形算法

本文提出一种基于有限反馈的波束和用户选择方案,在这种方案中,用户端利用一个随机正交码本对其信道方向信息(CDI)进行量化,计算其最大信号与干扰加噪声功率比(SINR),并把这些信息反馈给基站;基站根据接收到的这些反馈信息,按照和容量最大的准则选择出多个正交波束以及相应的多个用户.和sharif等人最近提出的方案相比,我们提出的方案能根据系统参数,如用户数和信噪比(SNR),对选择的波束成形矢量及其对应的用户的数量和集合进行调整,当用户数量较小时,和容量性能得到了很大的提升,同时避免了选择波束成形矢量时的用户冲突,另外,基站也不需要广播波束成形矢量给各个用户.     

改进的下行MIMO随机波束赋形算法

现有多输入多输出(MIMO)技术中,用户通常选择采用随机波束赋形(RBF)方法,而在用户数较少时,RBF会因为用户信道与发送信道不能准确匹配而使系统吞吐量下降.本文提出了一种改进的随机波束赋形用户选择策略.首先,中心基站发送信道检测信号,然后在用户端进行信道检测与匹配,按照本文提出的矫正算法反馈信道信息,最后基站根据信道反馈信息向用户发送数据.用户选择的判断标准不再是用户信道和随机发射波束的匹配,而改为用户信道校正后的等效信道与随机发射波束的匹配,这样减少了通信中天线间信号干扰,系统性能得到改善.仿真结果表明:与现有的MIMO用户选择策略相比,本文提出的方法在不明显增加运算复杂度的前提下,提高了发送波束与传输信道的匹配,系统吞吐量得到了提高.     

一种基于信干比门限反馈的MIMO下行系统自适应传输策略

以降低系统反馈为目标,提出一种在多天线下行系统基于信干比门限反馈的自适应传输策略.基于正交随机波束成形,提出仅当用户最大信干比超过门限时才将最大信干比和对应的波束序号反馈给基站,并给出了系统平均总速率与该信干比门限的关系表达式.仿真结果表明,通过选取有效的信干比门限,可在几乎不降低总速率的情况下,系统反馈极大降低.     

基于分簇门限反馈的机会波束成形算法研究

在波束间存在干扰的小区通信场景中,研究满足反馈用户数约束条件时,如何有效运用机会波束成形（ORBF）算法实现和速率最大化的问题。针对该问题,提出了一种基于分簇门限反馈的ORBF算法。首先,将问题建模为基于反馈用户数约束的和速率最大化优化问题。然后,根据用户信噪比信息对小区内各用户进行分簇处理,并在各簇内利用极值理论工具独立设置反馈门限。最终,在分簇基础上构造出多门限反馈的ORBF算法。对算法性能进行理论分析,获得了和速率损失量上界的闭合表达式以及多用户分集增益的渐进形式。仿真实验验证了理论分析的正确性,同时表明,该算法与经典ORBF算法相比,能够在极大降低反馈量的同时取得很好的和速率性能。     

多用户MIMO系统在有限反馈下结合预编码与调度算法的研究

捅要：研究了多用户多输入多输出（MIMO）系统在有限反馈下的一种结合单位预编码与用户调度算法的方案。在该系统中每一用户都具有多个接收天线,该方案具有较大的多用户分集增益和较小的计算复杂度,从而能够减少系统中的用户间干扰。每个用户独立地决定自己的天线合并矢量,并将最优波束矢量以及对应的估计信干噪比通过有限反馈信道反馈给基站,此时基站获取了相应的用户信道信息和用户间干扰信息。基于接收到的反馈信息,基站从预定义的码本中选取和速率最大的最优子集进行系统预编码,然后依照预编码矩阵调度欧氏距离最小的用户且用户个数不超过发送天线的数目。仿真结果显示该方案有效地改善了系统速率,特别是在用户数目较多或者信道环境较好的情况下。     

协作式中继增强MIMO通信系统的联合波束成形

本文对协作式中继辅助的多输入多输出(Multiple-input Muhiple-output,MIMO)通信中的联合波束成形问题进行了研究.首先推导了接收信噪比的下界,并基于该下界建立了联合波束成形的数学模型;然后推导了分布式波束成形的最优方案;最后设计了联合优化信源的多天线波束成形和协作式中继的分布式波束成形的算法,从而获得联合波束成形方案.计算机实验仿真表明所提联合波束成形方案获得明显的性能增益.     

MIMO-OFDM系统的自适应多用户分集及性能分析

 本文建立基于随机波束成形和自适应调制的MIMO-OFDM系统的自适应多用户分集系统模型,提出随机波束成形QR接收机的自适应多用户分集资源分配算法及其简化算法,推导在最大化系统吞吐量条件下系统的误码性能.仿真结果表明该算法在用户数很小时使系统性能收敛到特征波束成形系统的性能;当用户数增多时,采用天线分配算法的多用户分集系统能获得比特征波束成形系统更好的性能;将自适应编码调制技术运用到多用户分集系统来提高系统的实际吞吐量和误码性能.     

Enhanced multiuser random beamforming: dealing with the not so large number of users case

We consider the downlink of a wireless system with an M-antenna base station and K single-antenna users. A limited feedback-based scheduling and precoding scenario is considered that builds on the multiuser random beamforming (RBF). Such a scheme was shown to yield the same capacity scaling, in terms of multiplexing and multiuser diversity gain, as the optimal full CSIT-based (channel state information at transmitter) precoding scheme, in the large number of users K regime. Unfortunately, for more practically relevant (low to moderate) K values, RBF yields degraded performance. In this work, we investigate solutions to this problem. We introduce a two-stage framework that decouples the scheduling and beamforming problems. In our scenario, RBF is exploited to identify good, spatially separable, users in a first stage. In the second stage, the initial random beams are refined based on the available feedback to offer improved performance toward the selected users. Specifically, we propose beam power control techniques that do not change the direction of the second-stage beams, offering feedback reduction and performance tradeoffs. The common feature of these schemes is to restore robustness of RBF with respect to sparse network settings (low K), at the cost of moderate complexity increase.     

User Selection Algorithms for MU‐MIMO Systems with Coordinated Beamforming

In this paper, we propose two novel user selection algorithms for multiuser multiple‐input and multiple‐output downlink wireless systems, in which both a base station (BS) and mobile stations (MSs) are equipped with multiple antennas. Linear transmit beamforming at the BS and receive combining at the MSs are used to avoid interference between users and find a better sum‐rate capacity performance. An optimal technique for selecting users would entail an exhaustive search, which in practice becomes computationally complex for a realistic number of users. Suboptimal algorithms with low complexity are proposed for a coordinated beamforming scheme. Simulation results show that the performance of the proposed algorithms is better than that provided by previous algorithms and is very close to an optimal approach with reduced complexity.     

Enhanced Multi-mode Transmission by User Scheduling in MISO Broadcast Channels with Finite-Rate Feedback

This paper investigates the user selection strategy in multiuser downlinks using zero-forcing beamforming (ZFBF) and finite-rate feedback (FRF). In order to mitigate the interference-limited effect in ZFBF-FRF systems, we propose an efficient user scheduling scheme combined with adaptive transmission mode selection strategy. In this scheme, each user first evaluates its preferred transmission mode and the corresponding achievable rate according to a derived tight lower bound of the rate. Given such information on the users through feedback, the BS then determines the global transmission mode of the system and selects users for simultaneous transmission. Asymptotic analysis shows that limited feedback beamforming to a single user is the best choice at both low and high SNR regimes. Simulation results demonstrate individual effects of different system parameters on the sum rate performance by the proposed scheme.     

Effective channel control random beamforming for single user MIMO systems

In general, it has been demonstrated that the performance of conventional random beamforming (RBF) approaches that of ideal eigen beamforming when the number of users is large in a cell by exploiting multi-user diversity. However, if the number of users decreases, such as femto or pico cell in the 3GPP Long Term Evolution-Advanced standard, the performance degradation occurs in the RBF scheme due to the lack of multi-user diversity. In this paper, we present a novel precoder based on singular value decomposition (SVD) using feedback of weight values in an RBF environment. For achieving performance improvement in the femto cell environment, we generate a precoding matrix appropriate to user channel by controlling the feedback values with an equivalent feedback quantity. In the simulation results, we verify the outstanding performance of the proposed scheme for a small number of users.     

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.     

Enhanced Unitary Beamforming Scheme for Limited-Feedback Multiuser MIMO Systems

In this letter, we consider practical downlink multiuser multiple-input multiple-output systems where each user has multiple antennas and codebook-based limited channel feedback is available at base station. We propose a preprocessing scheme for downlink transmission where a unitary beamforming matrix is used. Firstly, we propose how to construct the unitary matrix that maximizes sum rate. Secondly, we propose a codebook-based channel feedback method for the proposed beamforming method. Numerical results show that the proposed scheme outperforms conventional zero-forcing beamforming scheme in terms of sum rate.     

存在信道估计误差的有限反馈多用户多输入多输出传输性能分析

该文针对存在信道估计误差的有限反馈多用户多输入多输出(MIMO)传输性能进行分析。基于量化微元逼近理论得出了多用户迫零波束赋型系统容量的下界;该下界表明：存在信道估计误差时,随着码本尺寸的增大,高信噪比条件下系统容量趋于一有限值;并且,信道估计误差越大,系统容量随码本尺寸收敛越早。进一步分析了采用多用户选择分集的系统容量性能,分析表明,当用户数量趋于无穷大时,和容量有界。该文结果和现有文献的结论不同,并经由仿真结果进行验证。     

Opportunistic Space-Division Multiple Access With Beam Selection

In this paper, a novel transmission technique for the multiple-input multiple-output (MIMO) broadcast channel is proposed that allows simultaneous transmission to multiple users with limited feedback from each user. During a training phase, the base station modulates a training sequence on multiple sets of randomly chosen orthogonal beamforming vectors. Each user sends the index of the best beamforming vector and the corresponding signal-to-interference-plus-noise ratio for that set of orthogonal vectors back to the base station. The base station opportunistically determines the users and corresponding orthogonal vectors that maximize the sum capacity. Based on the capacity expressions, the optimal amount of training to maximize the sum capacity is derived as a function of the system parameters. The main advantage of the proposed system is that it provides throughput gains for the MIMO broadcast channel with a small feedback overhead, and provides these gains even with a small number of active users. Numerical simulations show that a 20% gain in sum capacity is achieved (for a small number of users) over conventional opportunistic space division multiple access, and a 100% gain (for a large number of users) over conventional opportunistic beamforming when the number of transmit antennas is four.     

Joint Optimization of User Set Selection and Transmit Power Allocation for Orthogonal Random Beamforming in Multiuser MIMO Systems

When the number of users is finite, the performance improvement of the orthogonal random beamforming (ORBF) scheme is limited in high signal‐to‐noise ratio regions. In this paper, to improve the performance of the ORBF scheme, the user set and transmit power allocation are jointly determined to maximize sum rate under the total transmit power constraint. First, the transmit power allocation problem is expressed as a function of a given user set. Based on this expression, the optimal user set with the maximum sum rate is determined. The suboptimal procedure is also presented to reduce the computational complexity, which separates the user set selection procedure and transmit power allocation procedure.     

Maximum product of effective channel gains: an innovative user selection algorithm for downlink multi‐user multiple input and multiple output

Recently, zero‐forcing beamforming has been widely used for multiple‐input and multiple‐output broadcast channels, because it could provide suboptimal capacity with low complexity. To increase the sum data rate, a good user selection algorithm is attractive. In this paper, a new user selection algorithm named maximum product of effective channel gains is presented. The proposed algorithm is described mathematically, and the lower bound of the sum capacity is demonstrated to be proportional to the product of effective channel gains. Our simulation results show that maximum product of effective channel gains can achieve higher sum rate compared with the classical algorithm, semi‐orthogonal user selection, with the same complexity order, especially when the signal‐to‐noise ratio is high; in addition, the complexity of the proposed algorithm is superior to minimum of the Frobenius norm of the pseudo‐inverse algorithm. Meanwhile, the number of users that can be served simultaneously is equal to the number of transmission antennas, which is the maximum performance that can be achieved.Copyright © 2012 John Wiley & Sons, Ltd.