MIMO系统中的交叉优化调度算法

多入多出（MIMO）系统中在多用户环境下可以在链路级利用空间复用或者在系统级利用多用户调度来提高系统容量。但是仅仅是分别优化MIMO系统链路级性能或是仅仅单纯在系统级进行调度是不够的,将两者联合起来进行优化可以获得更大的系统容量。为此,该文提出了一种新的交叉优化调度算法（Cross Optimization Scheduling Algorithm,COSA）,将系统级的调度策略和链路级的物理层优化相结合,并且采用注水算法动态调整各天线的功率分配。仿真结果表明COSA算法不但在系统级为每个用户提供了公平的接入信道机会,而且在链路级中充分利用MIMO系统的空间复用特点以及动态的功率分配,提高了系统的容量。     

基于多小区容量最大化的分布式功率分配和调度算法

无线数据网络中传输功率和调度算法的联合最优化可以提供可观的系统容量增益,然而,这个问题被认为是在现实中很难解决的。本文中,我们分析一个多小区全复用网络的下行链路,以使它的整个网络容量达到最大化。我们提出了一种分布式功率分配和调度算法,可以为任何有限数量的用户提供很大的容量增益。这种分布式小区协调算法,实际上是动态频谱复用的一种形式,复用的数量随着信道条件的变化而变化。     

基于用户公平性的MIMO-OFDM空间子信道分配算法

对多用户"多入多出-正交频分复用"(MIMO-OFDM)系统的空间子信道分配算法进行了研究,提出了使系统吞吐量最大化并且满足用户速率最小要求的多用户无线资源调度算法.仿真结果表明,与波束形成相比.所提算法具有更好的性能,既充分利用空间子信道,提高了系统容量,又采取有效措施保障了用户的公平性.     

一种低复杂度的MIMO-OFDM下行链路子载波分配改进算法

针对多入多出正交频分复用( MIMO - OFDM)系统的下行链路,提出一种基于信道状态信息(CSI)反馈的次优子载波分配算法.算法从寻求容量和公平性之间的平衡出发,将提高系统容量作为资源分配的优化目标.该算法首先按照比例公平约束进行子载波初始分配,然后将现行分配给任意两个用户的子载波互换之后计算系统容量,如果系统容量增加,则将子载波在用户间进行交换,否则保持初始分配不变.将子载波在用户间进行迭代调整,直到系统总容量不再增加为止.仿真结果表明,该算法能够很好地保证比例公平约束,有效地提高系统容量,提升效率可以达到贪婪算法的40％左右,对MIMO - OFDM系统中的子载波分配具有一定的参考价值.     

基于自适应空分复用的分组多用户分集方案

在采用空分复用技术的多用户多输入多输出下行链路中,有限的空域信道资源限制了系统容量.针对这一问题,提出了一种新的基于自适应空分复用的分组多用户分集方案.针对空分复用算法的特点,该方案首先以信道响应矩阵主右奇异向量的互相关大小为度量,将全部用户分为互相关最小的若干组;然后采用一种新的自适应空分复用算法,求出每一组用户传输时所能获得的系统容量,并将信道分配给容量最大的那一组用户.仿真结果表明,所提出的方案不仅能保证信道资源调度的公平性,而且通过引入多用户分集和自适应空域信道分配,显著地提升了系统容量.     

改进PU2RC算法的多用户MIMO预编码研究

在LTE下行链路的多用户MIMO系统中,基于传统PU2RC算法的预编码方案,由于受正交性约束而使多用户分集增益及系统“和容量”受到限制,对此,提出一种基于改进PU2RC算法的多用户MIMO预编码方案。它通过在基站端增加近距码字集,并对用户集为空集的码字实施二次调度处理,来提高多用户分集增益及系统“和容量”。仿真结果表明,与基于传统PU2RC算法的多用户MIMO预编码系统相比,该方案可以在保持反馈量不变的前提下显著提高系统吞吐量。     

下行MIMO通信系统的多用户分集研究

该文研究了下行多用户MIMO通信系统中多用户分集问题,并且提出了两种基于最大系统容量准则的多用户分组调度算法。提出了一种基于相关用户的信道向量间内积的价值因子。通过使用该价值因子作为信道容量的评价标准,有效地降低了分组调度过程的复杂度。仿真结果显示该文提出的多用户调度算法可以明显提高系统容量;且随着系统中激活用户数量的增加,系统的调度增益不断增大。     

用于有限反馈MIMO系统中的统计多模发射天线选择算法

利用多输入多输出（MIMO）系统中的发射端天线选择算法,可以在降低复杂度的同时,有效地提高系统性能。考虑到基于线性接收机的空间复用系统,在通过已选择的发射天线上采用等功率分配等增益传输可以减少反馈信息量。因此,文章提出了空间相关衰落信道下可提升系统容量的统计多模发射天线选择方法。     

下行多用户MIMO-OFDMA/SDMA系统动态资源分配

该文对下行多用户MIMO-OFDMA/SDMA系统动态资源分配算法进行了研究,在满足各种约束条件的前提下,以最大化系统吞吐量为目标建立了相应的优化模型。由于最优解难以获得,将整个优化过程分两步完成,第1步定义了一个用于度量配置多根天线的用户空间兼容性的指标,并根据该指标提出了相应的调度算法;第2步提出了两种次优的资源分配算法。仿真结果表明,所提算法优于传统的随机调度算法,与功率复用策略结合时,所提算法的性能接近于基于用户选择的最优分配算法的性能。     

MIMO系统一种新的功率分配算法及容量分析

在不额外增加发射功率和带宽消耗的情况下,注水功率分配算法能够获得最大的多输入多输出(MIMO)系统容量.基于拉格朗日乘数法,推导给出了MIMO系统注水功率分配算法的显式解.利用信道冲激响应矩阵的奇异值分解(SVD)算法,推导给出了注水功率分配算法MIMO系统的容量分析公式.利用数字波束形成(DBF)技术,提出了一种新的功率分配算法,推导给出了该算法MIMO系统的容量分析公式.仿真结果表明,提出的功率分配算法的系统容量虽然略低于注水功率分配算法的系统容量,但它的计算复杂度较低.     

Enhancing coverage and capacity for multiuser MIMO systems by utilizing scheduling

Recent studies have revealed that the remarkable capacity improvement resulting from an open-loop multiple-input-multiple-output (MIMO) spatial multiplexing system may come at the sacrifice of degrading link reliability. This tradeoff between antenna multiplexing gain against antenna diversity gain may translate into smaller coverage areas. In this paper, we suggest using the multiuser diversity to replenish the diversity-deficient spatial multiplexing MIMO system. Specifically, we propose a fair scheduling scheme, called the strongest-weakest-normalized-subchannel-first (SWNSF) scheduling, which requires only limited amount of feedback. Our analysis and results indicate that the SWNSF scheduling can significantly increase the coverage of the multiuser MIMO system while further improving the system capacity.     

Simulation Models for Investigation of Multiuser Scheduling in MIMO Broadcast Channels

Spatial correlation is a result of insufficient antenna spacing among multiple antenna elements, while temporal correlation is caused by Doppler spread. This paper compares the effect of spatial and temporal correlation in order to investigate the performance of multiuser scheduling algorithms in multiple‐input multiple‐output (MIMO) broadcast channels. This comparison includes the effect on the ergodic capacity, on fairness among users, and on the sum‐rate capacity of a multiuser scheduling algorithm utilizing statistical channel state information in spatio‐temporally correlated MIMO broadcast channels. Numerical results demonstrate that temporal correlation is more meaningful than spatial correlation in view of the multiuser scheduling algorithm in MIMO broadcast channels. Indeed, the multiuser scheduling algorithm can reduce the effect of the Doppler spread if it exploits the information of temporal correlation appropriately. However, the effect of spatial correlation can be minimized if the antenna spacing is sufficient in rich scattering MIMO channels regardless of the multiuser scheduling algorithm used.     

空分复用多输入多输出系统中的分组多用户分集

该文针对基于空分复用的多用户多输入多输出系统下行链路,研究了空间衰落相关和信道估计误差对系统容量的影响,提出了两种新的分组多用户分集方案。所提出的方案通过合理选择共道用户,能有效提升系统容量,同时兼顾公平性。分析和仿真结果表明,所提出的方案对衰落相关性以及信道估计误差具有较好的稳健性;其中,第2种方案与第1种相比较,容量性能更优,但具有较高的计算复杂度。     

分布式天线系统的多用户分集

分布式天线系统(DAS)由于其具有更大的覆盖范围,较好的功率效率,以及更高的系统容量在近年来备受关注,但很多文献都只是基于以上几个方面进行分析,而没有考虑多用户分集。该文提出了一种考虑用户公平性的最小容量损失轮询调度算法,并以该算法为基础,从多用户分集的角度研究了基于迫零波束成形算法的下行分布式天线系统的信道容量。结果表明,在天线数目和总功率相同的情况下,采用分布式天线系统可以得到比集中放置天线系统(CAS)更大的多用户分集增益。最小容量损失轮询调度算法明显优于普通轮询调度算法,该算法对DAS和CAS都适用。     

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。     

Exploiting Multiuser MIMO in the IEEE 802.11 Wireless LAN Systems

By adopting multiple-input-multiple-output (MIMO) antenna technologies, IEEE 802.11 wireless LANs are evolving into high speed systems. While only one user can transmit at a time in the conventional IEEE 802.11 systems, we investigate the possibility of multiuser transmission by using MIMO antennas, which is now known as multiuser MIMO. The multiuser MIMO technique enables multiple users to receive packets over the downlink simultaneously, but it should be carefully used in the IEEE 802.11 systems for interoperation with non-MIMO legacy terminals. Through analysis and simulation evaluation, we demonstrate that multiuser transmission with a scheduling algorithm and single-user transmission with enhanced spatial multiplexing achieve enhanced performance by exploiting multiuser diversity in the space and time domains. Especially, when the number of stations is large, multiuser transmission shows better performance than enhanced single-user transmission.     

Performance Analysis of Scheduling in Multiuser MIMO Systems with Zero-Forcing Receivers

Despite its low-complexity, the zero-forcing receiver is known to suffer from noise enhancement to restore the spatially multiplexed data in a single-user MI MO system. Nevertheless, in the multiuser system, the poor-channel avoidance property of the scheduling technique provides a natural way to overcome the drawback of noise enhancement (Heath et al., 2001). In this paper, we present an analytical framework to evaluate the performance of the zero-forcing receiver operating in the multiuser MIMO system with user scheduling. Using the order statistics technique, we derive closed-form expressions for the sum-rate capacity of the multiuser MIMO system that employs the simple spatial multiplexing at the transmitter and zero-forcing processing at the receiver with a number of scheduling algorithms. These closed-form expressions hold for an arbitrary finite number of users and facilitate efficient numerical evaluations for cases of practical interest. In addition, the tractable analysis provides insight into how the scheduling technique affects the performance of the multiuser MIMO system under scalar feedback and vector feedback. The results are also extended to the case of heterogonous users with unequal average SNR.     

User Selection Criteria for Uplink Spatial Multiplexing MIMO Systems

We study in this paper multiuser uplink scheduling algorithms for Multiple-Input Multiple-Output (MIMO) systems, where the multiusers compete for the MIMO Channel and the scheduler selects one user at a time based on a certain criterion. Then the selected user spatially multiplexes his data over the transmit antennas. This spatial multiplexing (SM) scheme provides high data rates while the multiuser diversity obtained from scheduling improves the performance of the uplink system. At the receiver, the Vertical-Bell-Labs LAyered Space Time architecture (V-BLAST) is used to detect the information layers. The main contribution of this paper is proposing and comparing the performance of several scheduling criteria for MIMO uplink scheduling. In addition, novel V-BLAST capacity bounds based on random matrix theory is presented. Furthermore, we investigate suboptimal schedulers and compare their performance. The main results of this study show that the scheduler that maximizes the optimal MIMO capacity doesn’t work well for a V-BLAST system. Instead, the optimal scheduler that maximizes the V-BLAST capacity is derived and analyzed. In addition, we look into scheduling for SM with sphere decoding and we find that in this case, using MIMO capacity as the scheduling criterion performs the best.     

MIMO系统中线性弥散空时码的优化设计

MIMO系统的大部分空时编码方法在设计时单一强调对传输分集性能或传输复用性能的提高,为了联合提高分集性能和复用性能,在LDC编码基础上提出了线性正交弥散空时码(OLDC),LDC编码的优化中利用遗传算法来构造OLDC的空时正交调制基矩阵.优化的编码方法设计简单,便于调制解调.仿真结果表明,OLDC码比传统的LDC编码在误码性能、分集性能、复用性能等方面均有大幅度提高.     

An efficient resource-allocation scheme for spatial multiuser access in MIMO/OFDM systems

Fast adaptive transmission has been recently identified as a key technology for exploiting potential system diversity and improving power-spectral efficiency in wireless communication systems. An adaptive resource-allocation approach, which jointly adapts subcarrier allocation, power distribution, and bit distribution according to instantaneous channel conditions, is proposed for multiuser multiple-input multiple-output (MIMO)/orthogonal frequency-division multiplexing systems. The resultant scheme is able to: 1) optimize the power efficiency; 2) guarantee each user's quality of service requirements, including bit-error rate and data rate; 3) ensure fairness to all the active users; and 4) be applied to systems with various types of multiuser-detection schemes at the receiver. For practical implementation, a reduced-complexity allocation algorithm is developed. This algorithm decouples the complex multiuser joint resource-allocation problem into simple single-user optimization problems by controlling the subcarrier sharing according to the users' spatial separability. Numerical results show that significant power and diversity gains are achievable, compared with nonadaptive systems. It is also demonstrated that the MIMO system is able to multiplex several users without sacrificing antenna diversity by using the proposed algorithm.