Turbo-BLAST系统中基于容量的天线选择和功率分配算法

在不完全信道状态信息条件下,提出了一种适用于Turbo BLAST系统的天线选择和功率分配算法。所提算法以信道容量最大化为准则,从所有天线中选取一组天线子集用于发射,并对选择的天线子集进行注水功率分配,以充分利用Turbo BLAST系统的空间复用增益并提高信道容量。在接收端,采用Turbo原理对接收信号进行迭代检测以改善系统的误比特率性能。仿真结果表明采用所提算法不仅可以显著提高系统的信道容量, 而且误比特率性能也得到明显的改善。      

大规模MIMO相关信道下的联合天线分组和天线选择

在大规模多输入多输出系统中,针对密集部署的大型天线阵列之间的强相关性会抑制天线选择增益效果的问题。在系统下行链路场景下建立空间相关信道模型,提出了基于天线分组的天线选择算法。根据瞬时信道相关矩阵将天线阵列划分为若干组,保证各组内天线之间相关性较强。在完成天线分组的基础上,基于信道矩阵列范数准则在各组发射天线与接收天线之间构成的子信道矩阵中选择天线,进而构造有效发射天线与接收天线之间的信道矩阵。仿真分析了所提天线选择算法对系统遍历和速率的影响,结果表明,在基站天线数为32、接收天线数为2、选择天线数为2、天线相关因子为0.9的假设下,当信噪比为10 dB时,与基于相邻天线分组的天线选择算法相比,所提算法使系统和速率约提高了27.5%,且所提算法若要与最优天线选择算法达到相同的和速率,仅需将其信噪比提升1～2 dB即可。     

窄带波束信道MIMO系统的容量分析

最近的研究表明,多输入多输出(MIMO)技术在不增加功率和带宽消耗的情况下具有大幅提高无线通信速率的潜力.在传统的MIMO系统(称为天线信道MIMO系统)中,多个接收天线的输出被直接选作多输出信号.提出了波束信道MIMO系统的结构.在波束信道MIMO系统中,多个波束的输出被选作多输出信号.基于阵列方向响应矢量,提出了窄带MIMO信道冲激响应矩阵的仿真算法.基于提出的信道冲激响应矩阵算法,给出了天线信道MIMO系统和波束信道MIMO系统容量极限的分析算法.理论分析和仿真结果都表明:波束信道能够提高信噪比(SNR),降低信道间的互相关性,因此波束信道MIMO系统比天线信道MIMO系统具有更大的容量极限.     

基于增量和减量选择规则的天线选择与链路自适应

针对不相关MIMO和相关MIMO信道系统,提出了基于增量和减量选择规则的联合天线选择和链路自适应算法。具体实现是首先构建出受系统施加的总吞吐量和功率约束的MIMO系统的联合天线选择和链路自适应最优化问题;然后对于不相关MIMO信道系统,提出了带链路自适应的增量和减量的天线选择规则,增量选择将所需的天线递归地添加到初始为空的有源天线集合中,减量选择将不需要的天线递归地从初始为满的天线集合中移除,对于相关MIMO信道系统,基于慢变信道协方差信息,提出了一种带链路自适应的增量天线选择规则,从而得到2种情形在总吞吐量和功率约束下的误码率最小化;实验结果表明,本文提出的算法相比于传统的天线选择算法不仅有更低的误码率,而且对于不同反馈延迟有着较好的鲁棒性。     

基于容量的MIMO信道发射天线选择算法

当前的MIMO系统是在假设接收端已知信道信息(CSI)而发射端未知CSI的情况下进行研究的.本文提出的发射天线选择算法是用极小的信息反馈量,即反馈一组最优的发射天线子集,就可使信道容量得到很大的增加,较传统的注水算法而言,反馈量大大减少,而容量只略微减少,从而大大降低了反馈信道的带宽.     

基于MUSIC和ML方法的MIMO系统参数估计

该文提出了一种基于MUSIC和ML方法联合估计MIMO系统频偏和信道增益的算法,该算法首先使用MUSIC方法估计出多个发射天线到某一接收天线的频偏子集,然后利用最大似然方法在这个有限子集中分离出不同天线对之间的频偏,最后在频率同步的基础上利用最大似然估计器对信道增益进行估计。该算法解决了在估计多个频偏时直接使用最大似然估计进行多维搜索的问题,将多维搜索转化为一维搜索,降低了算法的复杂度。     

空间复用系统在相关信道下的两步选择天线算法

针对采用贝尔实验室垂直分层空时(V-BLAST)检测算法的空间复用系统存在信道相关的问题,提出一种新的两步选择发射天线的准则,首先利用信道矩阵奇异值确定有效发射天线数,然后根据最低检测后信噪比确定发射天线和子数据流之间的映射关系.仿真结果表明两步选择准则能获得比已有算法更高的选择增益,此外还分析并仿真了天线间距和角度扩展对符号向量错误概率的影响.     

多天线认知无线电网络多信道联合频谱感知策略

当前,以单天线认知用户组成的认知无线电网络同时协作检测多个信道的分配策略得到了广泛研究,而在认知用户可以灵活选取自身天线进行空间分集接收的条件下,当联合感知多信道时,多天线认知无线电网络如何获取最优的天线分配策略仍有待进一步研究。为解决这一问题,在限制各信道最大虚警概率的前提下,以最小化所有信道漏检概率之和为目标,建立了优化模型,并提出了基于分支定界的算法和基于贪婪思想的启发式算法。前者可以获得最优策略,但复杂度较高,后者以牺牲较小检测性能为代价,明显降低了复杂度,有效实现了检测性能与复杂度的平衡,并且在保护各个信道上主用户免受认知用户干扰层面,一定程度上兼顾了公平性。      

基于特征值估计的发射天线选择算法

现有的大多数发射天线选择算法都是假设信道是独立衰落的,这与实际的传播环境不相符。文章在相关信道的前提下研究MIMO(多输入多输出)系统,提出一种新的基于特征值估计的发射天线选择算法。算法通过特征值下界估计的方法,每次迭代中选择使信道矩阵最小特征值下界最大的列,来提高最小特征值并降低小天线间的相关性,使得容量最大化并使误码率最小化。理论分析结果表明,该算法在所选天线数目较多场合下具有较低的复杂度,同时其容量和误码性能优于随机选择算法,接近最优选择算法。     

多径信道下MIMO系统发送天线数估计

为了解决认知无线电或信号截获中多径信道下MIMO系统发送天线数估计问题,首先分析了现有模型在多径信道下失效的原因,将MIMO多径信道模型等效变换出一种虚拟信道矩阵,从而建立多径信道下MIMO系统发送天线数估计模型;然后,利用随机矩阵理论中协方差矩阵最小特征值分布的相关研究结果,证明了时不变瑞利信道的协方差矩阵最小特征值收敛于第二类Tracy-Widom分布,分析了该特点对发送天线数估计的影响,并提出一种改进的RMT估计算法来估计多径信道下MIMO系统发送天线数.最后对改进算法进行了仿真验证,结果表明在低信噪比和小数据条件下,改进算法的估计性能相比RMT算法有较大提升.     

MIMO antenna subset selection with space-time coding

This paper treats multiple-input multiple-output (MIMO) antenna subset selection employing space-time coding. We consider two cases differentiated based on the type of channel knowledge used in the selection process. We address both the selection algorithms and the performance analysis. We first consider the case when the antenna subsets are selected based on exact channel knowledge (ECK). Our results assume the transmission of orthogonal space-time block codes (with emphasis on the Alamouti (see IEEE J. Select. Areas Commun., vol.16, p.1451-68, Oct. 1998) code). Next, we treat the case of antenna subset selection when statistical channel knowledge (SCK) is employed by the selection algorithm. This analysis is applicable to general space-time coding schemes. When ECK is available, we show that the selection algorithm chooses the antenna set that maximizes the channel Frobenius norm leading to both coding and diversity gain. When SCK is available, the selection algorithm chooses the antenna set that maximizes the determinant of the covariance of the vectorized channel leading mostly to a coding gain. In case of ECK-based selection, we provide analytical expressions for average SNR and outage probability improvement. For the case when SCK-based selection is used, we derive expressions for coding gain. We also present extensive simulation studies, validating our results.     

Limited feedback unitary precoding for orthogonal space-time block codes

Orthogonal space-time block codes (OSTBCs) are a class of easily decoded space-time codes that achieve full diversity order in Rayleigh fading channels. OSTBCs exist only for certain numbers of transmit antennas and do not provide array gain like diversity techniques that exploit transmit channel information. When channel state information is available at the transmitter, though, precoding the space-time codeword can be used to support different numbers of transmit antennas and to improve array gain. Unfortunately, transmitters in many wireless systems have no knowledge about current channel conditions. This motivates limited feedback precoding methods such as channel quantization or antenna subset selection. This paper investigates a limited feedback approach that uses a codebook of precoding matrices known a priori to both the transmitter and receiver. The receiver chooses a matrix from the codebook based on current channel conditions and conveys the optimal codebook matrix to the transmitter over an error-free, zero-delay feedback channel. A criterion for choosing the optimal precoding matrix in the codebook is proposed that relates directly to minimizing the probability of symbol error of the precoded system. Low average distortion codebooks are derived based on the optimal codeword selection criterion. The resulting design is found to relate to the famous applied mathematics problem of subspace packing in the Grassmann manifold. Codebooks designed by this method are proven to provide full diversity order in Rayleigh fading channels. Monte Carlo simulations show that limited feedback precoding performs better than antenna subset selection.     

Adaptive transmit antenna selection with pragmatic space-time trellis codes

We consider the problem of selecting a subset of transmit antennas in MIMO systems to minimize error probability when only partial channel information is available at the transmitter. An upper bound for error probability of space-time coded transmit antenna selection scheme conditioned on the channel state information is presented. Based on the performance analysis, a criterion of selecting a subset of available transmit antennas to minimize the upper bound on the PEP is proposed. In contrast to other transmit antenna selection schemes for uncoded transmission or with a fixed number of antennas within the selection subset in the literature, the proposed scheme can adaptively select both a variable number of transmit antennas and their corresponding space-time codes for transmission. Furthermore, we present pragmatic space-time trellis coding schemes for slow Rayleigh fading channels. The principal advantage of the schemes is that a single encoder and decoder can be used for systems with a variable number of transmit antennas. The performance of the pragmatic space-time codes with adaptive antenna selection and the effect of the imperfect channel estimation on performance are evaluated by simulations. It is shown that the adaptive selection offers considerable antenna selection gain relative to the antenna selection system with a fixed number of antennas within the selection subset     

Receive antenna selection for unitary space-time modulation over semi-correlated Ricean channels

Receive antenna selection for unitary space-time modulation (USTM) over semi-correlated Ricean fading channels is analyzed (this work generalizes that of Ma and Tepedelenlio-glu for the independent and identically distributed (i.i.d.) Rayleigh fading case). The antenna selection rule is that the receive antennas with the largest signal powers are chosen. For single antenna selection, we derive the maximum likelihood decoding for the correlated Ricean case. We also derive the Chernoff bound on the pairwise error probability for the high signal to- noise ratio (SNR) region and obtain the coding gain and diversity order. Our results show that even when there are transmitter side correlations and a line of sight component, receive antenna selection with USTM preserves the full diversity order if the USTM constellation is of full rank. We also give an approximation to the distribution function of a quadratic form of non-zero mean complex Gaussian variates (from Nabar et al.) at the high SNR region. Based on this approximation, a closed-form expression for the coding gain is also obtained and compared with that of the i.i.d. Rayleigh case. We also analyze the case of multiple receive antenna selection and derive the coding gain and diversity order. We show that USTM constellations, which have been proposed for the i.i.d. Rayleigh channel, can be used with the correlated Ricean channel as well.     

Transmit antenna selection in linear receivers: geometrical approach

Transmit antenna subset selection in spatial multiplexing systems is considered. In particular, selection algorithms aiming to minimise the error rate when linear detectors are used at the receiver are proposed. Previous work on antenna selection has considered capacity and post-processing SNR selection criteria. However, a geometrical interpretation of the decoding process which also permits development of a suboptimal algorithm that yields a considerable complexity reduction with only a small loss in performance, is considered.     

Antenna selection for multiple-antenna transmission systems: performance analysis and code construction

This correspondence studies antenna selection for wireless communications systems that employ multiple transmit and receive antennas. We assume that (1) the channel is characterized by quasi-static Rayleigh flat fading, and the subchannels fade independently, (2) the channel state information (CSI) is exactly known at the receiver, (3) the selection is available only at the receiver, and it is based on the instantaneous signal-to-noise ratio (SNR) at each receive antenna, and (4) space-time codes are used at the transmitter. We analyze the performance of such systems by deriving explicit upper bounds on the pairwise error probability (PEP). This performance analysis shows that (1) by selecting the set of antennas that observe the largest instantaneous SNR, one can achieve the same diversity gain as the one obtained by using all the receive antennas, provided that the underlying space-time code has full spatial diversity, and (2) in the case of rank-deficient space-time codes, the diversity gain may be dramatically reduced when antenna selection is used. However, we emphasize that in both cases the coding gain is reduced with antenna selection compared to the full complexity system. Based on the upper bounds derived, we describe code design principles suitable for antenna selection. Specifically, for systems with two transmit antennas, we design space-time codes that perform better than the known ones when antenna selection is employed. Finally, we present numerical examples and simulation results that validate our analysis and code design principles.     

非相干天线选择算法

基于广义似然比检验(GLRT)与天线选择相结合,提出了平瑞利衰落信道的非相干天线选择(NON-AS)算法,天线选择和信号检测无需信道状态信息.NON-AS算法适用于多输入多输出(MIMO)系统的接收端,接收天线选择是基于每个天线瞬时接收到信号矢量的F-2范数.与相干检测的天线选择相比,NON-AS算法不需要估计信道,大大降低了系统复杂性.成对错误概率分析和仿真结果表明:在高信噪比情况下,选择有最大范数的接收天线,系统能实现和使用全部接收天线相同的分集增益.     

Transmit Antenna and User Selection for Multiuser Spatial Multiplexing with Maximum Likelihood Receiver

In this paper, we consider a transmit antenna and user selection for maximum-likelihood (ML) detector in multiuser spatial multiplexing systems. The conventional algorithm that maximizes the minimum stream SNR is not optimal in terms of the error probability, because it is tailored for linear detectors. We propose a simple transmit antenna and user selection scheme for the ML detector based on maximizing the minimum distance. Numerical results show that the proposed scheme provides enhanced performance compared with the conventional algorithms in terms of the error probability of ML receiver.