MIMO信道中衰落信号的空域相关性评估

将MIMO(多输入多输出)信道建立为Nakagami衰落信道,进一步推导单元天线接收多径衰落信号的空域相关系数的通用解析式,并在均匀分布、余弦分布、高斯分布和拉式分布的来波功率角谱下分别进一步评估接收信号的空域相关性,分析各参数对相关系数的影响,比较各种来波功率角谱下相关性的数值结果,这些对于准确分析MIMO系统性能与设计MIMO多天线系统是十分必要的.     

相关信道下MIMO信道容量优化算法的研究

该文研究MIMO系统收发端天线采用均匀线阵且放置空间有限,存在相关衰落时信道容量的优化方法。采用规范化信道模型,分析了信道相关性对平均信道容量和最优信号协方差矩阵的影响,推导了最优协方差矩阵的一阶条件;利用Jensen's不等式确定了信道容量的上界,给出了闭式解,并对相关信道下信号的传输模式进行了讨论。仿真结果表明,采用该优化方法,在各种SNR下,其平均容量接近Jensen's上界;得出信道相关程度对信道平均容量的影响依赖于信噪比的结论。     

多输入多输出系统信道容量研究

该文研究接收端采用均圆阵天线阵放置空间有限的条件下,存在相关衰落时MIMO系统的信道容量。建立了衰落相关模型,分析了散射角大小及天线数对信道容量的影响,采用随机理论推导了MN的MIMO系统信道容量的闭式解。分析结果表明,MIMO系统信道容量主要由衰落相关矩阵的特征值决定。仿真结果表明,在接收端空间有限的情况下,天线数增大到一定程度时,信道容量达到饱和,再增加天线数,对信道容量的影响很小。     

Optimal transmission strategies and impact of correlation in multiantenna systems with different types of channel state information

We study the optimal transmission strategy of a multiple-input single-output (MISO) wireless communication link. The receiver has perfect channel state information (CSI), while the transmitter has different types of CSI, i.e., either perfect CSI, or no CSI, or long-term knowledge of the channel covariance matrix. For the case in which the transmitter knows the channel covariance matrix, it was recently shown that the optimal eigenvectors of the transmit covariance matrix correspond with the eigenvectors of the channel covariance matrix. However, the optimal eigenvalues are difficult to compute. We derive a characterization of the optimum power allocation. Furthermore, we apply this result to provide an efficient algorithm which computes the optimum power allocation. In addition to this, we analyze the impact of correlation on the ergodic capacity of the MISO system with different CSI schemes. At first, we justify the belief that equal power allocation is optimal if the transmitter is uninformed and the transmit antennas are correlated. Next, we show that the ergodic capacity with perfect CSI and without CSI at the transmitter is Schur-concave, i.e., the more correlated the transmit antennas are, the less capacity is achievable. In addition, we show that the ergodic capacity with covariance knowledge at the transmitter is Schur-convex with respect to the correlation properties. These results completely characterize the impact of correlation on the ergodic capacity in MISO systems. Furthermore, the capacity loss or gain due to correlation is quantified. For no CSI and perfect CSI at the transmitter, the capacity loss due to correlation is bounded by some small constant, whereas the capacity gain due to correlation grows unbounded with the number of transmit antennas in the case in which transmitter knows the channel covariance matrix. Finally, we illustrate all theoretical results by numerical simulations.     

Correlation and channel capacity of MIMO systems employing multimode antennas

A novel way of exploiting higher modes of antennas as diversity branches in multiple-input-multiple-output (MIMO) systems is introduced. Essentially, antennas employing multiple modes offer characteristics similar to an antenna array, through multiple modes and using only a single element. The physical mechanism that yields different received signals is the fact that each mode has a different radiation pattern. Analytical expressions for the correlation between signals received by different modes are presented for a biconical and a circular microstrip antenna that employs higher order modes. It is found that the correlation is low enough to yield a significant diversity gain. Furthermore, the channel capacity of a MIMO system using a multimode antenna, i.e., an antenna employing multiple modes, is found to be comparable to the capacity of an array. Since only one element is needed, the multimode antenna offers several advantages over traditional arrays, and is an interesting antenna solution for future high capacity MIMO systems.     

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.     

Multiple-antenna capacity in correlated Rayleigh fading with channel covariance information

We analyze a mobile multiple input multiple output wireless link with M transmit and N receive antennas operating in a spatially correlated Rayleigh flat fading environment. Only the correlations between the channel coefficients are assumed to be known at the transmitter and the receiver. The channel coefficients are correlated in space and uncorrelated in time from one coherence interval to another. These coefficients remain constant for a coherence interval of T symbol periods after which they change to another independent realization according to the spatial correlation model. For this system we characterize the structure of the input signal that achieves capacity. The capacity achieving transmit signal is expressed as the product of an isotropically distributed unitary matrix, an independent nonnegative diagonal matrix and a unitary matrix whose columns are the eigenvectors of the transmit fade covariance matrix. For the case where the number of transmit antennas M is larger than the channel coherence interval T, we show that the channel capacity is independent of the smallest M-T eigenvalues of the transmit fade covariance matrix. In contrast to the previously reported results for the spatially white fading model where adding more transmit antennas beyond the coherence interval length (M>T) does not increase capacity, we find that additional transmit antennas always increase capacity as long as their channel fading coefficients are spatially correlated with the other antennas. We show that for fast hopping or fast fading systems (T=1) with only channel covariance information available to the transmitter and receiver, transmit fade correlations are beneficial. Mathematically, we prove this by showing that capacity is a Schur-convex function of the vector of eigenvalues of the transmit fade correlation matrix. We also show that the maximum possible capacity gain due to transmitter fade correlations is 10logM dB.     

The Downlink Capacity of Single-User SA-MIMO System

In this paper, a novel multiple antenna system framework, which combines smart antennas (SA) with multiple-input-multiple-output (MIMO) at the transmitter, is proposed. The downlink capacity of the single-user SA-MIMO wireless systems is investigated. The joint optimization problem corresponding to the capacity is deduced. After that, upper bounds of the capacity are given in general case and in the case of equal power allocation, respectively. Furthermore, in the case of equal power allocation and the same direction of departure from one transmit smart antenna to all antenna arrays at the receiver the closed-form expression of the capacity is obtained. Some numerical results are given to show that smart antennas can bring significant capacity gain for the MIMO systems due to the smart antennas gain, without additional spatial degrees of freedom, especially at high SNR with strong correlation among the MIMO channel links or at low SNR.     

A rigorous proof of MIMO channel capacity’s increase with antenna number

It is well known that adding more antennas at the transmitter or at the receiver may offer larger channel capacity in the multiple-input multiple-output（MIMO） communication systems. In this letter, a simple proof is presented for the fact that the channel capacity increases with an increase in the number of receiving antennas. The proof is based on the famous capacity formula of Foschini and Gans with matrix theory.     

Joint antenna selection and link adaptation for MIMO systems

Multi-input multi-output (MIMO) systems, with multiple antennas at both the transmitter and the receiver, are anticipated to be widely employed in future wireless networks due to their predicted tremendous system capacity. To protect the transmitted data against random channel impairment, it is desirable to consider link adaptation, such as rate adaptation and power control, to improve the system performance and guarantee certain quality of service. Based on the observation that link adaptation and antenna selection problems are often coupled, we propose a joint antenna subset selection and link adaptation study for MIMO systems. After the formulation of the multidimensional joint optimization problem, the main contribution of this paper lies in the design of efficient algorithms approaching the optimal solution for both uncorrelated and correlated MIMO channels. Specifically, we propose one simplified antenna selection and link adaptation rule based on the expected optimal number of active antennas for uncorrelated MIMO with Rayleigh fading and one for correlated MIMO channels only based on the slowly varying channel correlation information. Our proposed algorithms are verified through numerical results, demonstrating significant gains over traditional MIMO signaling, while feasible for practical implementation.     

Channel capacity of MIMO architecture using the exponentialcorrelation matrix

Multiple-input multiple output (MIMO) communication architecture has recently emerged as a new paradigm for wireless communications in rich multipath environment, which has spectral efficiencies far beyond those offered by conventional techniques. The channel capacity of the MIMO architecture in independent Rayleigh channels scales linearly as the number of antennas. However, the correlation of a real-world wireless channel may result in a substantial degradation of the MIMO architecture performance. In this letter, we investigate the MIMO channel capacity in correlated channels using the exponential correlation matrix model. We prove that, for this model, an increase in correlation is equivalent to a decrease in signal-to-noise ratio (SNR). For example, r=0.7 is the same as 3-dB decrease in SNR     

MIMO channel capacity and modeling issues on a measured indoor radio channel at 5.8 GHz

Multiple transmitters and receivers can be used to provide high link capacity in future wireless systems. Herein, an analysis of indoor environment multiple-input-multiple-output (MIMO) measurements in the industrial, scientific, and medical (ISM) band at 5.8 GHz is performed and the possible increase in capacity, utilizing multiple transmitters and receivers is examined. The investigation shows that in the measured indoor environment, the scattering is sufficiently rich to provide substantial link capacity increases. Furthermore, the effect of intra-element spacing on the channel capacity is studied. Our investigation also shows that the envelope of the channel coefficients for this obstructed-line-of-sight (OLOS) indoor scenario is approximately Rayleigh distributed and the MIMO channel covariance matrix can be well approximated by a Kronecker product of the covariance matrices describing the correlation at the transmitter side and the receiver side, respectively. A statistical narrowband model for the OLOS indoor MIMO channel based on this covariance structure is presented.     

MIMO Ricean channel capacity: an asymptotic analysis

This paper presents asymptotic bounds and limits for the mean channel capacity of MIMO systems under Ricean channel conditions. It is shown that the mean capacity per dimension decreases as the K factor increases in value and approaches a value equal to that of the underlying scattering channel when the number of antennas are large and the specular matrix has unit rank. The accuracy of the bounds is verified by simulations. In addition, a variety of results for the MIMO Ricean channel are brought together to give an overview of the current knowledge in this area. We also show that the variance of the capacity for a Ricean channel approaches that of the scattering channel for large numbers of antennas.     

基于共轭梯度法的低复杂度信道估计

考虑在大规模MIMO系统中基于导频的信道估计,基站端配置有数百根天线,传统的MMSE估计器虽然在估计精度上有着良好的性能,但是由于在利用MMSE方法进行信道估计时,存在对协方差矩阵求逆的运算,导致其计算复杂度为OM3,其中M为信道协方差矩阵的维度。在基站天线数很大的时候,这将是一个极其复杂的过程。为解决这个问题,将通过将求逆过程转化为解线性方程组的问题,利用共轭梯度法,使整个计算过程的计算复杂度降为ONM2,其中N为共轭梯度法的迭代次数,而且N<相似文献   

一种自适应MIMO信号发射与检测方法研究

无线通信中的多天线(MIMO)技术是提高系统容量的主要方法,在慢衰落信道下可以将接收端获得的信道信息(CSI)反馈到发送端以提高系统的性能.传统的反馈-预编码方案奇异值分解(SVD)法但受空间相关特性和传统VBLAST系统对收、发天线数目要求的影响而限制了它在实际系统中的应用.该文提出一种自适应多天线传输方案,其采用了统一信道参数反馈模型和空时分组编码(STBC),实现了一种可以用于各种空间相关特性和各种收、发天线数的多天线传输方案可以克服SVD方案的以上缺点.文中仿真也验证了该系统的接收天线可以比发射天线少,并且能够在高相关性信道下工作.     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

3×3多天线系统衰落相关与信道容量研究

为分析天线间距和散射角等信道物理参数对多输入多输出系统信道容量的影响,提出了一种相关衰落环境中信道容量的分析方法。该方法基于接收均匀圆阵构建了蕴含信道物理参数的衰落相关矩阵。并由此详细推导了3×3多天线系统信道容量的闭式表达。结果表明,相关矩阵特征值的个数和大小决定了系统信道容量的大小。该方法回避了已有算法需求取相关衰落信道特征值概率密度函数的问题,降低了运算量,可以被推广到任意收发天线数的多输入多输出和多输入多输出-频分复用系统。仿真结果表明,天线间距增大,信道容量随之增大。但是当天线间距增大到衰落相关的第一个过零点时,信道容量达到最大值,再增大天线间距对信道容量影响很小。散射角越大,信道容量收敛到最大值速率越快。     

Capacity of multiple-antenna fading channels: spatial fading correlation, double scattering, and keyhole

The capacity of multiple-input multiple-output (MIMO) wireless channels is limited by both the spatial fading correlation and rank deficiency of the channel. While spatial fading correlation reduces the diversity gains, rank deficiency due to double scattering or keyhole effects decreases the spatial multiplexing gains of multiple-antenna channels. In this paper, taking into account realistic propagation environments in the presence of spatial fading correlation, double scattering, and keyhole effects, we analyze the ergodic (or mean) MIMO capacity for an arbitrary finite number of transmit and receive antennas. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is allocated to each of the transmit antennas. Using some statistical properties of complex random matrices such as Gaussian matrices, Wishart (1928) matrices, and quadratic forms in the Gaussian matrix, we present a closed-form expression for the ergodic capacity of independent Rayleigh-fading MIMO channels and a tight upper bound for spatially correlated/double scattering MIMO channels. We also derive a closed-form capacity formula for keyhole MIMO channels. This analytic formula explicitly shows that the use of multiple antennas in keyhole channels only offers the diversity advantage, but provides no spatial multiplexing gains. Numerical results demonstrate the accuracy of our analytical expressions and the tightness of upper bounds.     

An Efficient CSI Feedback Scheme for MIMO-OFDM Wireless Systems

For antenna-array-based multiple-input multiple- output orthogonal-frequency-division-multiplexing (MIMO-OFDM) wireless systems, gain in channel throughput reduced through sufficient feedback of the channel state information (CSI) is significant, particularly when the number of transmit antennas is larger than the number of receive antennas. In this letter, we demonstrate that, in such scenarios, (1) the CSI of each OFDM sub-carrier can be parameterized into a short bit stream by a proposed low-complexity QR decomposition on the corresponding MIMO channel matrix, (2) the overall CSI can be reliably represented by a proposed parameter interpolation on the above bit streams of only a fraction of sub-carriers, and (3) a MIMO-OFDM system with a low-rate CSI feedback parameterized above can provide a channel throughput comparable to the channel capacity.     

基于天线互耦影响的大规模MIMO TDD系统信道互易性校准算法

射频器件的非理想性和信道的时变特性影响大规模多输入多输出（multiple-input multiple-output，MIMO）系统时分双工（time division duplex，TDD）模式的信道互易性，天线阵列的耦合效应影响信道矩阵的相关性.文中提出一种基于互耦影响的大规模MIMO互易性联合校准算法，将天线之间的互耦效应引入信道矩阵，采用OTA（over-the-air）校准算法和基于自回归（auto-regression，AR）模型预测信道矩阵相结合的方案实现同时校准射频非理想性和信道时变特性引起的互易性损失.仿真结果表明，该算法能够提高系统容量，降低误码率，有效地补偿互易性损失.本文算法可以为大规模MIMO系统的多因素联合校准提供参考.