Spatially and temporally correlated MIMO channels: modeling and capacity analysis

Wireless communication systems employing multiple antennas at both the transmitter and receiver have been shown to offer significant gains over single-antenna systems. Recent studies on the capacity of multiple-input-multiple-output (MIMO) channels have focused on the effect of spatial correlation. The joint effect of spatial and temporal correlation has not been well studied. In this paper, a geometric MIMO channel model is presented, which considers motion of the receiver and nonisotropic scattering at both ends of the radio link. A joint space-time cross-correlation function is derived from this model and variates with this joint correlation are generated by using the vector autoregressive stochastic model. The outage capacity of this channel is considered where the effects of antenna spacing, antenna array angle, degree of nonisotropic scattering, and receiver motion are investigated. When n transmit and n receive antennas are employed, it is shown that the outage capacity still increases linearly with respect to n, despite the presence of spatial and temporal correlation. Furthermore, analytical expressions are derived for the ergodic capacity of a MIMO channel for the cases of spatial correlation at one end and at both ends of the radio link. The latter case does not lend itself to numerical evaluation, but the former case is shown to be accurate by comparison with simulation results. The proposed analysis is very general, as it is based on the transmit and receive antenna correlations matrices.     

An Improved Simulator for the Correlation-Based MIMO Channel in Multiple Cluster Scattering Environments

An improved MIMO radio channel simulator is proposed, based on the most popular correlation-based MIMO channel model called Kronecker model and the sum-of-sinusoids (SoS) method which is widely used to generate Rayleigh fading waveforms with temporal correlation. Firstly, a simplified simulation model for generating multiple independent Rayleigh fading waveforms is presented, which employs only one random variable to set all Doppler frequency components in all waveforms. Next, a fast spatial correlation calculation technique, in a closed-form expression implemented by the Fourier Transform both for outdoor and indoor multiple cluster scattering environments, is introduced, which accurately reproduces the desired spatial correlation properties and indicates a direct dependence between spatial correlation and channel physical parameters. The ergodic and outage capacity of the simulated channel are also evaluated with respect to different azimuth of arrival and azimuth of departure (AoA/AoD) under the condition of 3GPP SCM (3rd Generation Partnership Project Spatial channel model) [23]. The presented simulator is therefore suitable for the theoretical analysis of MIMO radio systems, including dynamic system simulation.     

A stochastic multipath channel model including path directions for indoor environments

A novel stochastic channel model for the indoor propagation channel is presented. It is especially for, but not limited to future communication systems with multiple antennas like space division multiple access (SDMA), spatial filtering for interference reduction (SFIR), or multiple-input/multiple-output (MIMO). The model is designed for indoor scenarios, straight forward extendable to urban environments. It is based on physical wave propagation. The new approach describes the channel by multipath components, each characterized by its transfer matrix (including loss), delay, direction of arrival, and departure. The appearance and disappearance of multipath components over time is modeled as a birth and death process, a marked Poisson process. This enables first-time the correct modeling of spatial and temporal correlations. In each modeling step, path properties change according to the motion of transmitter and receiver. The changing delay times of propagation paths yield a realistic Doppler behavior of the channel. Deterministic ray tracing results are used to produce the huge data sets required for the statistical evaluation of the parameters of the proposed model. This method enables an automated parameter extraction for new environments or frequencies. The ray tracing tool has been verified by narrowband, wideband, and directional channel measurements. The novel stochastic spatial channel model allows the simulation of third-generation broadband radio systems including arbitrary antenna configurations and patterns. System simulations for the bit-error rate of radio links can be performed including intelligent antenna configurations like SDMA, SFIR, or MIMO. Furthermore, the capacity of complete systems can be investigated.     

基于阵列流形分离的多输入多输出信道模型

基于三维阵列流形分离技术,建立了一种天线独立的随机多输入多输出(MIMO)信道模型。将天线阵列的导向矢量进行球谐基函数展开,实现了天线阵列和无线传播环境的分离。对分离出的无线传播环境部分单独进行基于空间相关性的统计建模,得到了一种天线独立的解析MIMO信道模型。所建模型可方便用于MI-MO系统性能评估与分析设计。以圆柱阵列和球阵列为例,仿真验证了新模型的正确性和有效性。     

Environmental issues for MIMO capacity

Wireless communication using multiple-input multiple-output (MIMO) systems enables increased spectral efficiency for a given total transmit power. Increased capacity is achieved by introducing additional spatial channels that are exploited using space-time coding. In this paper, the environmental factors that affect MIMO capacity are surveyed. These factors include channel complexity, external interference, and channel estimation error. The maximum spectral efficiency of MIMO systems in which both transmitter and receiver know the channel (using channel estimate feedback) is compared with MIMO systems in which only the receiver knows the channel. Channel complexity is studied using both simple stochastic physical scattering and asymptotic large random matrix models. Both uncooperative (worst-case) and cooperative (amenable to multiuser detection) interference are considered. An analysis for capacity loss associated with channel estimation error at the transmitter is introduced.     

一种基于随机散射簇的非平稳3D空间信道模型

针对大规模MIMO信道的近场效应和非平稳特性,该文提出适用大规模MIMO信道的一种基于随机散射簇的非平稳3D空间信道模型。采用抛物波前代替球面波前建模近场效应,并分析抛物波前条件下该模型的信道容量。对于大规模MIMO信道的非平稳特性,提出基于散射簇的有效概率确定收发天线阵元的有效散射簇集合,从而建模散射簇沿天线阵列轴的随机演变来合理描述散射簇的出现和消失。仿真结果表明,用抛物波前和有效散射簇的随机演变来建模大规模MIMO信道特征是很好的候选方法。     

一种新的MIMO信道模型

实际无线通信环境中发送天线之间以及接收天线之间存在相关性.针对以上特点,从多径MIMO信道的特性出发,首先建立发射天线相关系数矩阵和接收天线相关系数矩阵,并将它们引入无线信道的莱斯MIMO信道模型中.最后通过分析LOS MIMO信道相关模型和瑞利衰落MIMO信道相关模型,给出了具体的建模步骤.仿真结果表明采用本文方法产生的信道模型的MIMO系统误码率更低,从而验证了该信道模型能够较好地模拟MIMO系统的空间信道.     

基于空时相关性的MIMO无线信道建模及仿真

针对多输入多输出无线信道的空时相关性，文章提出了一种改进的MIMO无线信道模型。该模型利用改进的Jakes模型仿真器来产生独立同分布零均值的复高斯随机变量，从而保证各个传播路径间的相关性很小。仿真结果表明改进的MIMO无线信道模型能够准确的描述出空时相关的MIMO无线信道的统计特性，即空间相关性随天线单元间距增大而战小，随散射信号角度扩展增大不是一致减小．     

A performance comparison of the SCM and the Onering channel modeling method for MIMO‐OFDMA systems

This paper compares two types of channel modeling methods, which are the spatial channel modeling (SCM) and the Onering channel modeling method. These two well‐known channel models are proposed for 4G wideband mobile communication networks. To compare the performance of these channel modeling methods, we analyze the properties of the spatial, temporal, frequency correlation functions simulated by using these methods. The correlation functions of the two channel models are compared in the same conditions of antenna arrangements. The simulation and calculation results show that the correlation functions of Onering and SCM channel models are very close to each other if the BS and the MS antenna arrays are parallel and perpendicular to the broadside of MS‐BS. In other cases, the correlation functions of the two models are slightly different; however, their shapes are similar. These differences can be explained that the Onering model hardly fully describes all the characteristics of 4G channels as the performance SCM model does. The performance of these channel modeling methods is compared in system simulation level—MIMO‐OFDMA systems. The combination SFBC‐MMSE is used for spatial channel coding and the signal detection. The simulation results show that the system performance obtained by using these two channel models are comparable, given that the both modeled channels have same parameters and antenna directions. Copyright © 2016 John Wiley & Sons, Ltd.     

An Extended One-Ring MIMO Channel Model

In this paper we develop a multiple input multiple output (MIMO) channel model and derive its spatial and temporal correlation properties. We present a generalized methodology to derive the spatial correlation when the angles of arrival (AoA) and angles of departure (AoD) are either independent or partly correlated. Our model therefore spans the full range from well-established single ring models, where AoA and AoD are fully correlated to complex industrial channel models where they are uncorrelated. It is shown that first order and second order approximations to the channel give rise to a single- Kroneckermodel and a sum-Kroneckermodel respectively. We compare our model to other MIMO channel models in terms of correlation structure and the ergodic mutual information (EMI) and study the effect of the non-Kronecker correlation structure.     

Experimental validation of analytical MIMO channel models

The promise of multiple-input multiple-output systems (MIMO) to overcome the radio bottleneck in high-speed data transmission requires detailed models of the spatio-temporal MIMO channel to come true. In this paper, popular MIMO channel models are compared with two independent measurement campaigns at 2 and 5 GHz by using four different, mostly novel performance figures (or metrics). Each of these metrics describes one or more different aspects of MIMO, such as multiplexing gain, spatial diversity, or beamforming. Of the models investigated, the Weichselberger model performs overall best, whereas the Kronecker model should be used only for limited antenna numbers, such as 2 × 2, and “the virtual channel representation” only for very large antenna numbers.     

A stochastic MIMO radio channel model with experimental validation

Theoretical and experimental studies of multiple-input/multiple-output (MIMO) radio channels are presented. A simple stochastic MIMO model channel has been developed. This model uses the correlation matrices at the mobile station (MS) and base station (BS) so that results of the numerous single-input/multiple-output studies that have been published in the literature can be used as input parameters. The model is simplified to the narrowband channels. The validation of the model is based upon data collected in both picocell and microcell environments. The stochastic model has also been used to investigate the capacity of MIMO radio channels, considering two different power allocation strategies, water filling and uniform and two different antenna topologies, 4/spl times/4 and 2/spl times/4. Space diversity used at both ends of the MIMO radio link is shown to be an efficient technique in picocell environments, achieving capacities within 14 b/s/Hz and 16 b/s/Hz in 80% of the cases for a 4/spl times/4 antenna configuration implementing water filling at a SNR of 20 dB.     

MIMO信道在巷道中的GBDB模型分析

多输入多输出(MIMO)技术可以有效减弱无线传输多径衰落现象。建立矿井巷道环境下MIMO信道的三维GBDB模型,推导了该模型的空时相关函数,并对矿井下MIMO信道容量进行了数值仿真。结果表明,矿井巷道中的空间相关性对MIMO系统容量的影响很大,增加接收端天线数量、增大天线间距可以大幅度提高系统的信道容量。     

Outdoor MIMO wireless channels: models and performance prediction

We present a new model for multiple-input-multiple-output (MIMO) outdoor wireless fading channels and their capacity performance. The proposed model is more general and realistic than the usual independent and identically distributed (i.i.d.) model, and allows us to investigate the behavior of channel capacity as a function of the scattering radii at transmitter and receiver, distance between the transmit and receive arrays, and antenna beamwidths and spacing. We show how the MIMO capacity is governed by spatial fading correlation and the condition number of the channel matrix through specific sets of propagation parameters. The proposed model explains the existence of "pinhole" channels which exhibit low spatial fading correlation at both ends of the link but still have poor rank properties, and hence, low ergodic capacity. In fact, the model suggests the existence of a more general family of channels spanning continuously from full rank i.i.d. to low-rank pinhole cases. We suggest guidelines for predicting high rank (and hence, high ergodic capacity) in MIMO channels, and show that even at long ranges, high channel rank can easily be sustained under mild scattering conditions. Finally, we validate our results by simulations using ray tracing techniques. Connections with basic antenna theory are made.     

Sampling-based soft equalization for frequency-selective MIMO channels

We consider the problem of channel equalization in broadband wireless multiple-input multiple-output (MIMO) systems over frequency-selective fading channels, based on the sequential Monte Carlo (SMC) sampling techniques for Bayesian inference. Built on the technique of importance sampling, the stochastic sampler generates weighted random MIMO symbol samples and uses resampling to rejuvenate the sample streams; whereas the deterministic sampler, a heuristic modification of the stochastic counterpart, recursively performs exploration and selection steps in a greedy manner in both space and time domains. Such a space-time sampling scheme is very effective in combating both intersymbol interference and cochannel interference caused by frequency-selective channel and multiple transmit and receiver antennas. The proposed sampling-based MIMO equalizers significantly outperform the decision-feedback MIMO equalizers with comparable computational complexity. More importantly, being soft-input soft-output in nature, these sampling-based MIMO equalizers can be employed as the first-stage soft demodulator in a turbo receiver for coded broadband MIMO systems. Such a turbo receiver successively improves the receiver performance through iterative equalization, channel re-estimation, and channel decoding. Finally, computer simulation results are provided to demonstrate the performance of the proposed sampling-based soft MIMO equalizers in both uncoded and turbo coded systems.     

MIMO无线通信系统的信道建模

MIMO信道的空时特性是决定空时信号处理的关键,一个体现信道衰落特性的MIMO信道模型对MIMO技术的研究和应用是至关重要的。本文回顾了MIMO信道建模的发展,阐述了几个典型的信道模型,指出其适用范围,给出了几个需进一步考虑的关键特性。     

Modeling, analysis, and simulation of MIMO mobile-to-mobile fading channels

This paper' deals with the modeling, analysis, and simulation of multiple-input multiple-output (MIMO) narrowband fading channels for mobile-to-mobile communications. A stochastic MIMO mobile-to-mobile reference channel model is derived from the geometrical two-ring scattering model under the assumption that both the transmitter and the receiver are surrounded by an infinite number of local scatterers. Using a wave propagation model, the complex channel gains are derived and their statistical properties are studied. General analytical solutions are provided for the three-dimensional (3-D) space-time cross-correlation function (CCF). We show that this function can be expressed as the product of two 2D space-time cross-correlation function (CFs), called the transmit and receive CF. From the non-realizable reference model, a stochastic and a deterministic simulation model are derived using a double sum of complex exponential functions. It is shown how the parameters of the simulation model can be determined for any given distribution of the angle of departure (AOD) and angle of arrival (AOA). In case of isotropic scattering, we present a closed-form solution for the parameter computation problem and illustrate some numerical results concerning the transmit CF. The proposed procedure provides an important framework for designers of future mobile-to-mobile communication systems to verify new transmission concepts employing MIMO techniques under realistic propagation conditions.     

基于稀疏贝叶斯学习的MIMO-OFDM电力线通信系统接收机设计

丰富的脉冲噪声干扰对基于MIMO-OFDM技术的电力线通信系统接收机设计带来了巨大挑战。针对这个问题,提出了一种联合估计电力线信道和脉冲噪声的接收机设计方案。该方案主要利用电力信道多径模型参数在频域上的稀疏性和脉冲噪声在时域上的稀疏性特征,将待估计信道模型参数和脉冲噪声联合视作一个稀疏向量,同时利用MIMO系统的空间相关性,构建了一个基于多测量向量的压缩感知模型,并引入多测量向量稀疏贝叶斯学习理论,设计了一种联合估计MIMO信道模型参数和脉冲噪声的方法。仿真结果表明,与传统的MIMO信道估计与脉冲噪声抑制相互分离的接收机方案相比,新方法在估计性能和误比特率性能上有明显提升。