Robust and Improved Channel Estimation Algorithm for MIMO-OFDM Systems

Multiple-input multiple-output (MIMO) system using orthogonal frequency division multiplexing (OFDM) technique has become a promising method for reliable high data-rate wireless transmission system in which the channel is dispersive in both time and frequency domains. Due to multiple cochannel interferences in a MIMO system, the accuracy of channel estimation is a vital factor for proper receiver design in order to realize the full potential performance of the MIMO-OFDM system. A robust and improved channel estimation algorithm is proposed in this paper for MIMO-OFDM systems based on the least squares (LS) algorithm. The proposed algorithm, called improved LS (ILS), employs the noise correlation in order to reduce the variance of the LS estimation error by estimating and suppressing the noise in signal subspace. The performance of the ILS channel estimation algorithm is robust to the number of antennas in transmit and receive sides. The new algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator. Also, with respect to mean square error criterion and without using channel statistics, the ILS algorithm achieves a performance very close to that of the minimum mean square error (MMSE) estimator in terms of the parameters used in practical MIMO-OFDM systems. A modification of the ILS algorithm, called modified ILS (MILS), is proposed based on using the second order statistical parameters of channel. Analytically, it is shown that the MILS estimator achieves the exact performance of the MMSE estimator. Due to no specific data sequences being required to perform the estimation, in addition to the training mode, the proposed channel estimation algorithms can also be extended and used in the tracking mode with decision-aided method.     

单载波宽带MIMO系统广义近似消息传递Turbo频域均衡

针对编码单载波循环前缀(SC-CP)多输入多输出(MIMO)系统,该文采用消息传递算法研究软输入软输出MIMO频域均衡器(FDE)的设计问题。基于广义近似消息传递(GAMP)算法,该文提出一种新的低复杂度MIMO频域均衡方法。这种消息传递MIMO均衡方法的显著特点是既保留了SC-CP传输所产生的频域均衡的优点,同时又避免了传统MIMO FDE中逐频点MIMO矩阵求逆运算,所以具有随MIMO系统接收天线数增加而线性增长的计算复杂度。计算机仿真结果表明,与传统方案相比,该文提出的MIMO频域均衡算法具有明显的误码率(BER)性能优势。     

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.     

Blind adaptive MIMO receivers for space-time block-coded DS-CDMA systems in multipath channels using the constant modulus criterion

We propose blind adaptive multi-input multi-output (MIMO) linear receivers for DS-CDMA systems using multiple transmit antennas and space-time block codes (STBC) in multipath channels. A space-time code-constrained constant modulus (CCM) design criterion based on constrained optimization techniques is considered and recursive least squares (RLS) adaptive algorithms are developed for estimating the parameters of the linear receivers. A blind space-time channel estimation method for MIMO DS-CDMA systems with STBC based on a subspace approach is also proposed along with an efficient RLS algorithm. Simulations for a downlink scenario assess the proposed algorithms in several situations against existing methods.     

Coordinated beamforming with limited feedback in the MIMO broadcast channel

In this paper, we propose a new joint optimization of linear transmit beamforming and receive combining vectors for the multiple-input multiple-output (MIMO) broadcast channel. We consider the transmission of a single information stream to two users with two or more receive antennas. Unlike past work in which iterative computation is required to design the beamformers, we derive specific formulations for the transmit beamformers for two active users via a power iteration and a generalized eigen analysis. To enable practical implementation, a new limited feedback algorithm is proposed that exploits the structure of the algorithm to avoid full channel quantization. The feedback overhead of the proposed algorithm is independent of the number of receive antennas. Monte Carlo simulations are used to evaluate the bit error rate and the sum rate performances of the proposed algorithm. Simulation results show that the proposed method performs close to the sum capacity of the MIMO broadcast channel even with limited feedback.     

Robust subspace blind channel estimation for cyclic prefixed MIMO ODFM systems: algorithm, identifiability and performance analysis

A novel subspace (SS) based blind channel estimation method for multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this work. With an appropriate re-modulation on the received signal blocks, the SS method can be effectively applied to the cyclic prefix (CP) based MIMO-OFDM system when the number of the receive antennas is no less than the number of transmit antennas. These features show great compatibility with the coming fourth generation (4G) wireless communication standards as well as most existing single-input single-output (SISO) OFDM standards, thus allow the proposed algorithm to be conveniently integrated into practical applications. Compared with the traditional SS method, the proposed algorithm exhibits many advantages such as robustness to channel order over-estimation, capability of guaranteeing the channel identifiability etc. Analytical expressions for the mean-square error (MSE) and the approximated Cramer-Rao bound (ACRB) of the proposed algorithm are derived in closed forms. Various numerical examples are conducted to corroborate the proposed studies.     

Reduced-Complexity Time-Domain Equalization for Turbo-MIMO Systems

A reduced-complexity time-domain equalization scheme for wideband turbo-multiple-input multiple-output (turbo-MIMO) systems is presented. This scheme, called iterative trellis search equalization, is based on a modified version of the M-Bahl-Cocke-Jelinek-Raviv (M-BCJR) algorithm, applied to a suitably chosen trellis representation of the wideband MIMO channel process. Exploiting the properties of quadrature amplitude modulation (QAM) signal constellations with block-partitionable labels, this modified M-BCJR algorithm has complexity per bit that is independent of the constellation size, and polynomial in the number of transmit antennas and channel memory. Results from computer simulations show that the new scheme successfully mitigates intersymbol interference even if only a very small fraction of trellis state transitions is considered. It is also demonstrated that asynchronous transmission of the spatially multiplexed symbol streams can result in considerable performance improvement compared to synchronous MIMO systems.     

基于奇异值分解的MIMO-OFDM系统角域MAP信道估计算法

最大后验概率信道估计算法应用于多输入多输出-正交频分复用(MIMOOFDM)系统时需要大规模的矩阵求逆和乘积运算,且系统数据传输效率随发送天线数的增加明显降低.为克服这些问题,提出了一种基于奇异值分解的角域最大后验概率信道估计算法.该算法通过期望最大化把(MIMO)信道估计问题简化为一系列独立的单输入单输出(SISO)问题,并使用奇异值分解避免了大规模矩阵求逆和乘积运算;通过多个OFDM符号联合估计信道提高了系统数据传输效率及算法的估计性能.仿真实验验证了此算法的有效性.     

Exact bit error probabilities and packet error statistics for SVD transmission over time-varying dual-branch MIMO systems obtained by a Markov model

Using a finite state Markov channel model, we develop an analytical method for evaluation of the packet error structure in multiple-input multiple-output (MIMO) systems based on singular value decomposition (SVD). We consider dual-branch MIMO systems, with either two transmit and arbitrary number of receive antennas, or arbitrary number of transmit and two receive antennas. The corresponding Markov model parameters are obtained using a novel closed-form expressions for probability density function and level crossing rate of the signal-to-noise ratio at the output of eigenchannels in a MIMO system, derived for a case of Rayleigh propagation, imperfect channel state information and any fixed power allocation. The exact bit error rate for the transmission of quadrature amplitude modulated (QAM) symbols through the eigenchannels is derived in polynomial closed form. Furthermore, by using the developed Markov model, the packet error statistics in the corresponding eigenchannels are determined, and the closed-form analytical expression for the system throughput is derived when ‘go-back-N’ automatic repeat request procedure is applied in time-varying eigenchannels. The analytical results are validated by using Monte Carlo simulations.     

MIMO系统中一种改进的盲MMSE空时多用户检测算法

针对MIMO系统,提出了一种改进的基于子空间的盲MMSE空时多用户检测算法。该算法结合MIMO系统的空间分集技术与Alamouti空时分组码方案,预估计MIMO信道信息并对信号子空间进行预处理,使用正交性能和稳态性能较好的NOOja算法跟踪信号子空间,在自适应过程中对特征值矩阵进行优化,去除迭代带来的噪声,解决了跟踪过程中信号特征值矩阵的近似估计会带来检测器性能恶化的问题。仿真结果表明这种算法,能有效地抑制多址干扰,抗远近效应能力强,尤其在低信噪比、远近效应明显的恶劣环境下,有稳定良好的性能表现。      

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.     

MIMO-OFDM系统中信道盲估计与检测

针对MIMO-OFDM系统,提出了一种基于子空间的盲信道估计与检测方案,该算法将阵列信号处理的思想应用到MIMO-OFDM系统中,通过发送端信号的冗余编码,利用一种类ESPRIT算法进行盲信号检测和信道估计。仿真结果表明该算法的有效性及其信道盲估计方法的性能。     

MIMO Radar Space–Time Adaptive Processing Using Prolate Spheroidal Wave Functions

In the traditional transmitting beamforming radar system, the transmitting antennas send coherent waveforms which form a highly focused beam. In the multiple-input multiple-output (MIMO) radar system, the transmitter sends noncoherent (possibly orthogonal) broad (possibly omnidirectional) waveforms. These waveforms can be extracted at the receiver by a matched filterbank. The extracted signals can be used to obtain more diversity or to improve the spatial resolution for clutter. This paper focuses on space-time adaptive processing (STAP) for MIMO radar systems which improves the spatial resolution for clutter. With a slight modification, STAP methods developed originally for the single-input multiple-output (SIMO) radar (conventional radar) can also be used in MIMO radar. However, in the MIMO radar, the rank of the jammer-and-clutter subspace becomes very large, especially the jammer subspace. It affects both the complexity and the convergence of the STAP algorithm. In this paper, the clutter space and its rank in the MIMO radar are explored. By using the geometry of the problem rather than data, the clutter subspace can be represented using prolate spheroidal wave functions (PSWF). A new STAP algorithm is also proposed. It computes the clutter space using the PSWF and utilizes the block-diagonal property of the jammer covariance matrix. Because of fully utilizing the geometry and the structure of the covariance matrix, the method has very good SINR performance and low computational complexity.     

Performance analysis of uplink spatial multiplexing MIMO MT‐CDMA over multipath fading channels

In this paper, we consider multiple‐input multiple‐output (MIMO) multi‐tone code division multiple access (MT‐CDMA) uplink transmission over multipath fading channels. The zero‐forcing vertical Bell Laboratories layered space‐time architecture (ZF V‐BLAST) algorithm and maximum ratio combining scheme are applied at the receiver. The average bit error rate (BER) expression is derived provided that the number of receive antennas is not less than that of transmit antennas. The BER expression is verified by simulations. Numerical results show that the numbers of transmit and receive antennas have significant effects on the BER performance of the considered system. Spatial and path diversity show different capabilities to improve the BER performance. The MIMO MT‐CDMA system based on the ZF V‐BLAST algorithm is capable of achieving a better BER performance and a higher capacity than the conventional MT‐CDMA system. Copyright © 2011 John Wiley & Sons, Ltd.     

空时编码多载波码分多址MIMO系统下行频率选择性信道盲估计

基于子空间方法的无线信道盲估计由于其算法的固有特性,使得估计结果与实际信道之间存在一个不确定复系数,无法得到无线信道的精确估计。在利用子空间分解方法对空时编码多输入多输出MC-CDMA系统下行频率选择性信道盲估计的基础上,利用发射符号的有限码集特性,将单载波系统下的模糊复系数盲辨识方法推广到多载波多输入多输出系统,从而得到信道的精确估计。Monte-Carlo仿真表明,在信噪比较低的情况下,本方法的信道估计误差仍然较小。     

Beam Tracking Particle Filter for Hybrid Beamforming and Precoding Systems

Because millimeter wave (mmWave) systems can span notably wide spectral bands, mmWave systems are expected to dominate fifth-generation (5G) communication systems. Due to the short wave-length of mmWave radiation, multiple-input multiple-output (MIMO) systems can use massive antennas and precoding technology to overcome signal attenuation in mmWave channels. However, the cost and power consumption of radio frequency (RF) chains would increase substantially with the number of antennas. Hence, hybrid beamforming was proposed to reduce the number of RF chains in massive MIMO systems. Hybrid beamforming involves RF beamforming matrix construction and baseband precoding matrix derivation. This study focused on the design and implementation of an algorithm for the RF beamforming matrix construction for mobile environments. Accordingly, this study presents a mixture particle filter that exploits the temporal continuity of beam clusters in a mobile mmWave channel to reduce the computational complexity of RF beamforming matrix construction. Moreover, this beam-tracking particle filter is based on parallel processing architecture to support the tracking of multiple beam clusters in the mmWave channel. Finally, the beam-tracking particle filter was implemented on a field-programmable gate array platform and was verified in a hybrid beamforming system for mmWave MIMO systems. The particle filter processor achieved a maximal throughput of 9.198k matrices/s with a clock rate of 192 MHz, which could support a speed of up to 88.5 km/h for mobile users.

     

一种有效的MIMO-OFDM系统MAP信道估计

对于MIMO-OFDM系统,最大后验概率(MAP)信道估计算法可通过期望最大化(EM)算法降低计算复杂度,但将产生误差平底(error floor)现象。并且,系统的数据传输效率受限于发送端天线的数目。针对这些问题,该文提出了一种有效的MAP信道估计算法,并分析了算法的性能。所提算法在利用EM算法减小MAP 算法计算复杂度的基础上,利用角域内信道间的独立性降低估计误差。为改善系统数据传输效率及估计性能,通过多个OFDM符号进行联合的信道估计。仿真实验验证了所提算法拥有更好的估计性能和数据传输效率。     

Implementation of a MIMO OFDM-based wireless LAN system

The combination of multiple-input multiple-output (MIMO) signal processing with orthogonal frequency division multiplexing (OFDM) is regarded as a promising solution for enhancing the data rates of next-generation wireless communication systems operating in frequency-selective fading environments. To realize this extension of OFDM with MIMO, a number of changes are required in the baseband signal processing. An overview is given of the necessary changes, including time and frequency synchronization, channel estimation, synchronization tracking, and MIMO detection. As a test case, the OFDM-based wireless local area network (WLAN) standard IEEE 802.11a is considered, but the results are applicable more generally. The complete MIMO OFDM processing is implemented in a system with three transmit and three receive antennas, and its performance is evaluated with both simulations and experimental test results. Results from measurements with this MIMO OFDM system in a typical office environment show, on average, a doubling of the system throughput, compared with a single antenna OFDM system. An average expected tripling of the throughput was most likely not achieved due to coupling between the transmitter and receiver branches.     

一种MIMO中继系统的自适应自干扰消除方法

为节省频率资源,全双工中继一般采用相同的频率接收和发射信号。由于收发天线之间无法充分隔离,接收天线容易受到自身发射天线的回波干扰。针对宽带全双工多输入多输出( MIMO)中继的自干扰问题,提出了一种基于梯度下降自适应算法的自干扰消除方法。该方法利用中继反馈的已知信号进行自干扰信道估计,并产生一个对自干扰信号的估计信号,从而在接收端将干扰抑制。仿真结果表明,该方法在自适应滤波器的跟踪性能、收敛分布和不同 MIMO 配置下的均方误差( MSE)性能等方面均取得良好效果。     

基于空间分集的MIMO雷达目标跟踪算法研究

针对基于空间分集的多输入多输出(MIMO)雷达多发多收的特殊结构,建立了基于逆协方差形式扩展卡尔曼滤波算法的MIMO雷达目标跟踪滤波模型,分析了影响算法滤波精度的4个因素,分别为信噪比、信号带宽、天线数以及天线与目标间的位置关系。通过使目标位置状态估计均方误差最小,在特定天线数条件下利用数值方法得到了使滤波精度达到最优的天线放置形式。仿真实验给出了不同信噪比、信号带宽、天线数以及天线与目标间不同位置关系时的MIMO雷达跟踪性能。