A subspace blind channel estimation method for OFDM systems without cyclic prefix

We propose a subspace based blind channel estimation method for orthogonal frequency-division multiplexing (OFDM) systems over a time-dispersive channel. Our approach is motivated by the resemblance of the multichannel signal model resulting from oversampling (or use of multiple receive sensors) of the received OFDM signal to that in conventional single carrier system. The proposed algorithm distinguishes itself from many previously reported channel estimation methods by the elimination of the cyclic prefix, thereby leading to higher channel utilization. Comparison of the proposed method with other two reported subspace channel estimation methods is presented by computer simulations to support its effectiveness.     

循环前缀块传输系统中的一种MIMO盲信道估计算法

信道估计一直是无线通信领域的研究热点之一,信道参数估计的好坏对系统的整体性能有着至关重要的影响。针对采用循环前缀的多输入多输出(MIMO-CP)系统,本文提出了一种基于子空间的盲信道估计方法,该算法利用了循环前缀所引起的冗余信息。基于子空间的盲信道估计算法都是通过对接收块的自相关矩阵进行奇异值分解(SVD)来实现信道估计的,因此需要利用尽可能多的接收块来得到准确的自相关矩阵的估计值,这就意味着会产生过久的判决延迟以及不能准确对快变信道进行跟踪。利用MIMO-CP系统中系统矩阵特有的块循环特性,对于连续的两个接收数据块以及对应的循环前缀部分组成的向量,可以重新构造一组新的向量而不改变系统的信道矩阵,因此可以通过较少的接收块来得到准确的自相关矩阵的估计值,该方法十分适用于对快变信道的盲估计。文章通过仿真分析了在不同的重复系数以及不同的接收块下该算法的性能并且比较了该算法与现有的“预编码”、“虚拟子载波”等盲信道估计算法的性能。仿真结果表明,提出的算法利用较少的数据块个数就得到了一个可靠的信道估计值和很好的误码率性能。      

Robust blind channel estimation algorithm for linear STBC systems using fourth order cumulant matrices

A novel blind channel estimation algorithm, based on fourth-order cumulant matrices, is proposed and applied to linear Space–Time Block Coded (STBC) for Multiple Input Multiple Output systems. Contrary to subspace and Second-Order Statistics (SOS) methods, the presented approach estimates the channel matrix without any modification of the transmitter. It takes advantage of the statistical independence of the signals in front of the space–time encoding. In this paper, the presented algorithm estimates the channel matrix by minimizing a cost function based on the higher cumulant matrices after Zero-Forcing equalization to mitigate the computational complexity and improve the performance. We employ the proposed method to the STBC systems including Spatial Multiplexing, Orthogonal, quasi-Orthogonal and Non-Orthogonal STBC systems. Symbol error rate and Normalized Mean Square Error simulations of the proposed algorithm are shown for a different number of users, signal to noise ratios and different number of symbols per user in comparison with subspace and Second-Order Statistics (SOS) methods. The results show that the presented method performs well and outperforms other methods in estimating the channel matrix from the received data. Moreover, the proposed method presents high convergence speed in estimating the channel matrix.     

OFDM系统信道盲估计的一种新算法

利用循环前缀（CP）引入的信息冗余，在利用接受信号的二阶统计特性实现正交频分复用（OFDM）系统信道盲估计的子空间算法基础上，采用矩阵变换的方法，改善信息序列的非周期相关函数，推导出信道估计的新算法。     

Subspace projection based blind channel order estimation of MIMO systems

In this paper, a novel algorithm based on subspace projections is developed for blindly estimating the discrete orders of a linear finite-impulse-response (FIR) multiple-input multiple-output (MIMO) system, the number of subsystems that attain each order as well as the total number of inputs. Furthermore, the proposed algorithm applies to single-input multiple-output (SIMO) system order estimation. Simulations in the context of blind channel order estimation show good performance in comparison to existing schemes developed for SIMO systems.     

一种FDD大规模MIMO系统下行信道估计算法

信道估计是大规模多输入多输出(MIMO)系统的关键技术之一。本文针对频分双工(FDD)大规模MIMO正交频分复用(OFDM)系统,研究了下行信道估计问题。通过利用大规模MIMO-OFDM信道在角度-频域中的块稀疏特性,提出了基于块匹配追踪的低复杂度估计算法。另外,针对采用时域正交导频存在估计周期过长,有可能超过系统相干时间的问题,提出了天线分组发送方案,通过牺牲观测数据长度来换取信道估计周期的减少。仿真结果表明,所提算法具有良好的抗噪性能,可以准确找出稀疏向量的非零值位置,并可自适应确定稀疏度。     

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。     

基于盲波束形成的MIMO雷达稳健参数估计

多输入多输出（MIMO）雷达采用多发多收模式,不仅存在接收端阵列误差,同时又引入了发射端阵列误差,因此克服系统误差,保证信号处理的稳健性要比传统雷达更为困难。在接收端和发射端未知阵列流形下,本文利用目标的多普勒信息,用盲自适应波束形成器实现了MIMO雷达DOA-Doppler的稳健估计。仿真结果验证了该方法的有效性。     

Randomized Kaczmarz algorithm for massive MIMO systems with channel estimation and spatial correlation

To exploit the benefits of massive multiple‐input multiple‐output (M‐MIMO) technology in scenarios where base stations (BSs) need to be cheap and equipped with simple hardware, the computational complexity of classical signal processing schemes for spatial multiplexing of users shall be reduced. This calls for suboptimal designs that perform well the combining/precoding steps and simultaneously achieve low computational complexities. An approach on the basis of the iterative Kaczmarz algorithm (KA) has been recently investigated, assuring well execution without the knowledge of second order moments of the wireless channels in the BS, and with easiness since no tuning parameters, besides the number of iterations, are required. In fact, the randomized version of KA (rKA) has been used in this context because of global convergence properties. Herein, modifications are proposed on this first rKA‐based attempt, aiming to improve its performance‐complexity trade‐off solution for M‐MIMO systems. We observe that long‐term channel effects degrade the rate of convergence of the rKA‐based schemes. This issue is then tackled herein by means of a hybrid rKA initialization proposal, which lands within the region of convexity of the algorithm and assures fairness to the communication system. The effectiveness of our proposal is illustrated through numerical results, which bring more realistic system conditions in terms of channel estimation and spatial correlation than those used so far. We also characterize the computational complexity of the proposed rKA scheme, deriving upper bounds for the number of iterations. A case study focused on a dense urban application scenario is used to gather new insights on the feasibility of the proposed scheme to cope with the inserted BS constraints.     

Closed-form blind MIMO channel estimation for orthogonal space-time block codes

In this paper, a new computationally simple approach to blind decoding of orthogonal space-time block codes (OSTBCs) is proposed. Using specific properties of OSTBCs, the authors' approach estimates the channel matrix in a closed form and in a fully blind fashion. This channel estimate is then used in the maximum-likelihood (ML) receiver to decode the information symbols. The proposed estimation technique provides consistent channel estimates, and, as a result, the performance of the authors' blind ML receiver approaches that of the coherent ML receiver, which exploits the exact channel state information (CSI). Simulation results demonstrate the performance improvements achieved by the proposed blind decoding algorithm relative to the popular differential space-time modulation scheme.     

On blind multiuser forward link channel estimation by the subspacemethod: identifiability results

Blind channel estimation for periodic sequence DS-CDMA systems can be cast into the framework of “structured” blind estimation of multi-input/multi-output (MIMO) FIR systems, where the structure is imposed by the user's signatures. A possible approach to tackle this problem consists in looking for a structured solution to one of the blind MIMO-FIR systems, proposed previously. This is the approach undertaken by several authors. However, most of them did not address identifiability issues. In this paper, we first recall and reformulate some general MIMO FIR identification results of Meraim, Loubaton and Moulines (see IEEE Trans. Inform. Theory, vol.43, p.499-511, 1997), and point out some difficulties posed by the subspace approach. Next, we use the above material in order to analyze the behavior of the subspace forward link channel estimate of CDMA systems. We derive new results showing that the subspace method is not robust to an over-determination of the channel order greater than the spreading factor. If however the over-determination error is less than the spreading factor, we show that the subspace estimate is consistent if the codes of the users are properly designed     

Sparsity adaptive channel estimation algorithm based on compressive sensing for massive MIMO systems

A sparsity-adaptive channel estimation algorithm based on compressive sensing was proposed for massive MIMO systems when the number of channel multi-paths was unknown.By exploiting the joint sparsity characteristics of the sub-channels，the proposed block sparsity adaptive matching pursuit (BSAMP) algorithm first selected atoms by setting a threshold and finding the position of the maximum backward difference，which reduces the energy dispersion caused by the non-orthogonality of the observation matrix and improves the performance of the algorithm.Then a regularization method was utilized to improve the stability of the algorithm.Simulation results demonstrate that the proposed algorithm recovers the channel state information accurately and shows a high computational efficiency.     

大规模MIMO系统中低复杂度的稀疏信道估计

针对大规模多输入多输出（MIMO）系统信道估计算法复杂度高的缺陷,结合无线通信信道固有的稀疏性提出了一种低复杂度的稀疏信道估计算法。该算法是在传统的离散傅里叶变换（DFT）信道估计的基础上利用分离算法将信道抽头与噪声空间分离开来,使得信道估计时只需要计算信道抽头的部分,因此算法的计算复杂度被大大降低。仿真结果表明,该算法在保持低复杂度的同时,可获得接近最小均方误差（MMSE）性能。     

一种改进的MIMO OFDM系统信道估计算法

本文对MIMO OFDM系统中基于训练序列的信道估计问题进行了研究，针对信道冲击响应的最大抽头数大于每个OFDM符号中导频数的情况，提出一种有效的结合前后若干训练序列进行信道估计的算法和结合方式。仿真结果表明，在基于无线局域网（WLAN）中打包传送的MIMO OFDM系统里，本文的方法比采用块状训练序列的估计算法有着更小的归一化均方误差。     

Hybrid channel coding scheme for blind space-time coded MIMO systems

This letter proposes a hybrid use of channel codes in wireless systems employing multiple transmit/multiple receive antennas. We concatenate space-time codes (STCs) serially with low-density parity check (LDPC) codes and turbo codes. We show that by using these powerful coding schemes effectively, substantial performance improvements can be achieved. This is motivated by the need for a scheme that gives promising performance even when no training is available. The proposed scheme results in a desirable trade-off between performance and complexity.     

一种OFDM系统中的盲信道估计算法

该文利用OFDM系统传输的信息符号为有限字符集和各子载波的相互独立特性,提出了用伪导频符号(PPS)进行信道的盲估计算法。与用于做信道估计的导频符号不同,PPS传输的是有用的数据,因此提高了系统的带宽利用率,PPS的平均功率增加3dB或6dB可有效抑制信道的加性高斯噪声。对信道盲估计的均方误差(MSE)和由此算法获得的信道的状态信息对无编码的OFDM系统进行解调的误比特率进行了仿真,结果表明提出的算法是有效的并具有很好的灵活性。     

一种联合TOA与DPS估计的MIMO OFDM系统信道估计算法

本文提出了一种基于联合TOA(到达时间)与DPS(时延功率谱)估计的MIMO OFDM系统信道估计算法,该算法借助导频设计,通过联合TOA与 DPS估计对各路径时延位置进行精确定位,并在此基础上,对初始时域信道估计进行非线性滤波,从而改善了大时延扩展信道条件下由于导频子载波受限所导致的估计性能恶化现象.此外,文中还进一步分析、推导了该算法所适用的信道多径时延条件.最后,仿真结果也表明该算法可有效对抗大时延扩展信道,而且其MSE、BER性能要优于传统的时域最小二乘信道估计算法.     

Linear precoding assisted blind channel estimation for OFDM systems

We propose a novel precoding approach for single transmit/receiver antenna orthogonal frequency-division multiplexing (OFDM) systems that enables blind channel estimation. A nonredundant nonunitary linear precoder is applied on each pair of blocks before they enter the OFDM system. The structure induced to the transmitted blocks allows for blind channel estimation at the receiver based on simple cross-correlation operations. At the same time, the multipath diversity of the system is increased. An optimal precoding scheme is pursued that, for quadrature phase-shift keying signals results in minimum channel error and asymptotically minimum bit error rate. Analytic performance evaluation of the proposed approach, and Cramer-Rao bound for the proposed channel estimate, are presented.     

Totally blind APP channel estimation for mobile OFDM systems

A new two-dimensional blind channel estimation scheme for coherent detection of orthogonal frequency-division multiplexing (OFDM) signals in a mobile environment is presented. The channel estimation is based on the a posteriori probability (APP) calculation algorithm. The time-variant channel transfer function is completely recovered without phase ambiguity with no need for any pilot or reference symbols, thus maximizing the spectral efficiency of the underlying OFDM system. The phase ambiguity problem is solved by using a 4-QAM (quadrature amplitude modulation) scheme with asymmetrical arrangement. The results clearly indicate that totally blind channel estimation is possible for virtually any realistic time-variant mobile channel.     

Research on an iterative algorithm of LS channel estimation in MIMO OFDM systems

An iterative Least Square (LS) channel estimation algorithm for MIMO OFDM systems was proposed in this paper. Compared to common LS channel estimation, this algorithm can greatly improve estimation accuracy, and the low-pass filtering in time domain reduces AWGN and ICI significantly. MIMO OFDM system with this algorithm also works well in mobile situations. Simulation results have shown good MSE performance for this algorithm.