Performance analysis of maximum ratio transmission with imperfect channel estimation

Maximal ratio transmission (MRT) is designed assuming the availability of perfect channel state information (CSI) at both the transmitter and the receiver. However, perfect CSI is not available in practice. This paper investigates the impact of Gaussian estimation errors on the MRT performance in independently and identically distributed (i.i.d.) Rayleigh fading channels. We derive the cumulative distribution function (cdf), the probability density function (pdf) and the moment generating function (mgf) of the MRT output signal-to-noise ratio (SNR) with imperfect CSI, enabling the evaluation of some useful performance metrics such as the average error rate and the outage performance. Numerical and simulation results are provided to show the impact of imperfect CSI on the MRT performance.     

Performance analysis of maximum ratio transmission based multi-cellular MIMO systems

In this paper, we analyze the performance of the uplink of multi-cellular MIMO systems in flat Rayleigh fading. There is co-channel interference from users within the same cell as well as from other cell users. I The channel model includes lognormal shadowing and path loss along with power control, resulting in a statistical model for user powers. Consistent with practical scenarios, the co-channel interference is categorized into two groups: intracell interference from users within the same cell as the desired user and intercell interference from outer cell users. We derive a compact, easily computable closed form outage probability expression in the form of finite sums. This expression allows for simpler and faster analysis of various MIMO configurations. It has been shown that using antennas on the receiver side results in better performance, since transmit diversity does not combat interference from same cell users.     

Performance analysis of semiblind channel estimation in long-code DS-CDMA systems

The performance of second-order statistics (SOS)-based semiblind channel estimation in long-code direct-sequence code-division multiple-access systems is analyzed. The covariance matrix of second-order statistics estimates is obtained in the large system limit and is used to analyze the large-sample performance of two SOS-based semiblind channel estimation algorithms. A notion of blind estimation efficiency is also defined and is examined via simulation results.     

Training-based channel estimation for multiple-antenna broadband transmissions

This paper addresses the problem of training sequence design for multiple-antenna transmissions over quasi-static frequency-selective channels. To achieve the channel estimation minimum mean square error, the training sequences transmitted from the multiple antennas must have impulse-like auto correlation and zero cross correlation. We reduce the problem of designing multiple training sequences to the much easier and well-understood problem of designing a single training sequence with impulse-like auto correlation. To this end, we propose to encode the training symbols with a space-time code, that may be the same or different from the space-time code that encodes the information symbols. Optimal sequences do not exist for all training sequence lengths and constellation alphabets. We also propose a method to easily identify training sequences that belong to a standard 2/sup m/-PSK constellation for an arbitrary training sequence length and an arbitrary number of unknown channel taps. Performance bounds derived indicate that these sequences achieve near-optimum performance.     

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。      

Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals

In this paper, we study the performance of multiple-input multiple-output channel estimation methods using training sequences. We consider the popular linear least squares (LS) and minimum mean-square-error (MMSE) approaches and propose new scaled LS (SLS) and relaxed MMSE techniques which require less knowledge of the channel second-order statistics and/or have better performance than the conventional LS and MMSE channel estimators. The optimal choice of training signals is investigated for the aforementioned techniques. In the case of multiple LS channel estimates, the best linear unbiased estimation (BLUE) scheme for their linear combining is developed and studied.     

Optimizing antenna configuration for MIMO systems with imperfect channel estimation

We study the optimal antenna configuration (i.e. number of transmit and receive antennas) for multiple-input multiple-output systems in pilot-symbol-assisted modulation schemes with imperfect channel estimation. We assume block flat-fading channels and focus on a practical range of high signal-to-noise ratio. An ergodic capacity lower bound is used as the objective function to be maximized. We analytically study the capacity gain from adding extra antennas to the transmitter or to the receiver in two different scenarios. Our numerical results show that the optimal antenna configuration under imperfect channel estimation can be significantly different from that under perfect channel estimation assumption. In addition, we investigate the capacity gain from optimizing antenna configuration and find that the gain can be larger than that achieved by optimizing transmit power over pilot and data symbols, particularly for large block lengths.     

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。     

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。     

Hybrid channel estimation for MIMO relay systems with Doppler offset influences

The design of the channel estimation method in a multiple‐input multiple‐output (MIMO) relay system plays a highly crucial role in deciding the overall system performance. For the realistic scenarios specifically, with fast time‐varying channel conditions due to highly mobile communicating nodes, the degree of accuracy to which the channel estimates are obtained for MIMO relay systems influences the communication system reliability significantly. However, most of the channel estimation approaches proposed in literature for MIMO relay systems assume that the Doppler offset contributed by highly mobile nodes is already known to the receiver, ignoring the resulting nonlinear system dynamics. Hence, a novel hybrid algorithm is proposed to address the issue of time‐varying channel estimation under fast‐fading channel condition with Doppler offset influences contributed by high‐mobility communicating nodes for a 1‐way 2‐hop MIMO amplify‐and‐forward relaying system. The problem is first formulated as a nonlinear state‐space model, and then an algorithm is developed to estimate the individual source‐to‐relay and relay‐to‐destination channels in the presence of the associated dynamic Doppler offset. In the proposed method, a set of superimposed orthogonal pilots is used for aiding in the updation of the channel gains, since Kalman filter–based updation may lead to accumulation of estimation and prediction error. A detailed computational complexity analysis of the proposed hybrid algorithm is presented, which shows that the algorithm has moderate computational complexity with a good performance in fast time‐varying channel conditions with high node mobility in a dual‐hop MIMO relay system.     

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.     

Efficient MIMO channel estimation for linear precoded OFDMA uplink systems

A novel and simple uplink MIMO channel estimation technique based on spread pilots well suited to LP OFDMA schemes is proposed. The combination with Alamouti code is studied and two different approaches are compared. The performance evaluated over a realistic MIMO channel shows the efficiency of this novel scheme, which appears to be a promising channel estimation for the uplink of future wideband wireless networks.     

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。     

Deep learning-based channel estimation for wireless ultraviolet MIMO communication systems

To solve the problems of pulse broadening and channel fading caused by atmospheric scattering and turbulence, multiple-input multiple-output(MIMO) technology is a valid way. A wireless ultraviolet(UV) MIMO channel estimation approach based on deep learning is provided in this paper. The deep learning is used to convert the channel estimation into the image processing. By combining convolutional neural network(CNN) and attention mechanism(AM), the learning model is designed to extract the depth f...     

Peak-to-average ratio reduction scheme for multi-carrier systems with block-based channel estimation

A simple scheme is proposed to reduce the peak-to-average ratio (PAPR) for multi-carrier systems with block-based channel estimation, where each user simultaneously transmits multiple traffic blocks across the frequency, and the channel estimation is done within each block. Unlike most existing schemes, the proposed scheme does not require additional side information or estimation at the receiver. Results indicate significant improvements in both the PAPR and cubic metric reduction.     

Optimal pilot sequence design for channel estimation in MIMO OFDM systems

In orthogonal frequency division multiplexing (OFDM) systems, since virtual subcarriers are not used for transmission, approach of conventional uniformly placed pilot tones is not applicable in some situations. In this letter, based on nonuniform pilot tone placement, we derive optimal pilot sequences, which can achieve the minimum mean square error of the least squares estimate for multiple-input multiple-output (MIMO) OFDM systems. Simulation results demonstrate the effectiveness of the proposed approach.     

基于平行因子分解的大规模MIMO盲信道估计

针对单小区大规模多输入多输出（Multiple-Input Multiple-Output,MIMO）系统上行链路,提出了一种基于平行因子（Parallel Factor,PARAFAC）模型的信道估计方法。在基站端,将接收信号构造成PARAFAC模型,利用大规模MIMO系统中信道的渐近正交的性质,提出了一种基于约束二线性迭代最小二乘算法(Constrained Blinear Alternating Least Squares,CBALS),从而实现了盲信道估计。理论分析及仿真结果表明,所提方法与传统最小二乘方法相比,不仅提高了频带利用率而且具有更高的估计精度;与已有的二线性交替最小二乘方法(BALS)相比,所提算法有更快的收敛速度。     

Channel estimation and channel tracking for correlated block-fading channels in massive MIMO systems

This paper presents a channel estimation and tracking method for correlated block-fading channels in massive MIMO wireless cellular systems. In order to conserve resources, the proposed algorithm requires the uplink pilot signal only once, at the start of communication. By utilizing the temporal correlation between consecutive Resource Blocks (RBs) and the error correction capability of turbo codes, the channel matrix in subsequent RBs is estimated at the Base Station (BS) itself using the uplink data of current the RB and the estimated channel matrix of previous the RB. Compared to existing blind estimation methods, the proposed method places fewer limitations on the system settings such as the number of BS antennas, the number of users, and the number of coherent channel usage compared to existing blind estimation methods. Simulation results show that the proposed algorithm provides better performance for a moderate RB size, a high-order of QAM scheme, and a smaller ratio of the number of BS antennas and mobile terminals (N/K). For a reasonably small N/K (order of 10), the proposed scheme achieves a lower symbol error probability than the conventional pilot-based estimation approach.     

Pilot embedding for joint channel estimation and data detection in MIMO communication systems

A novel pilot-aided joint channel estimation and data detection method for MIMO communication systems is proposed. Unlike, conventional methods where pilots are time-multiplexed with data symbols, a pilot-embedding method where low-level pilots are transmitted concurrently with the data is used to obtain an initial estimate of the channel such that a turbo decoding process can be started. The soft information obtained from the turbo decoder is subsequently used to improve channel estimates.