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.     

MUSIC-Based Pilot Decontamination and Channel Estimation in Multiuser Massive MIMO System

This paper addresses the problem of channel estimation in a multiuser multi-cell wireless communications system in which the base station (BS) is equipped with a very large number of antennas (also referred to as “massive multiple-input multiple-output (MIMO)”). We consider a time-division duplexing (TDD) scheme, in which reciprocity between the uplink and downlink channels can be assumed. Channel estimation is essential for downlink beamforming in massive MIMO, nevertheless, the pilot contamination effect hinders accurate channel estimation, which leads to overall performance degradation. Benefitted from the asymptotic orthogonality between signal and interference subspaces for non-overlapping angle-of arrivals (AOAs) in the large-scale antenna system, we propose a multiple signals classification (MUSIC) based channel estimation algorithm during the uplink transmission. Analytical and numerical results verify complete pilot decontamination and the effectiveness of the proposed channel estimation algorithm in the multiuser multi-cell massive MIMO system.     

多小区大规模阵列天线系统盲解码算法

针对多小区大规模阵列天线系统中干扰小区的导频复用造成的导频污染和解码性能下降问题,提出了基于ICA（独立分量分析）盲解码算法。所提盲解码算法,利用ICA法对接收多小区用户信号进行分离解码,不需要发射导频序列,避免了导频污染,提高了解码性能。所提盲解码算法在解码过程中同时估计各个用户波达方向,利用波达方向信息克服ICA方法分离顺序的不确定性,识别期望用户的信号。理论分析和仿真结果表明,所提盲解码方法比广泛应用的MMSE解码算法和最近提出的基于特征值的盲解码方法具有更好的性能。     

A lower bound on achievable rate of MRT precoding in multicell multiuser massive MIMO networks with Rician flat fading

A multicell multiuser massive multiple‐input‐multiple‐output (MIMO) network with Rician flat fading is considered. Given channel reciprocity, non‐orthogonal uplink channel training in conjunction with minimum mean square error channel estimation at the base stations are used to acquire channel state information. In the forward link, using maximal ratio transmission precoding, base stations send data to corresponding users. In this paper, first, a closed‐form expression for signal to interference and noise ratio and a lower bound on achievable rate are obtained for arbitrary number of base station antennas. Then, using random matrix theory, a simplified approximate expression for large number of base station antennas (i.e., massive MIMO scenario) are calculated. This simplified expression shows that in a multicell multiuser massive MIMO network with Rician flat fading, like Rayleigh fading, as the number of base station antennas goes to infinity, the effects of uncorrelated noise and intercell and intracell interferences tend to zero. The only factor limiting the performance of system is the correlated intercell interference, that is, pilot contamination, due to non‐orthogonality of channel training sequences in adjacent cells. Numerical results show that our obtained closed‐form expression is a good lower bound on sum‐rate for various system parameters. Copyright © 2016 John Wiley & Sons, Ltd.     

Pilot decontamination in massive MIMO system combining time-shifted and cell sectorization pilot assignment

Pilot contamination is appeared in massive MIMO (multiple input multiple output) system when using the same pilot sequences at different cells to get the channel state information.It becomes a bottleneck problem of massive MIMO when the number of antenna goes infinite.In order to dealt with pilot contamination,a new TS-CSPA joint scheme was proposed.This scheme can mitigate pilot contamination by reduce the reuse of pilot sequence through the time domain and space domain.And the closed-form expression for the achieved rates and signal to interference plus noise ratio(SINR) to verify the advantages of the proposed scheme were given.Numerical results show that significant performance gains to mitigate pilot contamination problem compared to other methods.     

Performance optimization of cell-free massive MIMO system with power control approach

The cell-free massive MIMO (multiple-input multiple-output) system involves a large number of access points serving a smaller number of mobile users (MUs) over identical time/ frequency resource. By providing large number of service antennas closer to the MUs, the cell-free massive MIMO can offer great spectral efficiency, better macro-diversity and minimal path loss. Despite several advantages, the cell-free massive MIMO suffers from energy overloading caused by uncontrolled backhaul power consumption for large number of distributed access points (APs) and pilot contamination during channel estimation. In this paper, we have taken into consideration a cell-free massive MIMO system with APs equipped with multiple antennas performing time-division-duplex (TDD) operation. Here, all the APs coordinate through a constrained backhaul network for joint transmission of signals to all the users simultaneously by multiplying the received signal with the normalized conjugate of the estimated channel state information (CSI) and send back a rounded off version of the weighted pattern to the central processing unit (CPU). Finally, an effective user defined algorithm is presented involving selection and grouping of various APs based on their individual contributions for a particular MU to improve the overall performance of the system.     

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。     

利用数据和导频的多小区Massive MIMO系统信道估计

本文提出一种通过同时利用上行数据和导频进行信道估计来对抗时分双工大规模多输入多输出（Massive multi-input multi-output,Massive MIMO）系统中导频污染的方法。考虑到Massive MIMO系统下空间相关信道在角度域具有近似稀疏性,期望用户信道和干扰信道的多径分量因而可分辨。同时上行数据子帧中的数据符号数远大于导频序列的长度。基于以上两点观察,首先利用上行导频对信道进行粗估计,然后将解码得到的上行数据符号视为导频序列,用于得到角度域信道估计中能量较大分量所处的位置。通过抽取信道粗估计中相应位置上的信道系数,可以得到信道的精估计。仿真表明,无论相邻小区采用同一组正交导频序列、还是不同组但具有相关性的导频序列,所提出的信道估计方法都能有效地消除导频污染。      

基于联合用户分组及天线选择的大规模MIMO波束成形

大规模MIMO系统中,当小区用户数与基站天线数较大时,各用户的信道条件不尽相同,提出一种适用于大规模MIMO下行链路的基于联合用户分组及天线选择的迫零波束成形算法。将用户分成两组,选择信道条件较优的一组用户来接收信号,并为每一个发送数据流选择最优的基站天线组合进行通信,以较小的性能损失,换取大规模MIMO 射频电路的成本与功耗的大幅度降低。仿真结果证明,该算法能够较好地实现系统性能与硬件复杂度的折中。     

时变信道下多小区多用户分布式大规模MIMO系统上行可达速率分析

针对多小区多用户分布式大规模多输入多输出(Multiple-Input Multiple-Output，MIMO)上行系统，考虑移动环境下信道时变特性，并结合多小区导频污染和信道估计误差条件，分析这类因素对系统可达速率的性能影响。采用一阶高斯马尔科夫过程对时变信道进行建模，以时间相关性系数为时变信道参量描述信道系数随时间变化的快慢程度。当基站采用最大比合并(Maximum Ratio Combining，MRC)接收机时，利用Jensen不等式、随机矩阵理论和Gamma随机变量的各阶矩，推导得出了包含导频污染、信道估计误差和信道时变参量的可达速率解析表达式。基于此，分析得出在多小区分布式大规模MIMO系统中，时变信道参量只会影响系统的可达速率绝对值，而不会影响发射功率缩放律。更重要的是，当不考虑发射功率缩放时，随总天线数增加，可达速率将不受时变信道的影响，而只由导频污染所决定，这表明该系统对时变信道具有良好的鲁棒性。最后，利用蒙特卡洛数值仿真验证了所得出的结论的正确性和有效性。      

联合波束域分解和SVD的多用户大规模MIMO系统信道估计

针对TDD(Time Division Duplex)模式下的多用户大规模MIMO(Multiple-Input Multiple-Output)系统,本文研究了将波束域分解和SVD(Singular Value Decomposition)同时用于该系统的信道估计。当基站天线数目较多时,信道估计误差、导频开销、信道估计算法的复杂度等问题将成为影响大规模MIMO系统性能的关键因素。运用波束域分解理论,将多用户的大规模MIMO系统分解成多个单用户的大规模MIMO系统,同时从波束域对信道建模,该方法降低导频开销的同时也减小了信道估计误差。另外运用SVD对信道自相关矩阵优化,可以进一步降低信道估计算法的复杂度。基于以上两点,本文提出了一种联合波束域分解和SVD的大规模MIMO信道估计方案,并推导出了估计误差协方差矩阵的闭式表达式。仿真结果表明,与同类方案相比,本文提出的方案具有更好的信道估计性能。      

大规模MIMO系统中融合用户调度的叠加导频信道估计方法

传统的信道估计策略通常基于时分复用方式实现导频配置,导致大规模多输入多输出系统的带宽利用率有限,同时受信道相干时间的限制,大规模MIMO系统可利用的导频资源非常有限,因此,相邻小区不得不通过导频复用来实现信道估计,从而引起导频污染问题。针对上述问题,融合用户调度,提出了一种基于叠加周期性导频的信道估计方法。该方法通过优化功率分配因子,以信号泄露噪比（SLNR）作为度量指标,对不同小区的用户进行协作调度并分配相同的导频,不仅减轻了导频污染,而且提高了信道估计的精度。数值仿真验证了方法的有效性。     

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.     

大规模 MIMO 蜂窝网络系统中的导频污染减轻方法简

提出了2个减轻大规模天线蜂窝网络导频污染的方案：利用正交导频把蜂窝系统中的小区划分为两类一维大的天线阵列网络,每一类之内采用相同的导频,两类之间采用正交的导频,再利用导频功率控制方法减轻了导频污染。利用基站间的协调,以所有基站信道估计均方误差的求和最小为目标函数,寻求近似最优的导频序列长度和同导频用户发射导频时隙的分配方案,从而提高了信道估计的性能,提升了整个系统的下行链路可达和速率。     

基于二维嵌套阵的3D MIMO系统信道估计算法

信道估计通过对基站接收信号和用户端发送的已知导频序列进行处理获得。二维嵌套阵列可以节约系统的成本并且得到大规模MIMO（multiple-input multiple-output）天线阵列的性能，然而由于二维嵌套阵列的结构不规整，直接对基站接收信号进行处理具有一定的难度。本文提出一种基于2D-DFT（two-dimensional Discrete Fourier Transform）的信道重构算法，首先对接收信号做自相关处理转化为连续差分阵列的接收信号，然后通过2D-DFT估计出用户的每一条路径的初始DOA（the direction of arrival），然后利用角度旋转技术增强DOA估计实现超分辨率估计，再根据精确的DOA估计通过传统的LS（least squares）估计方法估计出信道增益；最后重构出用户的信道。数值仿真验证了算法的有效性。      

无小区大规模MIMO系统中基于叠加导频的上行频谱效率理论上限分析

无小区大规模多输入多输出(Cell-Free Massive MIMO)突破传统蜂窝小区的概念,被认为是未来移动通信中十分富有潜力的技术.该技术通过部署大量的分布式接入点(Access Point,AP)以获得充分的宏分集增益,以提高用户服务质量.受信道相干时间的限制,系统中可供用户分配的正交导频资源非常有限,部分用户...     

A low-complexity sequential Monte Carlo algorithm for blind detection in MIMO systems

In statistical signal processing, the sequential Monte Carlo (SMC) method is powerful and can approach the theoretical optima. However, its computational complexity is usually very high, especially in multiple-input multiple-output (MIMO) systems. This paper presents a new low-complexity SMC (LC-SMC) algorithm for blind detection in MIMO systems, the main idea of which is to shrink the sampling space via channel estimation which is initialized using the first differentially modulated symbol and then updated using the Monte Carlo samples. Since the a posteriori probability of the transmitted symbols can be calculated separately by each transmit antenna, the proposed LC-SMC algorithm is not only computationally efficient, as compared to the original SMC whose complexity grows exponentially with the number of transmit antennas, but also makes blind turbo receiver more feasible for multilevel/phase modulations. Simulation results are presented to demonstrate the effectiveness of the LC-SMC algorithm.     

Blind downlink channel estimation for TDD‐based multiuser massive MIMO in the presence of nonlinear HPA

In time division duplex (TDD)‐based multiuser massive multiple input multiple output (MIMO) systems, the uplink channel is estimated and the results are used in downlink for signal detection. Owing to noisy uplink channel estimation, the downlink channel should also be estimated for accurate signal detection. Therefore, recently, a blind method was developed, which assumes the use of a linear high‐power amplifier (HPA) in the base station (BS). In this study, we extend this method to a scenario with a nonlinear HPA in the BS, where the Bussgang decomposition is used for HPA modeling. In the proposed method, the average power of the received signal for each user is a function of channel gain, large‐scale fading, and nonlinear distortion variance. Therefore, the channel gain is estimated, which is required for signal detection. The performance of the proposed method is analyzed theoretically. The simulation results show superior performance of the proposed method compared to that of the other methods in the literature.     

MC‐CDMA MIMO systems with quasi‐orthogonal space–time block codes: Channel estimation and multiuser detection

This paper investigates blind channel estimation and multiuser detection for quasi‐synchronous multi‐carrier code‐division multiple‐access (MC‐CDMA) multiple‐input multiple‐output (MIMO) systems with quasi‐orthogonal space–time block codes (QO‐STBC). Subspace‐based blind channel estimation is proposed by considering a QO‐STBC scheme that involves four transmit antennas and multiple receive antennas. Based on the first‐order perturbation theory, the mean square error of the channel estimation is derived. With the estimated channel coefficients, we employ minimum output energy and eigenspace receivers for symbol detection. Using the QO‐STBC coding property, the weight analyses are performed to reduce the computational complexity of the system. In addition, the forward–backward averaging technique is presented to enhance the performance of multiuser detection. Numerical simulations are given to demonstrate the superiority of the proposed channel estimation methods and symbol detection techniques. Copyright © 2011 John Wiley & Sons, Ltd.     

Mitigating Pilot Contamination for Channel Estimation in Multi-cell Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is a crucial technology platform for the fifth-generation of cellular systems (5G). However, massive MIMO systems are affected by pilot contamination, which influences the data rate of the system. This contamination is caused by the non-orthogonality of the pilot sequences transmitted by users in a cell similar to the neighboring cells. The current study proposes a channel-estimation scheme that employs comprehensive knowledge of large-scale gained by applying an orthogonal pilot reuse sequence to eliminate pilot contamination in edge users with reduced channel quality based on the approximation of large-scale fading, and the performance of this scheme is evaluated using the maximum ratio transmission and zero-forcing precoding techniques. Largely interfering users in neighboring cells are established based on an estimation of large-scale fading, and these users are included in the joint channel processing. The channel quality of users is enhanced by allocating orthogonal pilot reuse sequences to the center user and the edge users based on their levels of pilot contamination estimated from the large-scale fading to mitigate this problem when the number of antenna elements M is infinite. The findings of the simulation indicate that improved channel approximation and reduced performance loss could lead to a high data rate.