针对自适应编码调制系统的低复杂度MMSE信道估计（英文）

Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.     

PERFORMANCE OF THE ZERO FORCING PRECODING MIMO BROADCAST SYSTEMS WITH CHANNEL ESTIMATION ERRORS

In this paper, the effect of channel estimation errors upon the Zero Forcing (ZF) precoding Multiple Input Multiple Output Broadcast (MIMO BC) systems was studied. Based on the two kinds of Gaussian estimation error models, the performance analysis is conducted under different power allocation strategies. Analysis and simulation show that if the covariance of channel estimation errors is independent of the received Signal to Noise Ratio (SNR), imperfect channel knowledge deteriorates the sum capacity and the Bit Error Rate (BER) performance severely. However, under the situation of orthogonal training and the Minimum Mean Square Error (MMSE) channel estimation, the sum ca- pacity and BER performance are consistent with those of the perfect Channel State Information (CSI) with only a performance degradation.     

Iterative Estimation and Equalization for SCCP Over Doubly Selective Channels

In time varying channels, symbol recovery for single carrier cyclic prefix (SCCP) systems becomes complicated, because the orthogonality of channel frequency response (CFR) matrix is destroyed. In response, we propose a block turbo equalization algorithm in the time domain for SCCP to cope with channel time variations. In particular, the band structure of the channel time response (CTR) matrix is exploited to reduce the computational complexity of matrix inversion. In order to use this equalization scheme, accurate channel state information (CSI) must be available. Accordingly, we present a doubly selective channel estimation method for SCCP block transmissions with the aid of a Karhunen-Loeve basis expansion model (KL-BEM). In this method, the channel estimates are firstly obtained by using the cyclic prefix (CP) of each block, and then further refined by employing an expectation maximization (EM) based iterative algorithm. Combining the iterative estimator with the proposed equalizer naturally results in a doubly iterative receiver, the performance of which is shown to come close to the performance with perfect CSI.     

MLSE and MAP Equalization for Transmission Over Doubly Selective Channels

In this paper, equalization for transmission over doubly selective channels is discussed. The symbol-by-symbol maximum a posteriori probability (MAP) equalizer and the maximum-likelihood sequence estimation (MLSE) are discussed. The doubly selective channel is modeled using the basis expansion model (BEM). Using the BEM allows for an easy and low-complexity mechanism for constructing the channel trellis to implement the MLSE and the MAP equalizer. The MLSE and the MAP equalizer are implemented for single-carrier transmission and for multicarrier transmission implemented using orthogonal frequency-division multiplexing (OFDM). In this scenario, a complexity-diversity tradeoff can be observed. In addition, we propose a joint estimation and equalization technique for doubly selective channels. In this joint estimation and equalization technique, the channel state information (CSI) is obtained in an iterative manner. Simulation results show that the performance of the joint channel estimation and equalization approaches the performance when perfect CSI is available at the receiver.     

基于梳状导频的OFDM分组自适应比特装载与功率控制

无线通信环境中信道信息(ChannelStateInformation,CSI)随时间变化明显,需要不断地更新自适应比特装载和功率控制的策略。现有的OFDM自适应比特装载方法需要大量的信令来传递当前比特装载的策略,不适用于无线通信的应用环境。为此,本文针对OFDM系统的特征提出了一种利用插入梳状导频的信道估计得到的带有误差的信道信息,来完成自适应比特装载的算法。首先把OFDM子载波进行分组,然后利用基于梳状导频的信道估计对信道时变进行跟踪,使用即时获得的CS完成自适应比特装载算法。仿真实验证明,在保证算法简单、实用及保证要求的误码率(BER)性能的情况下,信道信令的开销低于传统算法的10%。     

Robust Linear Receivers for Multiaccess Space–Time Block-Coded MIMO Systems: A Probabilistically Constrained Approach

Traditional multiuser receiver algorithms developed for multiple-input–multiple-output (MIMO) wireless systems are based on the assumption that the channel state information (CSI) is precisely known at the receiver. However, in practical situations, the exact CSI may be unavailable because of channel estimation errors and/or outdated training. In this paper, we address the problem of robustness of multiuser MIMO receivers against imperfect CSI and propose a new linear technique that guarantees the robustness against CSI errors with a certain selected probability. The proposed receivers are formulated as probabilistically constrained stochastic optimization problems. Provided that the CSI mismatch is Gaussian, each of these problems is shown to be convex and to have a unique solution. The fact that the CSI mismatch is Gaussian also enables to convert the original stochastic problems to a more tractable deterministic form and to solve them using the second-order cone programming approach. Numerical simulations illustrate an improved robustness of the proposed receivers against CSI errors and validate their better flexibility as compared with the robust multiuser MIMO receivers based on the worst case designs.     

Practical robust uniform channel decomposition scheme for CSI mismatch in limited feedback MIMO systems

Uniform channel decomposition (UCD) has been proven to be optimal in bit error rate (BER) performance and strictly capacity lossless when perfect channel state information (CSI) is assumed to be available at both the transmitter and receiver side. In practice, CSI can be obtained by channel estimation at receiver and conveyed to transmitter via a limited-rate feedback channel. In such case, the implementation of traditional UCD by treating the imperfect CSI as perfect CSI cause significant performance degradation due to inevitable channel estimation error and vector quantization error. To overcome this problem, a practical robust UCD scheme was proposed in this paper, which includes two steps, firstly, a matching architecture was proposed to eliminate the mismatch between CSI at receiver (CSIR) and CSI at transmitter (CSIT), secondly, an MMSE based robust UCD scheme considering channel estimation error and vector quantization error as an integral part of the design was derived. Simulation results show that the proposed practical robust UCD scheme is capable of improving the BER performance greatly in the context of channel estimation error and vector quantization error compared with the traditional UCD scheme.     

一种基于QR分解的稳健干扰对齐算法

大多数干扰对齐算法都假定发送端可以获得理想的信道状态信息(CSI),由于信道估计误差、反馈延迟等原因,实际通信系统中CSI往往是有误差的。为此,该文提出一种基于QR分解的稳健干扰对齐算法。对含有误差的联合接收信号进行基于QR分解的预处理,消除一半有误差的干扰;然后在有误差的等效信道联合矩阵下,充分考虑信道误差和干扰的影响,通过最小化发送端泄漏到非目标接收端的干扰信号功率来设计预编码矩阵,并基于最小均方误差(MMSE)准则来设计干扰抑制矩阵。最后,在理想CSI和误差CSI的情况下,通过实验仿真,证明了该算法有效地提高了系统性能。     

存在估计误差的有限反馈MIMO性能分析

考虑的是利用有限反馈技术的下行多用户多天线系统。接收端通过信道估计获得信道状态信息,采用随机矢量量化信道信息并反馈码子的序号,发送端利用部分信道信息,采用波束成型的预编码技术实现多用户数据传输。考虑接收端信道估计存在误差,并对由此带来的系统性能影响进行分析,给出吞吐率损失的上界,以及使有限反馈系统保持固定空分复用增益,信道估计误差方差的限制条件和反馈比特数随发送功率的变化关系。     

利用无监督学习的RIS辅助毫米波通信系统鲁棒传输设计

本文研究了利用无监督学习的可重构智能表面（reconfigurable intelligent surface,RIS）辅助毫米波大规模多输入多输出（multiple input multiple output,MIMO）下行传输设计。首先,针对发送端信道状态信息（channel state information,CSI）非理想场景,推导了RIS辅助的毫米波下行传输系统平均频谱效率闭式上界。进一步,考虑实际系统硬件受限的条件,本文采用基于离散傅里叶变换（discrete Fourier transform,DFT）码本的模拟预编码,且RIS各反射单元仅能取有限的离散相移值。在此基础上,以所推导的平均频谱效率上界最大化为目标,提出一种基于无监督学习的发送端混合预编码、接收端数字合并以及RIS反射单元相移联合设计方法。所提方法采用两阶段无监督学习模型,分别生成RIS反射单元相移与发送端混合预编码,而接收端数字合并矩阵则采用最小均方误差（minimum mean squared error,MMSE）准则生成。同时,本文针对该模型提出了一种高效的分段训练方法。该训练方法分别对生成RIS反射...     

Joint channel estimation and resource allocation for MIMO systems-part I: single-user analysis

Multiple antenna systems are known to provide very large data rates, when the perfect channel state information (CSI) is available at the receiver. However, this requires the receiver to perform a noise-free, multi-dimensional channel estimation, without using communication resources. In practice, any channel estimation is noisy and uses system resources. We shall examine the trade-off between improving channel estimation and increasing the achievable data rate. We consider transmitside correlated multi-input multi-output (MIMO) channels with block fading, where each block is divided into training and data transmission phases. The receiver has a noisy CSI that it obtains through a channel estimation process, while the transmitter has partial CSI in the form of covariance feedback. In Part I of this two-part paper, we consider the single-user case, and optimize the achievable rate jointly over parameters associated with the training phase and data transmission phase. In particular, we first choose the training signal to minimize the channel estimation error, and then, develop an iterative algorithm to solve for the optimum system resources such as time, power and spatial dimensions. Specifically, the algorithm finds the optimum training duration, the optimum allocation of power between training and data transmission phases, the optimum allocation of power over the antennas during the data transmission phase.     

Game-Theoretic Joint Power Allocation and Beamforming for Cognitive MIMO Systems with Finite Feedback

In the paper, we consider the imperfect channel state information (CSI) in practical cognitive MIMO systems. We first analyze the feedback of quantified CSI from the primary user (PU) and propose a joint power allocation and beamforming algorithm via game theory. Compared with the game under the condition of perfect CSI, new utility function and cost function are constructed under imperfect CSI. We analyze the error introduced from the uniformly quantified CSI and obtain new constraints. Besides, existence of the Nash equilibrium in case of both perfect CSI and imperfect CSI are proven. We propose a new iterative algorithm to reach the Nash equilibrium (NE). Simulation results show that the proposed algorithm can converge quickly.     

无线OFDM系统频率选择性衰落信道下的SOVA译码算法

本文对正交频分复用(OFDM)系统频率选择性衰落信道中,信道状态信息(channel state information 简称CSI)确知,以及CSI不能或不必精确估计时的SOVA译码算法进行了研究,给出了OFDM系统频率选择性信道BPSK调制时SOVA译码算法的数学描述.在此基础上,我们提出了两种SOVA译码算法:一种是基于盲信道估计的SOVA算法;另一种是不必训练和信道估计的差分SOVA算法,该算法可以在CSI完全未知的情况下进行可靠的SOVA译码.仿真结果说明该算法具有良好的性能.     

Power allocations in minimum-energy SER-constrained cooperative networks

In this paper, we propose minimum power allocation strategies for repetition-based amplify-and-forward (AF) relaying, given a required symbol error rate (SER) at the destination. We consider the scenario where one source and multiple relays cooperate to transmit messages to the destination. We derive the optimal power allocation strategy for two-hop AF cooperative network that minimizes the total relay power subject to the SER requirement at the destination. Two outstanding features of the proposed schemes are that the power coefficients have a simple solution and are independent of knowledge of instantaneous channel state information (CSI). We further extend the SER constraint minimum power allocation to the case of multibranch, multihop network and derive the closed-form solution for the power control coefficients. For the case of power-limited relays, we propose two iterative algorithms to find the power coefficients for the SER constraint minimum-energy cooperative networks. However, this power minimization strategy does not necessarily maximize the lifetime of battery-limited systems. Thus, we propose two other AF cooperative schemes which consider the residual battery energy, as well as the statistical CSI, for the purpose of lifetime maximization. Simulations show that the proposed minimum power allocation strategies could considerably save the total transmitted power compared to the equal transmit power scheme.     

EM/SAGE Based ML Channel Estimation for Uplink DS-CDMA Systems over Time-Varying Fading Channels

The matrix inversion for the maximum likelihood (ML) channel estimation requires high complexity for the direct-sequence code-division multiple-access (DS-CDMA) systems. The prime motivation of the paper is to propose channel estimators that achieve mean square error (MSE) performance of ML channel estimator in an iterative manner without any matrix inversion. Therefore, two computationally efficient solutions to the problem of ML channel estimation are proposed.We compare the both algorithms in terms of the number of used iteration and show that the proposed algorithms converge the same MSE performance of the ML estimator as the increasing number of iterations.     

Dynamic resource allocation with beamforming for MIMO OFDM systems: performance and effects of imperfect CSI

We propose three different dynamic resource allocation algorithms using adaptive beamforming for multiple-input multiple-output (MIMO) OFDM systems, and investigate their performance over multipath fading channels under perfect and imperfect channel state information (CSI). These approaches involve the use of adaptive modulation, adaptive frequency-domain power allocation, and/or adaptive sub-channel allocation. By employing the proposed approaches in MIMO/OFDM systems, significant performance improvement can be achieved compared to the conventional adaptive antenna array based OFDM. The investigation of the effects of imperfect CSI reveals that the adaptive-modulation based approach is too sensitive to channel estimation errors, and that its performance is worse than the adaptive frequency-domain power allocation and/or adaptive sub-channel allocation approaches. The performance analysis also shows that combining adaptive power allocation with sub-channel allocation yields the best performance under imperfect CSI while being robust to channel estimation errors.     

波束空时分组编码的ICA盲检测方案

理论研究已经证明,结合波束形成和空时分组编码的混合系统与传统的单纯使用波束发射或空时编码的方案相比具有很大的性能提高;传统的译码方案是借助接收端的信道估计来实现的,它需要知道准确的信道状态信息(CSI)。但如果信道估计不易实现,则系统性能将受很大影响。独立分量分析(ICA)作为一种经典的盲信号分离技术可以在不进行信道估计的情况下对发射信号实现有效检测。本文针对接收端的信号结构提出了一种基于ICA的正交检测方案;并通过仿真将新方案与传统方案进行了性能比较。仿真结果表明,新方案具有较好的系统适应性和误码率特性。     

基于有限反馈的MIMO系统鲁棒性均匀信道分解

 在MIMO系统中,当假设发送端和接收端已知完美信道状态信息的情况下,均匀信道分解(UCD)被证明在误码率性能上是最优的且是容量无损的.然而在实际系统中,接收端或发送端获得的信道信息通常存在着一定的估计误差.本文提出一种基于有限反馈的鲁棒性均匀信道分解方案,在设计方案中充分考虑了信道估计误差的影响,并利用香农率失真定理和广义Lloyd矢量量化算法(GLA)得到了信道估计误差的近似值,使得本文提出的方案有很好的实用性.仿真结果表明与传统均匀信道分解方案相比,本文提出的鲁棒性均匀信道分解方案有效地降低了系统的误码平层,提高了系统容量.     

Unquantized and uncoded channel state information feedback in multiple-antenna multiuser systems

We propose a channel state information (CSI) feedback scheme based on unquantized and uncoded (UQ-UC) transmission. We consider a system where a mobile terminal obtains the downlink CSI and feeds it back to the base station using an uplink feedback channel. If the downlink channel is an independent Rayleigh fading channel, then the CSI may be viewed as an output of a complex independent identically distributed Gaussian source. Further, if the uplink feedback channel is an additive white Gaussian noise channel, and the downlink CSI is perfectly known at the mobile terminal, it can be shown that UQ-UC CSI transmission (that incurs zero delay) is optimal in that it achieves the same minimum mean-squared error distortion as a scheme that optimally (in the Shannon sense) quantizes and encodes the CSI, while theoretically incurring infinite delay. Since the UQ-UC transmission is suboptimal on correlated wireless channels, we propose a simple linear CSI feedback receiver that can be used to improve the performance of UQ-UC transmission while still retaining the attractive zero-delay feature. We provide bounds on the performance of such UQ-UC CSI feedback and study its impact on the achievable information rates. Furthermore, we explore its application and performance in multiple-antenna multiuser wireless systems, and also propose a corresponding pilot-assisted channel-state estimation scheme.     

高速移动通信系统中OTFS分数多普勒信道估计加窗研究

针对正交时频空间(OTFS)调制系统中分数多普勒信道对应的物理路径信道状态信息估计困难及计算复杂度较高等问题,该文提出一种节省导频资源的脉冲匹配滤波(PRS-PMF)信道估计算法。该算法首先使用数据与导频联合成帧的嵌入式辅助导频方法获得等效信道的估计,然后通过互相关匹配滤波估计出各路径信道状态信息,相比于传统的脉冲导频互相关匹配滤波信道估计算法,能够在降低计算复杂度的同时减少导频资源的占用。在此基础上,对OTFS系统加窗,减少窗口响应主瓣的整数样点数量并降低旁瓣电平,有效改善了等效信道多普勒响应函数的自相关特性,从而降低了其他符号及噪声对估计符号的干扰。