MIMO-OFDM系统中一种改进的信道估计方法

信道的准确估计是提高MIMO-OFDM系统性能的关键.在最优导频时域信道估计的基础上,提出了一种较低复杂度的改进算法,利用时变信道的自回归(AR)模型构造卡尔曼滤波器对估计出的时域信道响应进行滤波,提高信道时域响应的估计精度.仿真结果表明,在慢时变信道环境下,改进方法可以进一步提高信道估计的精度,同时保持了较低的复杂度.     

有限反馈分布式预编码协作通信系统及性能分析

该文提出了一种有限反馈条件下的分布式预编码非正交协作分集系统(DP-NOCD)。该系统利用目的端的多天线特性,将中继信号进行预处理后在共享的信道资源上发送,从而同时提高了传统正交协作分集(OCD)系统的频谱效率和可靠性。利用译码转发(DF)中继信道模型,并将虚拟的两输入多输出信道在矢量空间分解为两个正交子信道,提出了一种系统误码率最小准则下的预编码方法。该方法能改善系统误码性能,且反馈量低。仿真结果表明,在理想协作场景下,与非协作系统和无干扰的OCD系统相比,DP-NOCD系统在误码率为10-3时分别可获得5～6.2 dB和1～1.2 dB的增益。     

时变信道中自适应VR-HARQ研究

为了更好地解决时变信道中可靠性与吞吐率这一对矛盾,本文提出一种基于线性预测的自适应冗余可变混合ARQ(VR-HARQ)方案.在该方案中,由于时变信道的慢衰落特性,时变信道被等效为有限状态的Markov过程,每个Markov状态对应信道的不同信噪比,同时,文章详细地描述了信道吞吐率与误码率之间的数学关系,推导了每个Markov状态的最佳编码方案,然后系统采用自适应线性预测算法,根据当前个时段的信道状态,估计下一个时段信道的信噪比以及其所对应的Markov状态,最后根据吞吐率最大原则选择合适的纠错编码方案.仿真结果表明:自适应线性预测VR-HARQ方案的性能明显优于传统VR-HARQ方案.     

基于卷积码的差分DF协作分集通信系统

现存的协作分集通信系统都是在假设接收端完全掌握了信道状态信息(CSI)的情况下建立起来的,这就不可避免地增加了接收端对CSI的重传。然而,在某些实际情况下,由于衰落信道条件变化太快难以进行有效的信道估计或为了降低移动终端的复杂度和造价而免去信道估计,这时就必须研究其他方案来弥补这个不足。协作分集的差分调制模型可以解决这个问题。差分调制模型虽然不需要知道CSI,但是系统性能不是很理想。将卷积编码与差分调制相结合,就可以在很大程度上提高系统的性能。     

基于DFT-BEM模型的LOFDM系统双散射信道最大多普勒扩展估计

栅格正交频分复用（Lattice Orthogonal Frequency Division Multiplexing, LOFDM）系统凭借特殊的网格时频结构和更大的欧式距离特性,在快速移动环境下展现了卓越的抗时变、抗多径能力。最大多普勒扩展作为LOFDM系统自适应策略的重要参数之一,准确的最大多普勒扩展估计对于LOFDM系统发送信号设计以及自适应策略实现十分重要。本文针对LOFDM系统的特殊信号结构以及双散射信道的快时变特性,采用DFT-BEM信道模型近似快时变信道响应,结合快时变信道下LOFDM系统块传输接收实现,利用梳状导频辅助估计多普勒域平均信道频率响应,在此基础上利用信道响应估计值的时间相关函数实现基于F范数的信道最大多普勒扩展估计;并提出基于子空间的最大多普勒扩展估计算法,降低了噪声对最大多普勒扩展估计性能的影响,在低信噪比条件下有效改善了估计性能。      

移动环境中WIMAX-OFDM的一种信道估计算法

对在移动环境下WIMAX-OFDM系统的信道估计进行了分析，并在此基础土提出一种新的前导信道估计方法，通过虚载波信道估计和自适应低通滤波实现了移动环境下的信道估计。仿真结果表明：该算法在复杂度增加很少的前提下，不仅给出了精度较高的信道估计信息，而且明显提高了系统误码性能。     

基于低轨卫星PCMA信号的信道估计算法研究

【目的】随着天地一体化信息网络的发展,低轨卫星通信系统迎来发展热潮,成对载波多址（PCMA）技术凭借其节省带宽资源的优点也逐渐向低轨卫星通信发展。然而,传统PCMA技术多用于高轨卫星中,无法适应低轨卫星信道高动态的衰落信道特性,使得PCMA接收端误码性能大大下降,其中的瓶颈在于重叠信号的信道估计与均衡技术。【方法】针对低轨卫星信道特点,文章提出了一种联合训练序列估计与自回归（AR）模型预测的信道估计方案。借鉴叠加训练序列信道估计的思想,引入了适用于PCMA混合信号信道估计的迭代方法,通过迭代提升训练序列信道估计的精确度;并利用AR模型实时预测数据序列的信道状态信息（CSI）,同时也通过AR模型预测达到降低训练序列信道估计频次的目的,以适应低轨卫星信道的动态性。【结果】仿真结果表明,叠加训练序列信道估计的思路可以适用于PCMA信号中,经过迭代可以获得精确信道估计值。文章所提方法可以有效提高信道估计的精确性,且经过信号分离以及解调后,在信噪比>9 dB时误码率可以达到10-3量级。【结论】文章所提信道估计方案并入PCMA接收方案中后,误码率损失在可接受范围内,可以支持PCMA技术在低...     

基于波束空间CSI估计的OFDM自适应天线

现有pre-FFT OFDM自适应天线系统中信道状态信息(CSI)估计在阵元空间进行,其性能易受干扰的影响而恶化,本文提出一种基于波束空间CSI估计的pre-FFT自适应天线阵方案,可显著提高CSI估计的精度和稳健性,仿真结果表明该方案较传统的阵元空间天线阵有明显的性能提升,特别在强干扰条件下,阵元空间阵列可能无法工作,而本文方案仍然具有良好的性能.     

基于Simulink的WiMAX-MIMO-OFDM物理层性能仿真

为了估计WiMAX-MIMO-OFDM系统的信道特性,使用Simulink工具搭建了一个基于IEEE802．16e的WiMAX物理层模型,改进了一种针对快速时变信道的估计算法,研究和对比了在接收端不同移动速度情况下,线性插值、高斯插值和三次样条插值在原算法和改进算法下的系统误码率性能。仿真结果表明,在高速运动情况下,提出的改进算法能有效提高系统性能,三次样条插值的性能最好,但运算复杂度较高。     

UPF算法在OFDM时变信道估计中的应用

为了提高正交频分复用(OFDM)系统中时变信道估计的精度和系统性能,提出一种利用无迹粒子滤波(UPF)算法的OFDM时变信道估计方法.该方法首先将OFDM系统时变信道建模为具有动态特性的状态方程,然后利用UPF算法,结合接收信号动态地估计信道状态.仿真结果表明:在高斯和非高斯环境下,所提的方法均可以获得比采用传统粒子滤...     

基于过时信道信息的多用户中继网络性能分析

该文对基于非实时信道状态信息(Channel State Information, CSI)的多用户放大转发(Amplify-and- Forward, AF)协作通信系统的性能进行分析。系统采用一点对多点的通信系统模型,中继节点根据过时的CSI选择用户。通过推导得出中断概率、信道容量和符号错误概率(Symbol Error Rate, SER)的近似表达式。理论分析适用于链路同分布或者非同分布。仿真结果验证理论的正确性,并说明了各种参数对系统性能的影响。同时指出,增加用户数并不能提高系统性能,性能的提高可以通过改变中继的位置来实现。     

Optimal power allocation with AF and SDF strategies in dual-hop cooperative MIMO networks

Dual-hop cooperative Multiple-Input Multiple-Output (MIMO) network with multi-relay cooperative communication is introduced. Power allocation problem with Amplify-and-Forward (AF) and Selective Decode-and-Forward (SDF) strategies in multi-node scenario are formulated and solved respectively. Optimal power allocation schemes that maximize system capacity with AF strategy are presented. In addition, optimal power allocation methods that minimize asymptotic Symbol Error Rate (SER) with SDF cooperative protocol in multi-node scenario are also proposed. Furthermore, performance comparisons are provided in terms of system capacity and approximate SER. Numerical and simulation results confirm our theoretical analysis. It is revealed that, maximum system capacity could be obtained when powers are allocated optimally with AF protocol, while minimization of system’s SER could also be achieved with optimum power allocation in SDF strategy. In multi-node scenario, those optimal power allocation algorithms are superior to conventional equal power allocation schemes.     

SER PERFORMANCE ANALYSIS OF DECODE-AND-FORWARD COOPERATIVE SCHEME IN SATELLITE MOBILE CHANNEL

In this paper,Symbol-Error-Rate (SER) performance analysis is provided for a Decodeand-Forward (DF) cooperative scheme in satellite mobile channel environment.We present a satellite mobile cooperative communication system model and derive two generalized error probability expressions with Cyclical Redundancy Check (CRC) or not.We also derive and simulate SER of the proposed system over different satellite mobile channels.The results show that the analytical results are in great accordance with the ones obtained by simulation.Also,it was shown that,whether or not adopt CRC depends on the channel link quality between the source node and the relay node.     

Performance analysis and power allocation for decode‐and‐forward cooperative communications over Rician fading channel

This paper derives the asymptotic symbol error rate (SER) and outage probability of decode‐and‐forward (DF) cooperative communications over Rician fading channels. How to optimally allocate the total power is also addressed when the performance metric in terms of SER or outage probability is taken into consideration. Analysis reveals the insights that Rician factor has a great impact on the system performance as compared with the channel variance, and the relay–destination channel quality is of importance. In addition, the source–relay channel condition is irrelevant to the optimal power allocation design. Simulation and numerical evaluation substantiate the tightness of the asymptotic expressions in the high‐SNR regions and demonstrate the accuracy of our theoretical analysis. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Nakagami-m衰落信道下空时分组码的性能估计

基于等效单输入单输出SISO (Single-input Single-output) 模型,利用矩量母函数 (MGF) 分析法,空时分组码STBC (Space-Time Block Coding) 的误符号率是可以得到其准确闭式表达式的.对于独立同分布Nakagami-m衰落信道下的空时分组码的性能进行了研究,给出了采用M-PSK 和M-QAM调制方案的不同空时分组编码矩阵误符号率的闭式解以及基于闭式解的解析性能结果,通过蒙特卡洛仿真验证了闭式解的准确性.还从调制方案的角度对于几种新的空时分组码的性能进行了一些新的讨论.     

Effects of channel estimation error on array processing based QO-STBC coded OFDM systems

This letter addresses the issues on performance degradation caused by channel estimation error of quasiorthogonal space-time block (QO-STBC) coded OFDM systems employing array processing decoder. The least square (LS) channel estimator is employed to obtain the required channel state information (CSI). Taking mean square error (MSE) as a performance metric, we evaluate the performance of the LS estimator in MIMO-OFDM systems over frequency selective channels, and its impact on symbol error rate (SER) using both analysis and simulations.     

Cooperative Transmission Using Quasi-Orthogonal Space-Time Block Codes with Adaptive Decode-and-Forward Relaying Protocol

In this paper, we propose a cooperative transmission scheme using quasi-orthogonal space-time block codes (QOSTBCs) for multiple-input multiple-output (MIMO) relay networks. Comparing with the conventional cooperative transmission scheme using orthogonal space-time block codes (OSTBCs), the proposed scheme can achieve higher bandwidth efficiency with the same decoding complexity. Moreover, an adaptive decode-and-forward (ADF) relaying protocol is proposed based on one-bit channel state information (CSI) feedback. According to the CSI feedback, a better transmission mode can be selected between the direct transmission and decode-and-forward (DF) cooperative transmission. In addition, the outage performance of the proposed scheme is investigated and a closed-form upper bound on the outage probability is derived. The performance analysis shows that the proposed scheme can achieve a full diversity order, which is higher than that of the direct and DF cooperative transmissions.     

Capacity of Time-Varying Channels With Causal Channel Side Information

We derive the capacity of time-varying channels with memory that have causal channel side information (CSI) at the sender and receiver. We obtain capacity of block-memoryless and asymptotically block-memoryless channels with block-memoryless or weakly decorrelating side information. Our coding theorems rely on causal generation of the codewords relative to the causal transmitter CSI. The CSI need not be perfect, and we consider the case where the transmitter and receiver have the same causal CSI as well as the case where the transmitter CSI is a deterministic function of the receiver CSI. For block-memoryless and asymptotically block-memoryless channels, our coding strategy averages mutual information density over multiple transmission blocks to achieve the maximum average mutual information. We apply the coding theorem associated with the block-memoryless channel to determine the capacity and optimal input distribution of intersymbol interference (ISI) time-varying channels with causal perfect CSI about the time-varying channel. The capacity of this channel cannot be found through traditional decomposition methods     

Bi-directional LSTM based channel estimation in 5G massive MIMO OFDM systems over TDL-C model with Rayleigh fading distribution

In this work, a deep learning (DL)-based massive multiple-input multiple-output (mMIMO) orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped delay line type C (TDL-C) model with a Rayleigh fading distribution at frequencies ranging from 0.5 to 100 GHz. The proposed bi-directional long short-term memory (Bi-LSTM) channel state information (CSI) estimator uses online learning during training and offline learning during the practical implementation phase. The design of the estimator takes into account situations in which prior knowledge of channel statistics is limited and targets excellent performance, even with limited pilot symbols (PS). Three separate loss functions (mean square logarithmic error [MSLE], Huber, and Kullback–Leibler Distance [KLD]) are assessed in three classification layers. The symbol error rate (SER) and outage probability performance of the proposed estimator are evaluated using a number of optimization techniques, such as stochastic gradient descent (SGD), momentum, and the adaptive gradient (AdaGrad) algorithm. The Bi-LSTM-based CSI estimator is trained considering a specific number of PS. It can be readily seen that by incorporating a cyclic prefix (CP), the system becomes more resilient to channel impairments, resulting in a lower SER. Simulations show that the SGD optimization approach and Huber loss function-trained Bi-LSTM-based CSI estimator have the lowest SER and very high estimation accuracy. By using deep neural networks (DNNs), the Bi-LSTM method for CSI estimation achieves a superior channel capacity (in bps/Hz) at 10 dB than long short-term memory (LSTM) and other conventional CSI estimators, such as minimum mean square error (MMSE) and least squares (LS). The simulation results validate the analytical results in the study.