Non data-aided SNR estimation of OFDM signals

This letter deals with the problem of non data aided (NDA) signal to noise ratio (SNR) estimation of OFDM signals transmitted through unknown multipath fading channel. Most of existing OFDM SNR estimators are based on the knowledge of pilot sequences which is not applicable in some contexts such as cognitive radio for instance. We show that it is possible to take advantage of the periodic redundancy induced by the cyclic prefix to get an accurate NDA SNR estimator. Numerical simulations highlight the benefit of the proposed method compared with the state of the art.     

Non Data Aided SNR Estimation for OFDM Signals in Frequency Selective Fading Channels

This paper deals with the problem of non data aided (NDA) signal to noise ratio (SNR) estimation of OFDM signals transmitted through unknown multipath fading channel. Most of present day’s SNR estimators are based on the knowledge of pilot sequences which is not applicable in some contexts such as cognitive radio for example. Moreover in Multipath fading channels SNR also depends on frequency offset which is caused by mismatch between the oscillator in the transmitter and that in the receiver. Previous NDA SNR estimation schemes assumed a perfect synchronization at reception (i.e. τ = 0 and ${\varepsilon = 0}$ ) which results estimation of SNR with less accuracy. The frequency offset attenuates the desired signal and causes intercarrier interference, thus reducing the SNR. In this paper we propose a new NDA SNR estimator which uses periodic redundancy induced by the cyclic prefix, considering SNR degradation due to frequency offset ( ${\varepsilon}$ ).     

A robust channel estimator for DS-CDMA systems under multipath fading channels

This paper addresses the problem of channel estimation for direct-sequence code-division multiple-access (DS-CDMA) systems with time-varying multipath fading channels. The multipath fading channels are modeled as autoregressive (AR) models. A method is first proposed to convert the time-varying regression model due to the time-varying nature of users' information symbols into a time-invariant one. Then, a polynomial approach is proposed to obtain the minimum mean square error (MMSE) estimator. The uncertainty of the channel model and decision errors of the DS-CDMA detector are taken into consideration in the design of the MMSE estimator. Compared with the Kalman estimator, the computational complexity of the proposed algorithm is much lower. The simulation results show that the proposed estimator provides a comparable estimation performance with the Kalman estimator and is robust for fast-fading channels.     

Robust channel estimation for OFDM systems with rapid dispersivefading channels

Orthogonal frequency-division multiplexing (OFDM) modulation is a promising technique for achieving the high bit rates required for a wireless multimedia service. Without channel estimation and tracking, OFDM systems have to use differential phase-shift keying (DPSK), which has a 3-dB signal-to-noise ratio (SNR) loss compared with coherent phase-shift keying (PSK). To improve the performance of OFDM systems by using coherent PSK, we investigate robust channel estimation for OFDM systems. We derive a minimum mean-square-error (MMSE) channel estimator, which makes full use of the time- and frequency-domain correlations of the frequency response of time-varying dispersive fading channels. Since the channel statistics are usually unknown, we also analyze the mismatch of the estimator-to-channel statistics and propose a robust channel estimator that is insensitive to the channel statistics. The robust channel estimator can significantly improve the performance of OFDM systems in a rapid dispersive fading channel     

Soft Decoding Assisted SNR Estimation Under Block Fading Channels for Orthogonal Modulations

The performance of the coded orthogonal modulation (OM) system under slow fading channels heavily depends on the estimation of the signal-to-noise ratio (SNR), including the fading amplitude and the noise spectral density. However, a relatively long packet of pilot symbols is often required to guarantee the accuracy of the SNR estimation, which makes it impractical in some situations. To address this problem, this paper proposes an iterative SNR estimation algorithm using the soft decoding information based on the expectation-maximization algorithm. In the proposed method, a joint iterative loop between the SNR estimator and decoder is performed, where the extrinsic information generated by the soft decoder is employed to enhance the estimation accuracy and the SNR estimated by the estimator is used to generate the soft information to the decoder. Also, no pilot symbols are needed to estimate the SNR in the proposed estimator. The Cramer–Rao lower bound (CRLB) of fully data-aided (FDA) estimation is derived to works as the final benchmark. The performance of the proposed algorithm is evaluated in terms of the normalized mean square errors (NMSEs) and the bit error rates (BERs) under block fading channels. Simulation results indicate that the NMSE of the proposed estimator reaches the CRLB of the FDA estimator and outperforms that of the approximate ML (ML-A) estimator proposed by Hassan et al. by 4.1 dB. The BER performance of coded OM system with the proposed estimation algorithm is close to the ideal case where the channel fading and the noise spectral density are known at the receiver.     

基于基扩展模型的UKF-RTSS高可靠鲁棒V2V信道估计

车联网应用场景对无线通信在带宽、时延、可靠性方面提出了更高的需求,特别是车辆对车辆(Vehicle to Vehicle, V2V)场景。针对V2V高速移动场景,时/频域选择性衰落(双选衰落)和非平稳特性给信道估计带来的技术挑战,该文提出了一种基于基扩展模型(Basis Expansion Model, BEM)的UKF-RTSS (Unscented Kalman Filter- Rauch-Tung-Striebel Smoother)信道估计方法。该方法采用BEM拟合快时变信道,将信道参数的估计转化为基函数系数的估计;通过无迹卡尔曼滤波(UKF),联合估计数据处信道冲激响应与时域自相关系数,用于追踪快时变的信道响应。为了进一步提升信道估计的精度,引入RTSS对后向信道状态信息进行信道估计和插值,与UKF构成了“滤波和平滑”结构的UKF-RTSS联合估计器。系统仿真分析表明,在不同速度的快时变条件下,所提方法相比其他经典方法具有更高的信道估计精度和鲁棒性,特别适用于车联网下的无线通信场景。     

Receiver structures for time-varying frequency-selective fadingchannels

Several receiver structures for linearly modulated signals are proposed for time-varying frequency-selective channels. Their channel estimators explicitly model the time variation of the channel taps via polynomials. These structures are constructed from the following building blocks: (i) sliding or fixed block channel estimators; (ii) maximum likelihood sequence detectors (MLSDs) or decision feedback equalizers (DFEs); and (iii) single or multiple passes. A sliding window channel estimator uses a window of received samples to estimate the channel taps within or at the end of the window. Every symbol period, the window of samples is slid along another symbol period, and a new estimate is calculated. A fixed block channel estimator uses all received samples to estimate the channel taps throughout the packet, all at once. A single pass receiver estimates the channel and detects data once only. A multipass receiver performs channel estimation and data detection repetitively. The effect of the training symbol positions on the performance of the block multipass approach is studied. The bit error rate (BER) performance of the MLSD structures is characterized through simulation and analysis. The proposed receivers offer a range of performance/complexity tradeoffs, but all are well suited to time-varying channels. In fast fading channels, as the signal-to-noise ratio (SNR) increases, they begin to significantly outperform the per-survivor processing-based MLSD receivers which employ the least mean-squares (LMS) algorithm for channel estimation     

Time and Frequency Synchronization with Channel Estimation for SC-FDMA Systems Over Time-Varying Channels

The constant amplitude zero autocorrelation sequence based synchronization and its usage in the block-type channel estimation for the single carrier frequency division multiple access (SC-FDMA) systems are vulnerable to the time-varying channels. Therefore, the channel estimation errors limit the performance of SC-FDMA systems in fast fading environments and result an irreducible error floor. In this paper, cyclic prefix based maximum likelihood estimator of time/frequency synchronization with comb-type channel estimation for the SC-FDMA systems are proposed to track the channel variations. Moreover, the residual time/frequency offsets calculations are derived for SC-FDMA systems. Simulation results confirm and illustrate that the proposed receiver is capable of tracking fast fading channel parameters and improving the overall performance as compared with the conventional receiver.     

Analytical Analysis of Bayesian CramÉr–Rao Bound for Dynamical Rayleigh Channel Complex Gains Estimation in OFDM System

In this paper, we consider the Bayesian Cramer-Rao bound (BCRB) for the dynamical estimation of multipath Rayleigh channel complex gains in data-aided (DA) and non-data-aided (NDA) OFDM systems. This bound is derived in an online and offline scenarios for time-invariant and time-varying complex gains within one OFDM symbol, assuming the availability of prior information. In NDA context, whereas this true BCRB is hard to evaluate, we present a closed-form expression of a BCRB, i.e., the asymptotic BCRB (ABCRB) or the modified BCRB (MBCRB). We discuss, based on the theoretical and simulation results, the interest of using some past and future observations in terms of Doppler spread for the complex gains estimation.     

直扩系统时变单音干扰抑制的新方法

针对直接序列扩频通信系统中的时变单音干扰,提出了一种频域干扰估计时域对消的新方法。在系统中,将干扰信道建模为时变衰落信道。该算法首先在频域对时变单音干扰信号参数进行估计,然后对时变单音干扰进行重构和对消,推导了理论误码率公式。理论分析和仿真结果表明,该算法性能由干扰功率和多普勒频移等因素决定。在频率选择性衰落信道下,当信噪比为20dB,扩频增益为16,干扰信道多普勒频移为100Hz时,该算法可以抑制20dB(干信比)的单音干扰。      

基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法

提出了一种适用于时间频率选择性衰落信道的MIMO-OFDM系统的组合信道估计方法。采用AR过程对信道进行建模,利用基于导频的低维Kalman滤波算法进行信道估计,并采用LS算法估计时变的信道衰减因子。Kalman滤波跟踪了信道的时域相关性,为了同时跟踪信道的频域相关性,采用了一种基于MMSE(minimum mean square error)的合并器对Kalman滤波算法进行修正。仿真表明,提出的这种组合算法降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,改进了基于LS准则的信道估计算法,并且与复杂的高维Kalman滤波算法的信道估计性能相当。     

Model-based pilot and data power adaptation in psam with periodic delayed feedback

We consider the optimum design of pilot-symbolassisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in mediumrate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.     

Pilot-based estimation of time-varying multipath channels forcoherent CDMA receivers

Reliable coherent wireless communication requires accurate estimation of the time-varying multipath channel. This paper addresses two issues in the context of direct-sequence code-division multiple access (CDMA) systems: (i) linear minimum-mean-squared-error (MMSE) channel estimation based on a pilot transmission and (ii) impact of channel estimation errors on coherent receiver performance. A simple characterization of the MMSE estimator in terms of a bank of filters is derived. A key channel characteristic controlling system performance is the normalized coherence time, which is approximately the number of symbols over which the channel remains strongly correlated. It is shown that the estimator performance is characterized by an effective signal-to-noise ratio (SNR)-the product of the pilot SNR and the normalized coherence time. A simple uniform averaging estimator is also proposed that is easy to implement and delivers near-optimal performance if properly designed. The receivers analyzed in this paper are based on a time-frequency RAKE structure that exploits joint multipath-Doppler diversity. It is shown that the overall receiver performance is controlled by two competing effects: shorter coherence times lead to degraded channel estimation but improved inherent receiver performance due to Doppler diversity, with opposite effects for longer coherence times. Our results demonstrate that exploiting Doppler diversity can significantly mitigate the error probability floors that plague conventional CDMA receivers under fast fading due to errors in channel estimation     

宽带CDMA中一种新的自适应信道估计方法

在衰落信道中进行相干解调必须知道瞬时的信道参数，但由于信道是时变的，所以信道估计器的频率响应和带宽应该是由衰落信道的统计特性和系统的信干比决定。利用瞬时信道估计的自相关函数，本文提出了信道估计的一种新的自适应算法。在平坦瑞利信道中的计算机仿真表明本方法在3G标准支持的所有多普勒频率范围内都能获得良好的均方误差性能。     

Timing Synchronization for Cooperative Communications with Detect and Forward Relaying

A non-data-aided near maximum likelihood (NDA-NML) symbol timing estimator is presented, which is applied to a cooperative communication system with a source, relay and destination. A Cramer rao bound (CRB) for the estimator for asymptotically low signal-to-noise (SNR) ratio case is derived. The timing complexity of the NDA-NML estimator is derived and compared with the correlation based data-aided maximum likelihood (DA-ML) estimator. It is demonstrated that the complexity of the NDA-NML estimator is much less than that of correlation based DA-ML estimator. The bit-error-rate (BER) performance of this system operating in a detect-and-forward (DAF) mode is studied where the channel state information (CSI) is available at the receiver and the symbol timings are estimated independently for each channel. SNR combining (SNRC) and equal ratio combining (ERC) methods are considered. It is found that timing estimation error has a significant effect on BER performance. It is also found that for large timing error the benefit of cooperative diversity could vanish. It is demonstrated that significant gains can be made with both combining methods with cooperation and timing estimation, where the gains are the same for both estimators.     

Gaussian codes and weighted nearest neighbor decoding in fading multiple-antenna channels

We investigate the fading multiple-antenna channel. The decoder is assumed to possess imperfect channel fading information. A modified nearest neighbor decoder with an innovative weighting factor is introduced and an expression for the generalized mutual information (GMI), the achievable rate, is obtained. We show that under certain conditions the achievable rate is equivalent to that of a fading multiple-antenna Gaussian channel where fading is known to the receiver and is equal to the channel estimation, and where noise is due to both the channel noise and the channel estimation error. We show that for our communication scheme, the minimum mean square error (MMSE) channel estimator is optimal in the sense that it achieves the highest value of GMI, and hence the highest communication rate. Additionally, a training based multiple-input multiple-output (MIMO) scheme in a block-fading channel is investigated and it is shown that the number of degrees of freedom depends on the signal-to-noise ratio (SNR).     

Channel estimation for ultra-wideband communications

This paper deals with channel estimation in ultra-wideband communications operating in a multipath environment and in the presence of multiaccess interference. The channel parameters are the attenuations and delays incurred by the signal echoes along the propagation paths. Time-hopping modulation with binary symbols is assumed. The estimation method is based on the maximum-likelihood criterion and is applied to two different scenarios: either with known symbols (DA estimation) or with unknown symbols (NDA estimation). The effects of the estimation errors on the performance of a RAKE receiver are assessed by simulation by comparing the receiver bit-error rate with either perfect channel estimates or imperfect estimates as obtained from the proposed algorithms. The results show that the degradations are tolerable as long as the number of users is limited. They also show that the DA method has an edge over the NDA in that it can handle a larger number of users for a fixed degradation. The number of users that can be accommodated in practice is found for some values of the system parameters.     

An adaptive receiver for the time- and frequency-selective fadingchannel

An adaptive receiver is presented in this paper for the reception of linearly modulated signals transmitted over a time- and frequency-selective fading channel. The channel is modeled as a truncated power series which represents the dispersive fading channel as a sum of three elementary flat-fading channels. The proposed receiver consists of a sequence estimator with a parallel channel estimator. The channel estimator recovers the instantaneous fading processes associated with each elementary channel and filters them to generate one-step predictions of each fading process. Some implementation difficulties and solutions are also discussed. Computer simulations using quadrature phase-shift keying (QPSK) and channels with moderate delay spreads and fade rates have been used to evaluate the performance of the receiver. The results show that our technique has potential in channels with delay spread of about 20%, signal-to-noise ratio (SNR) greater than 15 dB, and applications requiring bit-error rates (BER's) less than 10^-2     

MIMO-OFDM快衰落信道的稀疏自适应感知估计

在多输入多输出（MIMO）-正交频分复用（OFDM） 系统中,怎样在较高频谱利用率的情况下对快时变信道进行较为准确的估计是一个具有挑战性的课题。该文在利用压缩感知理论可提高系统频谱利用率的基础上,提出了一种适合于快时变环境下MIMO-OFDM 系统的稀疏自适应信道估计方法。该方法不再受到奈奎斯特采样频率条件约束,避免了传统导频辅助信道估计方法频谱利用率低的缺点。该文方法通过构建多天线群时频结构特征稀疏基,利用多天线间和群时变OFDM符号内信道冲激响应具有更强稀疏性的特点,对MIMO-OFDM快衰落信道进行稀疏变换。由于实际MIMO-OFDM快衰落信道往往处于频率选择性、时变性和多种干扰并存的复杂环境,受到干扰的信道参数对系统而言是未知,采用该方法克服了现有基于压缩感知理论的信道估计方法需要预先知道信道冲激响应稀疏度才能重构信道参数的不足,在信道稀疏度未知道的情况下,运用稀疏自适应的方法来对不同时频结构特征的信道参数进行估计。仿真结果表明所提估计方法具有对快时变信道参数估计的鲁棒性和较高频谱利用率,且均方误差小。      

Maximum likelihood carrier phase recovery for coherently orthogonalCPFSK signals

ML estimation of carrier phase for coherently orthogonal continuous-phase frequency-shift-keying (COCPFSK) signals is considered. Although the estimator, in general is nonimplementable, its high and low signal-to-noise-ratio approximations both lead to linear readily implementable receiver structures. The high SNR approximation yields a DA receiver, whereas the low SNR approximation yields an NDA receiver. The performance of both receivers in term of bit error probability is analyzed. The existence of an unmodulated component in the sufficient statistical representation of a COCPFSK signal is pointed out, and it is shown how this component enters directly into maximum-like carrier recovery. This leads to interpretation of the NDA receiver as a generalization of the conventional matched-filter envelope-detector receiver. The insights gained here are useful to the problem of ML carrier recovery for Viterbi decoding of continuous phase modulation signals