MIMO SC-FDE系统的时域信道估计新算法

研究了循环正交训练序列的设计,并提出了适用于多入多出单载波频域均衡系统的时域信道估计新算法。首先选取Chu序列作为基准序列,并引入循环前缀与循环后缀构成循环正交序列,从而在接收端通过相关运算得到多天线信道的时域冲激响应估计。进一步,将长训练序列替换为多组连续重复且总长度相等的循环正交短训练序列,并利用时域相关和时间分集达到与原有长序列法相同的性能。仿真结果表明,所提时域信道估计算法不仅能够抑制天线间的干扰,而且有效地降低了噪声的方差,即使在低信噪比下也能获得较好的误比特率性能。     

Enhanced channel-estimation technique for MIMO-OFDM systems

In multi-input-multi-output orthogonal frequency-division multiplexing systems, conventional channel-estimation techniques using comb-type training symbols give relatively large mean squared errors (MSEs) at the edge subcarriers. To reduce the MSEs at these subcarriers, a cyclic comb-type training structure is proposed. In the proposed cyclic training structure, all types of training symbols are transmitted cyclically at each antenna. At the receiver, the channel frequency responses that are estimated using each training symbol are averaged with weights obtained from the corresponding MSEs. Computer simulations showed that the proposed cyclic training structure gives more signal-to-noise ratio gain than the conventional training structure.     

基于LDPC码的单载波频域均衡系统

该文设计了一种联合判决-反馈均衡的单载波频域均衡(SC-FDE)系统,该系统用固定波形的短pn序列取代常规SC-FDE系统中的循环前缀(CP),并以多个短pn序列组成的长PN序列作信道训练从而解决快变信道的初始估计和跟踪问题。针对该系统,一种在时域内对接收的多个训练序列进行平均,然后提出了在频域对信道信息进行估计的信道训练算法,该算法与传统SC-FDE系统相比,其计算复杂度较低。另外,提出了一种增加纵向校验的LDPC码用于该系统中降低信噪比门限,提高系统的整体性能。仿真结果表明在多径衰落信道中,此系统可获得较为理想的结果。     

Blind channel estimation of space-time Frequency-Shift Keying

The decoupled coherent Maximum Likelihood （ML） detection algorithm presented in this letter can sharply reduce the complexity of the receiver as well as provide better error performance under the precondition that channel should be estimated first. Considering the bandwidth inefficiency of Frequency Shift Keying （FSK）, the acquisition of channel state information through training sequences will further decrease the transmission efficiency. This letter presents a blind channel estimation algorithm based on noise subspace theory which can acquire channel information without any training symbols. The simulation shows that the algorithm brings about fewer channel estimation errors while the frequency efficiency can be increased.     

Robust multiuser detection for multicarrier CDMA systems

Multiuser detection (MUD) for code-division multiple-access (CDMA) systems usually relies on some a priori channel estimates, which are obtained either blindly or by using training sequences, and the covariance matrix of the received signal, usually replaced by the sample covariance matrix. However, such prior estimates are often affected by errors that are typically ignored in subsequent detection. In this paper, we present robust channel estimation and MUD techniques for multicarrier (MC) CDMA by explicitly taking into account such estimation errors. The proposed techniques are obtained by optimizing the worst case performance over two bounded uncertainty sets pertaining to the two types of estimation errors. We show that although the estimation errors associated with the prior channel estimate and the sample covariance matrix are generally not bounded, it is beneficial to optimize the worst case performance over properly chosen bounded uncertainty sets determined by a parameter called bounding probability. At a slightly higher computational complexity, our proposed robust detectors are shown to yield improved performance over the standard detectors that ignore the prior estimation errors.     

Training Signal Design for Estimation of Correlated MIMO Channels With Colored Interference

In this paper, we study the problem of estimating correlated multiple-input multiple-output (MIMO) channels in the presence of colored interference. The linear minimum mean square error (MMSE) channel estimator is derived and the optimal training sequences are designed based on the MSE of channel estimation. We propose an algorithm to estimate the long-term channel statistics needed for the construction of the optimal training sequences. We also design an efficient scheme to feed back the required information to the transmitter where we can approximately construct the optimal sequences. Numerical results show that the optimal training sequences provide substantial performance gain for channel estimation when compared with other training sequences     

隐含训练序列信道估计中的功率分配

与传统时分发送训练序列的信道估计算法相比,隐含训练序列信道估计算法将训练序列与信息序列直接相加后通过天线发送,从而节约了信道带宽。然而,在天线发送总功率一定时,训练序列的功率越大,信息序列的功率便越小,从而导致信道均衡器的信噪比减小。本文研究了基于MIMO系统的隐含训练序列信道估计算法,分析了信道均衡器信噪比与训练序列功率的关系,并根据均衡器信噪比最大原则推导出训练序列与信息序列的最佳功率分配。分析和仿真结果表明:在训练序列的最佳功率点上,信道均衡器的信噪比最高;随着接收天线信噪比的增加,训练序列的最佳功率增大。     

Analysis of protocol sequences for slow frequency hopping

An error probability bound for protocol sequences is derived for frame asynchronous access on a slow frequency hopping channel. This bound depends on the maximum and average cyclic Hamming correlation properties of the protocol sequences used. Constructions of protocol sequences with good cyclic correlation properties are given.     

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。     

EM-based joint data detection and channel estimation of DS-CDMA signals

We present two efficient iterative receiver structures of tractable complexity for joint multiuser detection and multichannel estimation (JDE) of direct-sequence code-division multiple-access signals. The schemes result from an application of the expectation-maximization (EM) and the space-alternating generalized expectation-maximization (SAGE) algorithms, respectively. The EM-JDE receiver updates the data bit sequences in parallel, while the SAGE-JDE receiver reestimates them successively. The channel parameters are updated in parallel in both schemes. The EM algorithm provides a set of free parameters, called weight coefficients, which can be selected to optimize its performance. Two optimality criteria are defined and analytical expressions for the corresponding optimized weight coefficients are given. Monte-Carlo simulations of a synchronous scenario show that the proposed JDE receivers have excellent multiuser efficiency and are robust against errors in the estimation of the channel parameters. Moreover, very short training sequences are required for the JDE schemes to converge. Simulation results further demonstrate that the SAGE-JDE receiver exhibits a better performance when the users' bit sequences are updated in the order of increasing signal strength, i.e., the bit sequence of the user with the weakest signal strength is updated first at each stage.     

Subspace-based blind channel estimation for OFDM by exploiting virtual carriers

Reliable channel estimation is indispensable for orthogonal frequency-division multiplexing (OFDM) systems employing coherent detection and adaptive loading in order to achieve high data rate communications. Several options exist in practical OFDM systems-including training symbols, cyclic prefix, virtual carriers, pilot tones, and receiver diversity-to facilitate channel estimation. In this paper, a subspace blind channel estimation method based on exploiting the presence of virtual carriers is proposed for OFDM systems over a time-dispersive channel. The method can be applied to conventional OFDM systems with cyclic prefix as well as OFDM systems with no cyclic prefix. The reduction/elimination of cyclic prefix thereby provides the OFDM systems the potential to achieve higher channel utilization than most previously reported cyclic prefix based estimators. Sufficient channel identifiability condition is developed as well. Comparison with two other recently reported subspace methods is presented via computer simulations to support the effectiveness of the proposed method.     

高性能的OFDM频偏估计新方法

频偏估计是OFDM的关键技术.本文提出了一种具有高精度的OFDM频偏估计新方法.新方法首先将接收信号与本地训练序列作相关来消除训练序列的影响,然后进行频率粗同步.补偿粗频偏后再利用消除训练序列影响的序列或循环前缀作相关实现频率精同步.新方法具有频率偏移估计范围大和估计精度高的优点.文中分析并得出这两种估计方法的频偏估计下界.此频偏估计方法使训练序列的设计更加灵活,可按时间同步或信道估计等性能最优来设计.     

基于叠加训练的非合作多用户/MIMO信道估计

提出一种基于叠加训练的单载波非合作多用户/MIMO系统的迭代信道估计与检测方案。首先利用变换域方法构造具有零周期互相关特性的训练序列,从而消除多天线间的相互干扰,实现基于一阶统计量的信道估计。然后采用联合符号检测的迭代信道估计方法,利用检测序列作为额外的“训练序列”来降低信息序列自身干扰。与现有的叠加训练信道估计方案比较,新方案中训练序列构造更加灵活,在低信噪比下信道估计均方误差和误码率性能更优,且复杂度更低,仿真结果表明了该方案的有效性。     

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.     

Space-time channel estimation and performance analysis for wireless MIMO-OFDM systems with spatial correlation

This paper treats channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with correlation at the receive antenna array. A two-step channel estimation algorithm is proposed. Firstly, the iterative quadrature maximum likelihood based time delay and spatial signature estimation is presented by utilizing special training signals with a cyclic structure. The receive spatial correlation matrix of the vector valued channel impulse response is formulated as a function of the spatial signature, the time delay, and the pulse shaping filter. The joint spatio-temporal (JST) filtering based minimum mean squared error channel estimator is derived by virtue of the spatial correlation. In addition, the effect of channel estimation errors on the bit error probability performance of the space-time block coded OFDM system over correlated MIMO channels is derived. The Cramer-Rao lower bound on the time delay estimate is provided for a benchmark of the performance comparison. The performance of proposed algorithms is illustrated based on analysis and computer simulations. The JST channel estimator achieves significant gains in the mean squared error compared to the temporal filtering. It also enables remarkable savings in the pilot symbol power level.     

Block FIR decision-feedback equalizers for filterbank precodedtransmissions with blind channel estimation capabilities

In block transmission systems, transmitter-induced redundancy using finite-impulse response (FIR) filterbanks can be used to suppress intersymbol interference and equalize FIR channels irrespective of channel zeros. At the receiver end, linear or decision-feedback (DF) FIR filterbanks can be applied to recover the transmitted data. Closed-form expressions are derived for the FIR linear or DF filterbank receivers corresponding to varying amounts of transmission redundancy. Our framework encompasses existing block transmission schemes and offers low implementation-cost equalization techniques both when interblock interference is eliminated, and when IBI is present as, e.g., in orthogonal frequency-division multiplexing with insufficient cyclic prefix. By applying blind channel estimation methods, our filterbank transmitters-receivers (transceivers) dispense with bandwidth consuming training sequences. Extensive simulations illustrate the merits of our designs     

Blind channel identification and equalization withmodulation-induced cyclostationarity

Recent results have pointed out the importance of inducing cyclostationarity at the transmitter for blind identification and equalization of communication channels. This paper addresses blind channel identification and equalization relying on the modulation-induced cyclostationarity, without introducing redundancy at the transmitter. It is shown that single-input single-output channels can be identified uniquely from output second-order cyclic statistics, irrespective of the location of channel zeros, color of additive stationary noise, or channel order overestimation errors, provided that the period of modulation-induced cyclostationarity is greater than half the channel length. Linear, closed-form, nonlinear correlation matching, and subspace-based approaches are developed for channel estimation and are tested using simulations. Necessary and sufficient blind channel identifiability conditions are presented. A Wiener cyclic equalizer is also proposed     

Adaptive channel estimation using cyclic prefix in multicarriermodulation system

Multicarrier modulation (MCM) is a promising technique for high rate data transmission and the channel estimation is very important for the implementation of MCM. We found that the cyclic prefix, originally used solely to reduce the intersymbol interference (ISI), can be viewed as a source of channel information. Based on this observation, we propose an adaptive channel estimation algorithm using the cyclic prefix. This algorithm can adaptively track the channel variation without additional training sequences     

OFDM系统中帧同步技术研究

在分析S＆C算法的基础上,提出一种基于新训练序列的改进的正交频分复用（OFDM）同步方法。改进后的算法仍使用两个训练符号,以训练符号本身的强自相关性来消除定时同步中的峰值平台问题,并将训练符号的循环前缀（CP）置为0,以尽量消除CP对定时同步的影响。新的训练符号可直接在时域估计出栽波频偏。改进后的算法在定时同步的准确性...     

Iterative channel estimation for turbo equalization of time-varying frequency-selective channels

We investigate turbo equalization, or iterative equalization and decoding, as a receiver technology for systems where data is protected by an error-correcting code, shuffled by an interleaver, and mapped onto a signal constellation for transmission over a frequency-selective channel with unknown time-varying channel impulse response. The focus is the concept of soft iterative channel estimation, which is to improve the channel estimate over the iterations by using soft information fed back from the decoder from the previous iteration to generate "extended training sequences" between the actual transmitted training sequences.