脉冲超宽带(UWB)跳时系统的频域信道估计

提出一种基于序列和的最大似然(ML)频域信道估计算法,该算法可适用于对跳时UWB通信系统进行基于训练序列的信道估计和盲信道估计,大大简化了运算的复杂性。在仿真中比较了基于理想信道估计、基于一般的频域信道估计以及基于序列和的ML频域信道估计的性能。结果显示,在频域的估计过程中,对发射信号的频谱设定适当的可信门限后,可以获得与直接进行频域信道估计相似的性能。     

SNR estimation in time-varying fading channels

Signal-to-noise ratio (SNR) estimation is considered for phase-shift keying communication systems in time-varying fading channels. Both data-aided (DA) estimation and nondata-aided (NDA) estimation are addressed. The time-varying fading channel is modeled as a polynomial-in-time. Inherent estimation accuracy limitations are examined via the Cramer-Rao lower bound, where it is shown that the effect of the channel's time variation on SNR estimation is negligible. A novel maximum-likelihood (ML) SNR estimator is derived for the time-varying channel model. In DA scenarios, where the estimator has a simple closed-form solution, the exact performance is evaluated both with correct and incorrect (i.e., mismatched) polynomial order. In NDA estimation, the unknown data symbols are modeled as random, and the marginal likelihood is used. The expectation-maximization algorithm is proposed to iteratively maximize this likelihood function. Simulation results show that the resulting estimator offers statistical efficiency over a wider range of scenarios than previously published methods.     

Genetic algorithm assisted joint multiuser symbol detection andfading channel estimation for synchronous CDMA systems

A novel multiuser code division multiple access (CDMA) receiver based on genetic algorithms is considered, which jointly estimates the transmitted symbols and fading channel coefficients of all the users. Using exhaustive search, the maximum likelihood (ML) receiver in synchronous CDMA systems has a computational complexity that is exponentially increasing with the number of users and, hence, is not a viable detection solution. Genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems. Based on the ML rule, GAs are developed in order to jointly estimate the users' channel impulse response coefficients as well as the differentially encoded transmitted bit sequences on the basis of the statistics provided by a bank of matched filters at the receiver. Using computer simulations, we showed that the proposed receiver can achieve a near-optimum bit-error-rate (BER) performance upon assuming perfect channel estimation at a significantly lower computational complexity than that required by the ML optimum multiuser detector. Furthermore, channel estimation can be performed jointly with symbol detection without incurring any additional computational complexity and without requiring training symbols. Hence, our proposed joint channel estimator and symbol detector is capable of offering a higher throughput and a shorter detection delay than that of explicitly trained CDMA multiuser detectors     

On the effect of receiver estimation error upon channel mutual information

Our goal in this paper is to study the effect of the receiver structure upon the achievable data rates. We consider transmission of linearly precoded data symbols over a frequency selective block fading multiple input multiple output (MIMO) wireless channel. To encompass a number of transmission schemes, we study this problem utilizing affine precoding, which is a unified model of linearly precoded data symbols with superimposed training. We focus on Bayesian receivers that estimate both the unknown fading coefficients and the data symbols. The receiver may adopt either of the following strategies to retrieve the data symbols: strategy (i) the receiver obtains joint Bayesian channel and symbol estimates, strategy, (ii) the receiver obtains a Bayesian channel estimate initially and the channel measurement is utilized to estimate the data symbols. For both strategies, we provide lower bounds on the mutual information between the data symbols and their corresponding estimates, and we relate these bounds to the symbol Cramer-Rao bound (CRB) matrices. In contrast to strategy (ii), for strategy (i) the lower bound does not depend on either the channel estimate or the covariance of the channel estimation error. For strategy (ii) we show that asymptotically (as the size of the transmission block grows) there is no loss of information after the maximum a posteriori (MAP) estimate of Gaussian symbols. We also provide guidelines to design affine precoders that maximize the derived lower bounds under the total average transmit power constraint.     

Turbo Equalization with Prediction and Iterative Estimation of Time-Varying Frequency-Selective Channels

Turbo equalization that cooperates with channel prediction and iterative channel estimation is investigated for mobile wireless communications. Frames of information bits are encoded, interleaved, and mapped to symbols for transmission over time-varying frequency-selective fading channels. At the receiver, the Turbo equalizer consists of a maximum a posteriori probability equalizer/demapper and a soft-input soft-output maximum a posteriori probability decoder. With initial channel estimates and sparse pilot insertion across a number of frames, the receiver predicts the channel of the current frame. The effect of error propagation of channel prediction is mitigated by the de-interleaver that is embedded in the Turbo equalizer. The predicted and interpolated channel is refined through a channel estimator that uses the soft estimates of data symbols at each Turbo iteration. Due to the bandlimiting feature of channel variation, the channel estimation error can be smoothed by low-pass filters that follow the channel estimator. Simulation results show that incorporating Turbo equalization with channel prediction and iterative channel estimation can combat time- and frequency-selective fading and improve reception performance.     

Trade-Off Between Diversity and Channel Estimation Errors in Asynchronous MC-DS-CDMA and MC-CDMA

This paper investigates the trade-off between diversity and channel estimation errors for asynchronous multi-carrier CDMA (MC-CDMA) and multicarrier direct-sequence CDMA (MC-DS-CDMA). We construct a side-by-side comparison between the two systems by assuming equal operating and channel conditions. Both systems perform pilot-symbol- aided channel estimation and maximal ratio combining at the receiver, where the weighting coefficients are determined by the channel estimates at each sub-carrier. Closed-form expressions for the probability of error of both systems are derived under two separate channel scenarios. These two scenarios assume a frequency-selective Rayleigh fading channel, where the coherence bandwidth is equal to either the bandwidth of a MC-DS-CDMA sub-band or the bandwidth of a MC-CDMA sub-band. Finally, we compare the bit error rates of the two systems for different information rates, number of users, and number of pilot symbols used in each channel estimate.     

Code-aided joint channel and frequency offset estimation for DS-CDMA

This paper deals with joint data detection, synchronization and channel parameter estimation for direct-sequence code-division multiple-access systems over frequency-selective channels. In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. We show through computer simulations that the proposed code-aided estimation techniques considerably outperform their conventional DA counterparts.     

Channel estimation and multiuser detection in long-code DS/CDMAsystems

The problems of channel estimation and multiuser detection for direct sequence code division multiple access (DS/CDMA) systems employing long spreading codes are considered. With regard to channel estimation, several procedures are proposed based on the least-squares approach, relying on the transmission of known training symbols but not requiring any timing synchronization. In particular, algorithms suited for the forward and reverse links of a single-rate DS/CDMA cellular system are developed, and the case of a multirate/multicode system, wherein high-rate users are split into multiple virtual low-rate users, is also considered. All of the proposed procedures are recursively implementable with a computational complexity that is quadratic in the processing gain, with regard to the issue of multiuser detection, an adaptive serial interference cancellation (SIC) receiver is considered, where the adaptivity stems from the fact that it is built upon the channel estimates provided by the estimation algorithm. Simulation results show that coupling the proposed estimation algorithms with a SIC receiver may yield, with a much lower computational complexity, performance levels close to those of the ideal linear minimum mean square error (MMSE) receiver, which assumes perfect knowledge of the channels for all of the users and which (in a long-code scenario) has a computational complexity per symbol interval proportional to the third power of the processing gain     

Performance comparisons of channel estimation techniques in multipath fading CDMA

The problem of pilot-symbol-aided estimation of multipath fading channels in up-link code-division multiple-access (CDMA) systems is considered. The transmitted symbol streams of each user are divided into time-slots; and each time-slot contains a number of pilot-symbols followed by information data symbols. Channel estimation is based on interpolation of the channel values corresponding to the pilot symbols in adjacent time-slots. Existing channel estimation techniques, including the weighted multislot average method and the wavelet expansion method, are studied. Two new channel estimation methods, namely, the robust channel interpolator, and the polynomial channel interpolator, are developed and are compared with these techniques. It is seen that the two new channel estimation methods significantly outperform the existing methods in multipath fading CDMA systems, for a wide range of Doppler values, and under various receiver schemes (with single or multiple receive antennas), such as the RAKE receiver, the interference cancellation receiver, and a receiver which performs iterative channel estimation and interference cancellation.     

Iterative receiver for OFDM-SDMA system

An iterative receiver is proposed based on the EM (Expectation-Maximization) algorithm for an OFDM-SDMA (Orthogonal Frequency Division Multiplexing-Space Division Multiple Access) system. By using a few pilots in every OFDM symbol, both channel estimation and multiuser detection can be simultaneously obtained by iteration. The computer simulation results show this receiver can track channel variations and detect multiuser symbols for different number of users under time-varying multipath channels.     

BLIND CHANNEL ESTIMATION IN DELAY DIVERSITY FOR FREQUENCY SELECTIVE CHANNELS1

Delay diversity is an effective transmit diversity technique to combat adverse effects of fading. Thus far, previous work in delay diversity assumed that perfect estimates of current channel fading conditions are available at the receiver and training symbols are required to estimate the channel from the transmitter to the receiver. However, increasing the number of the antennas increases the required training interval and reduces the available time with in whichdata may be transmitted. Learning the channel coefficients becomes increasingly difficult for the frequency selective channels. In this paper, with the subspace method and the delay character of delay diversity, a channel estimation method is proposed, which does not use training symbols. It addresses the transmit diversity for a frequency selective channel from a single carrier perspective in the form of a simple equivalent flat fading model. Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.     

多码CDMA系统中联合并行干扰抵消与迭代信道估计方法

本文针对多码CDMA系统提出了一种联合并行干扰抵消与迭代信道估计方法。该方法首先通过导频符号对信道进行估计，然后使用RAKE接收机后的软信息对信道参数进行修正，最后通过并行干扰抵消(PIC)去除多码干扰(MCI)。仿真结果表明，经过多次迭代后，该方法可显著地降低多码CDMA系统的误比特率平台。本文同时还给出了信道估计质量、码道数和PIC次数对多码CDMA系统性能的影响。     

A VERTICAL LAYERED SPACE—TIME CODE AND ITS CLOSED—FORM BLIND SYMBOL DETECTION

Vertical layered space-time codes have demonstrated the snormous potential to accommodate rapid flow data.Thus far,vertical layered space-time codes assumed that perfect estimates of current channel fading conditions are available at the receiver.However,increasing the number of transmit antennas increases the required training interval and reduces the available time in which data may be transmitted before the fading coefficients change.In this paper,a vertical layered space-time code is proposed.By applying the subupace method to the layered space-time code,the symbols can be detected without training symbols and channel estimates at the transmitter or the receiver.Monte Carlo simulations show that performance can approach that of the detection method with the knowledge of the channel.     

Binary adaptive coded pilot symbol assisted modulation over Rayleigh fading channels without feedback

Pilot symbol assisted modulation (PSAM) is a standard approach for transceiver design for time-varying channels, with channel estimates obtained from pilot symbols being employed for coherent demodulation of the data symbols. In this paper, we show that PSAM schemes can be improved by adapting the coded modulation strategy at the sender to the quality of the channel measurement at the receiver, without requiring any channel feedback from the receiver. We consider performance in terms of achievable rate for binary signaling schemes. The transmitter employs interleaved codes, with data symbols coded according to their distance from the nearest pilot symbols. Symbols far away from pilot symbols encounter poorer channel measurements at the receiver and are therefore coded with lower rate codes, while symbols close to pilot symbols benefit from recent channel measurements and are coded with higher rate codes. The performance benefits from this approach are quantified in the context of binary signaling over time-varying Rayleigh fading channels described by a Gauss-Markov model. The spacing of the pilot symbols is optimized to maximize the mutual information between input and output in this setting. Causal and noncausal channel estimators of varying complexity and delay are considered. It is shown that, by appropriate optimization for the spacing between consecutive pilot symbols, the adaptive coding techniques proposed can improve achievable rate, without any feedback from the receiver to the sender. Moreover, channel estimation based on the two closest pilot symbols is generally close to optimal.     

How much training is needed in multiple-antenna wireless links?

Multiple-antenna wireless communication links promise very high data rates with low error probabilities, especially when the wireless channel response is known at the receiver. In practice, knowledge of the channel is often obtained by sending known training symbols to the receiver. We show how training affects the capacity of a fading channel-too little training and the channel is improperly learned, too much training and there is no time left for data transmission before the channel changes. We compute a lower bound on the capacity of a channel that is learned by training, and maximize the bound as a function of the received signal-to-noise ratio (SNR), fading coherence time, and number of transmitter antennas. When the training and data powers are allowed to vary, we show that the optimal number of training symbols is equal to the number of transmit antennas-this number is also the smallest training interval length that guarantees meaningful estimates of the channel matrix. When the training and data powers are instead required to be equal, the optimal number of symbols may be larger than the number of antennas. We show that training-based schemes can be optimal at high SNR, but suboptimal at low SNR.     

垂直分层空时码系统下的信道盲估计

对垂直分层空时码系统进行信道估计时，常需采用训练序列，发射天线个数的增加会使得所需的训练符号个数增加，减少了传输数据的有效时间。本文将信号处理中的子空间方法同分层空时码的编码结构相结合，提出了一种垂直分层空时码，实现了无需训练序列的信道估计。Monte Carlo仿真结果表明，在相干时间允许的范围内，利用本文算法估计出的信道进行信号检测时，其性能十分接近使用准确信道信息的检测结果。     

Optimum transmit-receive beamforming with noisy channel estimates for correlated MIMO Rayleigh channels

In this paper, we design jointly optimum transmitter and receiver beamforming structures in correlated MIMO Rayleigh fading channels with noisy channel estimates, and evaluate their performance through a closed-form expression for the probability of error. At the receiver, an estimate of the channel is obtained based on the transmitted pilot symbols. The knowledge of the estimate is then made available to the transmitter through a feedback channel. It is assumed that spatial correlation exists, either at the transmitter or at the receiver. A new exact closed-form expression for the probability of error is derived and the joint effects of diversity order and channel estimation accuracy on system performance are analyzed.     

Performance of antenna diversity multiuser receivers in CDMA channels with imperfect fading estimation

The performance of antenna diversity coherent and differentially coherent linear multiuser receivers is analyzed in frequency-nonselective Rayleigh fading CDMA channels with memory. The estimates of the complex fading processes are utilized for maximal-ratio combining and carrier recovery of the coherent multiuser receiver. To analyze the impact of channel estimation errors on the receiver performance, error probability is assessed directly in terms of the fading rate and the number of active users, showing the penalty imposed by imperfect channel estimation as well as the fading-induced error probability floor. The impact of fading dynamics on the differentially coherent decorrelating receiver with equal-gain combining is quantified. While performance of multiuser receivers at lower SNR is determined by both the fading dynamics and the number of active CDMA users, performance at higher SNR is given by an error probability floor which is due to fading only and has the same value as in a single-user case. The comparison of the two receiver structures indicates that the coherent decorrelating receiver with diversity reception may be preferable to the differentially coherent one in nonselective fading CDMA channels with memory.     

Data-Aided Synchronization for MF-TDMA Multi-Carrier Demultiplexer/Demodulator (MCDD)

In this paper, a data-aided (DA) synchronization method is developed to jointly recover symbol-timing, frequency offset, and carrier phase for MF-TDMA on-board processing (OBP) satellite system. The estimates, which are obtained from a block of symbols transmitted through an Additive White Gaussian Noise (AWGN) channel and a fast Rayleigh fading channel, can be obtained with reduced computational complexity and fast acquisition time. The estimation accuracy in terms of MSE is derived and illustrated. Its effect on the overall system BER performance is also discussed. Furthermore, the relationships between timing synchronization, frequency offset recovery, and carrier phase error compensation are also analyzed respectively. It is apparent that the proposed estimation method is not only accurate and efficient, but it makes the communication system robust to impairment parameters as well.      

平坦衰落信道下基于变分贝叶斯的多天线信号联合符号检测算法

该文针对平坦衰落信道下存在信道参数差异的多天线接收信号联合参数估计和符号检测问题,提出一种基于变分贝叶斯的联合处理算法。算法直接利用多个接收数据流进行信息符号的估计,抑制传统信号合成与解调解耦处理带来的性能损失。将问题建模为已知多组观测数据条件下发送符号、信道传输时延、信道增益和噪声功率的联合最大后验估计问题。基于变分贝叶斯理论对该最大后验进行近似求解,在相对熵最小化的准则下,推导得到了各个待估参数解析形式的近似后验分布——变分分布。所提算法无需计算各参数精确的点估计值,而是采用信道参数和信息符号变分分布迭代处理的方式进行联合求解。仿真结果表明,所提算法通过多信号、多参数的联合处理能够获得优于经典解耦处理和部分联合处理技术的系统误码率性能,且在接收天线数目较多和观测数据长度较短时性能优势体现更加明显。