Joint channel estimation and symbol detection in Rayleighflat-fading channels with impulsive noise

A new technique for joint channel estimation and symbol detection in the Rayleigh flat-fading channels with impulsive noise is developed. This technique involves an approximation to the likelihood statistics for such channels, which in turn is based on the Masreliez approximation of nonlinear filtering. It is seen that the proposed detector outperforms the detector based on the Kalman filter     

Low-complexity joint channel estimation and decoding for pilotsymbol-assisted modulation and multiple differential detection systemswith correlated Rayleigh fading

Joint channel estimation and decoding in a time-varying Rayleigh fading channel is considered. Knowing that the optimal solution or even the truncated near-optimal solution using iterative processing has an exponential complexity which hinders the practicability, a reduced complexity approach is proposed. This approach keeps the existing channel estimation and decoding schemes almost intact, while applying iterative processing to effectively exchange information between them. Thus, the complexity is rendered linear, and estimator adaptability can be easily established. We apply this approach to pilot symbol-assisted modulation (PSAM) and differentially modulated systems. It turns out that the performance is improved and the robustness to fading parameters is enhanced. Through simulations, we also show that the proposed method performs almost as well as the near-optimal design     

Maximum-likelihood bearing estimation with partly calibrated arraysin spatially correlated noise fields

The problem of using a partly calibrated array for maximum likelihood (ML) bearing estimation of possibly coherent signals buried in unknown correlated noise fields is shown to admit a neat solution under fairly general conditions. More exactly, this paper assumes that the array contains some calibrated sensors, whose number is only required to be larger than the number of signals impinging on the array, and also that the noise in the calibrated sensors is uncorrelated with the noise in the other sensors. These two noise vectors, however, may have arbitrary spatial autocovariance matrices. Under these assumptions the many nuisance parameters (viz., the elements of the signal and noise covariance matrices and the transfer and location characteristics of the uncalibrated sensors) can be eliminated from the likelihood function, leaving a significantly simplified concentrated likelihood whose maximum yields the ML bearing estimates. The ML estimator introduced in this paper, and referred to as MLE, is shown to be asymptotically equivalent to a recently proposed subspace-based bearing estimator called UNCLE and rederived herein by a much simpler approach than in the original work. A statistical analysis derives the asymptotic distribution of the MLE and UNCLE estimates, and proves that they are asymptotically equivalent and statistically efficient. In a simulation study, the MLE and UNCLE methods are found to possess very similar finite-sample properties as well. As UNCLE is computationally more efficient, it may be the preferred technique in a given application     

Space-time modulation and coding over transmit correlated fading channels

Multi-dimensional space-time modulation schemes can be classified by the manner in which signal dimensions are shared among transmit antennas. In aggregate transmit antenna (ATA) systems, a generalization of Tarokh, Seshadri, Calderbank's (TSC) approach, there is total sharing of dimensions. In orthogonal transmit antenna (OTA) systems, a generalization of many traditional diversity schemes, there is no sharing of dimensions. In partially orthogonal transmit antennas (POTA), a combination of ATA with OTA, subsets of available dimensions are shared by subsets of transmit antennas. This letter considers such coded schemes for spatially correlated fading channels. Over strongly transmit correlated channels, in addition to coding and diversity gains, ATA and POTA can harvest a transmit beamforming-like gain. This letter presents a scheme, POTARep, designed to provide beamforming-like gain as well as diversity and coding gains, yielding improved performance over a highly transmit correlated channel.     

Joint symbol detection and channel parameter estimation inasynchronous DS-CDMA systems

A method for jointly estimating the time delay and complex gain parameters, as well as detecting the transmitted symbols in an asynchronous multipath DS-CDMA system, is presented. A short training sequence is used to obtain a coarse estimate of the channel parameters, which is consequently used to detect the symbols. By exploiting structure in the digitally modulated signals, the method iterates to (i) improve the estimate of the channel parameters and (ii) reduce the probability of incorrect detection. The method's efficacy is demonstrated by numerical simulations     

Space-time coding ambiguities in joint adaptive channel estimation and detection

This paper studies the error propagation effect that is caused by certain ambiguities in joint data detection-channel tracking algorithms for transmission diversity schemes. Here, we use a space-time (ST) receiver based on the maximum a posteriori (MAP) method that takes into account the channel estimation error assuming the unknown channel to have a given complex multivariate Gaussian probability density function (pdf) (i.e., a Ricean channel). The decision criterion that is expressed in quadratic form represents either a linear detector or a noncoherent-nonlinear detector in extreme cases. Then, the channel pdf for the next iteration is updated by estimates of the second-order statistics of the channel coefficients, and a very simple decision-directed adaptive algorithm is derived for adaptive channel estimation. The adaptive algorithm can efficiently track a fast Rayleigh fading channel and, as a result, achieves robust performance. However, the occurrence of two types of ambiguities initiated in deep fades result in error propagation. Some remedies called space-time ambiguity remedies (STARs) are proposed to prevent error propagation. A new time-varying space-time coding (TVST) scheme is suggested as a bandwidth-efficient method to combat the permutation ambiguity impairment. This coding scheme, in conjunction with a differential detector, can resolve the ambiguity problem.     

Space-time coding over correlated fading channels with antenna selection

In a previous paper by Bahceci et al., antenna selection ' for multiple-antenna transmission systems under the assumption that the subchannels between antenna pairs fade independently was studied. In this paper, the performance of such systems when the subchannels experience correlated fading is considered. It is assumed that the channel-state information (CSI) is available only at the receiver, the antenna selection is performed only at the receiver, and the selection is based on the instantaneous received signal power. The effects of channel correlations on the diversity and coding gain when the receiver system is a subset of the antennas are quantified. Theoretical results indicate that the correlations in the channel do not degrade the diversity order, provided that the channel is full rank. However, it does result in some performance loss in the coding gain.     

On noncoherent receivers for DSTM in spatially correlated fading

In this letter, we derive a multiple-symbol differential detection (MSDD) and a novel MSDD-based decision-feedback differential detection (MS-DFDD) receiver for differential space-time modulation transmitted over spatially correlated multiple-input multiple-output fading channels. We show that MS-DFDD outperforms previously proposed DFDD schemes that are based on scalar and vector prediction (SP-DFDD and VP-DFDD). In addition, we prove that at high signal-to-noise ratio (SNR) VP-DFDD is equivalent to SP-DFDD and thus fails to properly exploit the spatial fading correlations.     

A spatially and temporally correlated fading model for arrayantenna applications

In this paper, a new channel model is proposed. Since it is spatially and temporally correlated simultaneously, this new model is well consistent with the real environment of array antenna applications. The widely used sum of scattered waves and the measurement-based model have a common drawback of imperfect statistical properties, reducing the reliability of simulation results. The new model (spatially and temporally correlated fading model [STCFM]) is derived rigorously in the spatiotemporal domain so that it can provide high accuracy for the evaluation of the array antenna system. Simulation results show that direction of arrival (DOA) and angle of spread (AOS) are well defined in STCFM, BPSK with two-branch maximal ratio combining and DBPSK with differential detection are considered to verify the spatial and temporal correlation robustness of the new model, respectively. As is shown, the simulation results agree well with the theory     

OFDM系统的迭代联合信道估计与符号检测算法

提出了通过降低导频功率来提高OFDM传输效率,同时采用迭代的联合信道估计和符号检测算法来保证较好误码性能的接收方案。理论分析与仿真结果表明,当数据信息与导频信息的功率比不高于l0dB时,本文提出的算法能够有效地降低系统误码率,同时该方法还具有算法简单,收敛速度快的特点。     

Adaptive joint multiuser detection and channel estimation in multipath fading CDMA channels

The problem of joint multiuser detection and channel estimation in frequency-selective Rayleigh fading CDMA channels is considered. First the optimal multiuser detector for such channels is derived, which is seen to have a computational complexity exponential in the product of the number of users and the length of the transmitted data sequence. Two suboptimal detectors are then developed and analyzed, both of which employ decorrelating filters at the front-ends to eliminate the multiple-access interference and the multipath interference. The symbol-by-symbol detector uses a Kalman filter and decision feedback to track the fading channel for diversity combining. The per-survivor sequence detector is in the form of the Viterbi algorithm with the trellis updates being computed by a bank of Kalman filters in the per-survivor fashion. Both suboptimal detectors require the knowledge of all waveforms of all users in the channel and the channel fading model parameters. Adaptive versions of these suboptimal detectors that require only the knowledge of the waveform of the user of interest are then developed. The adaptive receivers employ recursive-least-squares (RLS) minimum-mean-square-error (MMSE) filters at the front-end to mitigate the interference, and use a bank of linear predictors to track the fading channels. It is shown that the front-end RLS-MMSE filters can be implemented using systolic arrays to exploit massively parallel signal processing computation, and to achieve energy efficiency. Finally, the performance of the suboptimal detectors and their adaptive versions are assessed by simulations. This revised version was published online in July 2006 with corrections to the Cover Date.     

DS-CDMA system with joint channel estimation and MAP detection intime-selective fading channels

In this paper, maximum a posteriori (MAP) detection is applied to a direct-sequence code-division multiple-access (DS-CDMA) system jointly with identification and estimation of time-selective fading channels. By sampling the outputs of the matched filter and combining antenna array elements, strong and time-varying multiple-access interference (MAI) is characterized and suppressed instantaneously. The decision statistics for MAP detection are obtained from the conditional probability density function of the prediction error. The prediction is accomplished by approximating the fading channel with a constrained nonlinear state model. Unknown parameters such as auto-regressive (AR) process coefficients, noise covariance matrices, and the antenna array vector are estimated based on received sample vectors only. Also, differential modulation is applied to eliminate the need for pilot insertion. Through computer simulations, near-optimum bit error rates (BERs) are found     

UN-MUSIC and UN-CLE: an application of generalized correlationanalysis to the estimation of the direction of arrival of signals inunknown correlated noise

A new approach is proposed for the consistent estimation of the directions of arrival (DOA) of signals in an unknown spatially-correlated noise environment. The signal and noise model used is based on the assumption that the data are received by two arrays well separated so that their noise outputs are uncorrelated. The generalized correlation decomposition of the cross-correlation matrix between the two arrays is then introduced. Of particular interest is the canonical correlation decomposition. The analysis of the generalized correlation leads to various interesting geometric and asymptotic properties of the eigenspace structure. Two algorithms, UN-MUSIC and UN-CLE, are developed to estimate the DOA of signals in unknown spatially correlated noise based on the utilization of these properties. Computer simulations show that these methods are superior in performance compared to conventional methods. Furthermore, it is demonstrated that the new methods are equally effective even when only one sensor array is employed     

A deterministic channel simulation model for spatially correlatedRayleigh fading

We propose a deterministic vector channel simulation model for generating the fading waveforms that satisfy not only rigorous temporal correlation but also arbitrary spatial correlation by means of Doppler phase difference sampling. The proposed method is more efficient than the conventional pseudonoise (PN) filtered Gaussian model with coloring process in evaluating the laboratory level performance of the mobile communication systems employing adaptive arrays or space diversity     

Joint channel and symbol estimation by oblique projections

The problem of simultaneous blind channel and symbol estimation of a single-input multiple-output (SIMO) communication channel is considered. It is shown that the outer product of the channel vector and the channel input sequence can be obtained by a linear estimator that has the finite sample convergence property. Furthermore, this estimator can be obtained by the use of oblique projections. An order detection algorithm that avoids the use of subjective thresholding is also proposed. Applications to multiuser detection are also considered     

Approximate capacity of OSTBC-OFDM in spatially correlated MIMO Nakagami-m fading channels

Orthogonal space-time block coding in combination with orthogonal frequency-division multiplexing converts frequency-selective multiple-input-multiple-output (MIMO) channels into a set of equivalent scalar Gaussian channels. For MIMO Nakagami-m fading channels in the presence of spatial correlation, a simple and closed-form approximation for the capacity of the equivalent channels is derived with good accuracy.     

Time delay estimation with unknown spatially correlated Gaussiannoise

The problem of estimating the difference in arrival times of a non-Gaussian signal at two spatially separated sensors is considered. The signal is assumed to be corrupted by spatially correlated Gaussian noises of unknown cross-correlation. The author proposes and analyzes two new classes of methods for time delay estimation based on higher order statistics. The proposed methods are conceptually very similar to the traditional cross-correlation-based techniques in that the proposed criteria peak at a lag value equalizing true delay. Since the proposed methods are based upon higher order cumulant statistics of the data, they result in estimators that remain unbiased in the presence of Gaussian noise     

On channel estimation and detection for multicarrier signals infast and selective Rayleigh fading channels

Time-domain channel estimation and detection techniques are presented for multicarrier signals in a fast and frequency-selective Rayleigh fading channel. As a consequence of the time-varying channel, the orthogonality between subcarriers is destroyed in conventional frequency-domain approaches, resulting in interchannel interference, which increases an irreducible error floor in proportion to the normalized Doppler frequency. An important feature of the proposed technique is the ability to exploit the time-selective channel as a provider of time diversity. This enables us to achieve performance superior to any other structure without increasing bandwidth or incorporating redundancy, in order to reduce the complexity of the estimator, we apply the theory of optimal low rank approximation to a minimum mean squared error channel estimator and present a theoretical calculation of mean squared error and simulations to confirm that the estimator is robust to changes in channel characteristics     

Frequency-selective fading channel estimation with a polynomialtime-varying channel model

A rectangular-windowed least-squares estimator using a polynomial model of the time-varying channel taps is proposed for estimating the impulse response of a frequency-selective fading channel. This method provides a significant improvement in mean square identification error (MSIE) over the conventional least mean squares (LMS) and the exponentially weighted recursive least squares (EW-RLS) algorithms without a polynomial model. A detailed study of the effects of channel parameters, such as the fading rate and the signal-to-noise ratio, on the proposed method is carried out. The performance of the method depends on the window size of the least squares estimator and the polynomial order being used. Algorithms to obtain the approximately optimal window size and polynomial order are proposed and are shown to perform well