Blind Channel Estimation Research Articles

Transmit Delay Structure Design for Blind Channel Estimation over Multipath Channels

Wireless communications often exploit guard intervals between data blocks to reduce interblock interference in frequency-selective fading channels. Here we propose a dual-branch transmission scheme that utilizes guard intervals for blind channel estimation and equalization. Unlike existing transmit diversity schemes, in which different antennas transmit delayed, zero-padded, or time-reversed versions of the same signal, in the proposed transmission scheme, each antenna transmits an independent data stream. It is shown that for systems with two transmit antennas and one receive antenna, as in the case of one transmit antenna and two receive antennas, blind channel estimation and equalization can be carried out based only on the second-order statistics of symbol-rate sampled channel output. The proposed approach involves no preequalization and has no limitations on channel-zero locations. Moreover, extension of the proposed scheme to systems with multiple receive antennas and/or more than two transmit antennas is discussed. It is also shown that in combination with the threaded layered space-time (TST) architecture and turbo coding, significant improvement can be achieved in the overall system performance.

A Low Complexity RLS-PASTd Algorithm for Blind Multiuser Detection in Dispersive CDMA Channels

For joint blind channel estimation and multiuser detection in direct-sequence code division multiple access (DS-CDMA) systems, a combined scheme is proposed, which couples the recursive least-squares (RLS) adaptations and the PASTd subspace tracking algorithm. A major advantage of the RLS-PASTd algorithm is that it admits an adaptive implementation with low computational complexity instead of singular value decomposition. Simulation results demonstrate the fast tracking capability and high steady-state estimation accuracy of the proposed algorithm in both the time-invariant and time-variant environments

Blind signal reception in downlink time‐hopping ultrawideband communication system

AbstractUltra wideband (UWB) impulse radio (IR) system is currently being considered for several applications due to its attractive features that include low‐power carrierless modulation and ample multipath diversity. Among the various modulation and multiple‐access schemes, this paper deals with time‐hopping (TH) antipodal pulse amplitude modulation (PAM), operating in the presence of multipath‐fading downlink channel. We develop two types of low‐complexity mobile station (MS) receivers. One is based on the RAKE reception scheme and the other is designed to meet the minimum‐output‐energy (MOE) criterion. However, since accurate channel information is crucial for reliable operation, thereby we propose a blind (non‐data aided) channel estimator. Simulation results show that the MOE receiver outperforms the RAKE receiver in multiuser environment. Moreover, both the channel estimation algorithm and the MOE reception schemes are shown to be reliable and near‐far resistant. Copyright © 2007 John Wiley & Sons, Ltd.

Blind Channel Estimation Based on URV Decomposition Technique for Uplink of MC-CDMA

In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity. Keywords—Channel estimation, MC-CDMA, SVD, URV

(Semi-)blind channel estimation for space time block coded system with transmit diversity

This paper deals with a blind channel estimation method for space-time coded block transmission system. By concatenating the real part and imaginary part of the received signal to form an elongated vector, we derive an equivalent input–output system model. Then channel state information (CSI) is blindly estimated using subspace method, utilizing only the redundancy inherent in space-time block coding (STBC) and cyclic prefix (CP). The estimation ambiguity, which is common to all blind methods, is analyzed in detail and we prove that there only exist four scalar indeterminacies. Three effective methods to eliminate the ambiguities are also proposed. Compared with other blind channel estimation methods for space time systems, this method needs neither redundant precoding nor oversampling, and thus has higher data rate. Besides, this method is robust to channel order overestimation, which is effectively demonstrated by numerical simulations.

Blind Channel Estimation for MIMO-OFDM Systems

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> By combining multiple-input multiple-output (MIMO) communication with the orthogonal frequency division multiplexing (OFDM) modulation scheme, MIMO-OFDM systems can achieve high data rates over broadband wireless channels. In this paper, to provide a bandwidth-efficient solution for MIMO-OFDM channel estimation, we establish conditions for channel identifiability and present a blind channel estimation technique based on a subspace approach. The proposed method unifies and generalizes the existing subspace-based methods for blind channel estimation in single-input single-output OFDM systems to blind channel estimation for two different MIMO-OFDM systems distinguished according to the number of transmit and receive antennas. In particular, the proposed method obtains accurate channel estimation and fast convergence with insensitivity to overestimates of the true channel order. If virtual carriers (VCs) are available, the proposed method can work with no or insufficient cyclic prefix (CP), thereby potentially increasing channel utilization. Furthermore, it is shown under specific system conditions that the proposed method can be applied to MIMO-OFDM systems without CPs, regardless of the presence of VCs, and obtains an accurate channel estimate with a small number of OFDM symbols. Thus, this method improves the transmission bandwidth efficiency. Simulation results illustrate the mean-square error performance of the proposed method via numerical experiments. </para>

Blind OFDM Channel Estimation Using FIR Constraints: Reduced Complexity and Identifiability

In this correspondence, blind channel estimators exploiting finite alphabet constraints are discussed for orthogonal frequency-division multiplexing (OFDM) systems. Considering the channel and data jointly, a joint maximum-likelihood (JML) algorithm is described, along with identifiability conditions in the noise-free case. This approach enables development of general identifiability conditions for the minimum-distance (MD) finite alphabet blind algorithm of Zhou and Giannakis. Both the JML and MD algorithms suffer from high numerical complexity, as they rely on exhaustive search methods to resolve a large number of ambiguities. We present a substantially more efficient blind algorithm, the reduced complexity minimum distance (RMD) algorithm, by exploiting properties of the assumed finite-length impulse response (FIR) channel. The RMD algorithm exploits constraints on the unwrapped phase of FIR systems and results in significant reductions in numerical complexity over existing methods. In many cases, the RMD approach is able to completely eliminate the exhaustive search of the JML and MD approaches, while providing channel estimates of the same quality

Blind Equalization with Generalized Inverse Channel Estimation and Fractional Phase MLSE Metrics for Mobile Communications

This paper proposes a new blind adaptive MLSE equalizer for frequency selective mobile radio channels. The proposed equalizer performs channel estimation for each survivor path of the Viterbi algorithm (VA), and restricts the number of symbol candidates for the channel estimation in order to reduce prohibitive complexity. In such channel estimation, autocorrelation matrices of the symbol candidates are likely to become singular, which increases the estimation error. To cope with the singularity, the proposed equalizer employs a recursive channel estimation algorithm using the Moore-Penrose generalized inverse of the autocorrelation matrix. As another problem, the blind channel estimation can yield plural optimal estimates of a channel impulse response, and the ambiguity of the estimates degrades the BER performance. To avoid this ambiguity, the proposed equalizer is enhanced so that it can take advantage of the fractional sampling. The enhanced equalizer performs symbol-spaced channel estimation for each fractional sampling phase. This equalizer combines separate channel estimation errors, and provides the sum to the VA processor as the branch metric, which tremendously reduces the probability that a correct estimate turns into a false one. Computer simulation demonstrates the effectiveness of the proposed equalizers in the frequency selective fading channels.

Nonredundant Precoding-Assisted Blind Channel Estimation for Single-Carrier Space–Time Block-Coded Transmission With Frequency-Domain Equalization

Relying on nonredundant diagonal precoding and independent and identically distributed (i.i.d.) source assumption, this paper proposes a blind channel estimation scheme for single-carrier frequency-domain equalization-based space-time block coded systems. The proposed method exploits the precoding-induced linear signal structure in the conjugate cross correlation between the two temporal block received signals as well as the circulant channel matrix property and can yield exact solutions whenever the channel noise is circularly Gaussian and the receive data statistic is perfectly obtained. The channel estimation formulation builds on rearranging the set of linear equations relating the entries of conjugate cross-correlation matrix and products of channel impulse responses into one with a distinctive block-circulant with circulant-block (BCCB) structure. This allows a simple identifiability condition depending on precoder parameters alone and also provides a natural yet effective optimal precoder design framework for improving solution accuracy when imperfect data estimation occurs. We consider two models of data mismatch, from both deterministic and statistical points of view, and propose the associated design criteria. The optimization problems are formulated to take advantage of the BCCB system matrix property and are solved analytically. The proposed optimal precoder aims to optimize solution robustness against deterministic error perturbation and also minimize the mean-square error when the data mismatch is modeled as a white noise. Pairwise error probability analysis is conducted for investigating the equalization performance. Numerical examples are used to illustrate the performance of the proposed method

Supervised Phase Correction of Blind Space–Time DS-CDMA Channel Estimates

Blind channel-estimation algorithms return phase-ambiguous estimates. From a receiver design point of view, the phase-ambiguity problem can be by-passed by differential modulation and detection at the expense of a well-known performance loss, in comparison with direct modulation and coherent detection schemes. An alternative approach is followed in this paper. A theoretical minimum mean-square error phase-estimation criterion leads to a supervised phase-recovery procedure that directly corrects the phase of arbitrary linear filter receivers through a simple closed-form projection operation. Conveniently, any known blind channel-estimation algorithm can be used to provide the initial phase-ambiguous estimate. The presentation is given in the context of adaptive space-time receiver designs for binary phase-shift keying direct-sequence code-division-multiple-access antenna array systems. Numerical and simulation studies support the theoretical developments and show that effective phase correction and multiple-access interference suppression can be achieved with about 2% pilot signaling

Blind acquisition of short burst with per-survivor processing

In this letter, the blind acquisition performance of PSP is discussed. Based on the theory of indistinguishable sequences (K.M. Chugg, 1998), modifications to conventional PSP are suggested that improve acquisition performance significantly. The effects of tree search and list-based algorithms on PSP are also discussed. In blind channel estimation, the performance of list-based algorithms is better than trellis-based algorithms and can be further enhanced using the proposed techniques. The blind acquisition techniques described here can be used for other applications like multi-user detection or space-time trellis codes

Blind channel estimation, equalisation and CRB for OFDM with unmodelled interference

A blind channel estimation and equalisation scheme is given for orthogonal frequency-division multiplexing systems with unmodelled interference. The approach uses a generalised multichannel minimum variance principle to design an equalising filterbank that preserves the desired signal components and suppresses the overall interference. A channel estimate is then obtained by deriving an asymptotically tight lower bound of the filterbank output power, which reduces the problem to a quadratic minimisation. By imposing a special structure on the received signal, the performance is shown to be significantly increased. To assess the performance of the proposed scheme, an unconditional Cramer–Rao bound (CRB) is derived which, similar to the proposed blind channel estimator, does not assume knowledge of the transmitted information symbols. The CRB serves as a lower bound for all unbiased blind channel estimation schemes. Numerical examples show that the proposed scheme approaches the CRB as the SNR increases. It also exhibits low sensitivity to unknown narrowband interference and compares favourably with a subspace blind channel estimator.

A proposal of blind equalizer using kurtosis and skewness

In a transmission system, the conventional adaptive blind equalizers are implemented a direct estimation for the parameters of the equalizers. But both convergence rate of these algorithms and reliability of the regenerated signals degrade down. In this paper, we propose a new equalization system and a new adaptive algorithm using the blind channel estimation for improving these two faults above. In the proposed method, first, we provide a psudo-channel and input signals to the psudo-channel in received part, and characteristics of the channel are adaptivly estimated using simplified kurtosis, skewness of output signals of the channel and the psudo-channel. Secondly, we design the equalizer using an adaptive orthogonal projection algorithm for the estimated channel impulse response matrix. We confirm that convergence rate of the proposed algorithm and reliability of the regenrated signals are better than those of the conventional adaptive blind algorithm by numerical example.

Blind Channel Estimation for MIMO OFDM Systems via Nonredundant Linear Precoding

Based on the assumption that the transmitted symbols are independent and identically distributed (i.i.d.), we develop a simple subspace-based blind channel estimation technique for orthogonal frequency-division multiplexing (OFDM) systems by utilizing nonredundant linear block precoding. A novel contribution is that the proposed method can be applied for scenarios, where the number of receive antennas is less than the number of transmit antennas, e.g., multiple-input single-output (MISO) transmissions, in which case the traditional subspace-based methods could not be applied. Further consideration that can eliminate the multidimensional ambiguity in channel estimation under multiple transmitter scenarios is also proposed. The numerical results clearly show the effectiveness of our proposed algorithm

Cramer-Rao Lower Bounds for Semi-Blind ML Channel Estimation in UWB Systems

This paper derives a unified representation of the Cramer-Rao lower bounds (CRLBs) for semi-blind maximum-likelihood (ML) channel estimation in time-hopping (TH) ultra-wideband systems with pulse amplitude and position modulation, pulse amplitude modulation and pulse position modulation (PPM). These bounds subsume the existing results for both pilot-based and blind ML channel estimation in TH-PPM as special cases. A numerical example is used to illustrate the effects of different data modulation formats and system parameters on the CRLBs derived

IMM-based Kalman filter for channel estimation in UWB OFDM systems

Ultra-wide band (UWB) communication is one of the most promising technologies for high-data rate wireless networks for short-range applications. This paper proposes a blind channel estimation method namely Interactive Multiple Model (IMM)-based Kalman algorithm for UWB OFDM systems. IMM-based Kalman filter is proposed to estimate frequency selective time-varying channel. In the proposed method, two Kalman filters are concurrently estimating channel parameters. The first Kalman filter, namely the Static Model Filter (SMF) gives an accurate result when the user is static while the second Kalman filter namely the Dynamic Model Filter (DMF) gives an accurate result when the receiver is in moving state. The static transition matrix in SMF is assumed as an Identity matrix where as in DMF, it is computed using Yule–Walker equations. The resultant filter estimate is computed as a weighted sum of individual filter estimates. The proposed method is compared with other existing channel estimation methods.

Pilot-Assisted and Blind Joint Data Detection and Channel Estimation in Partial-Time Jamming

We consider a communication scenario in which a message is received in the presence of partial-time Gaussian jamming and additive white Gaussian noise. We consider a quasi-static channel, in which the amplitude and phase are constant over each packet transmission. The receiver does not know the amplitude and phase of the incoming signal, which symbols are jammed, or even the statistics of the jammer, such as the jamming power and jamming probability. In this scenario, the receiver must accurately estimate the parameters of the channel and the jamming to achieve good performance. We apply the expectation-maximization (EM) algorithm to iteratively approximate the maximum-likelihood (ML) estimator for all of the parameters. We find that the overall performance of the EM algorithm is very sensitive to the initial estimates, so we propose a new initial estimator that offers good performance. The EM algorithm approach requires pilot symbols to resolve a phase ambiguity. Thus, we also present a blind estimation algorithm to avoid the reduction in overall code rate from the use of pilot symbols

Blind Estimation of the Ocean Acoustic Channel by Time&amp;ndash;Frequency Processing

A blind estimator of the ocean acoustic channel impulse response envelope is presented. The signal model is characterized by a deterministic multipath channel excited by a highly nonstationary deterministic source signal. The time-frequency (TF) representation of the received signal allows for the separation between the channel and the source signal. The proposed estimator proceeds in two steps: First, the unstable initial arrivals allow for the estimation of the source signal instantaneous frequency (IF) by maximization of the radially Gaussian kernel distribution; then, the Wigner-Ville distribution (WV) is sequentially windowed and integrated, where the window is defined by the previously estimated IF. The integral gives the channel impulse response envelope, which turns to be an approximation to the blind conventional matched filter (MF). The blind channel estimator (CE) is applicable upon the following conditions: that the multipath channel contains at least one dominant arrival well separated from the others, and that the IF of the source signal is a one-to-one function. Results obtained on real data from the INternal TIde Measurements with Acoustic Tomography Experiments (INTIMATE'96), where the acoustic channel was driven by an linear frequency modulation signal, show that the channel's envelope detailed structure could be accurately and consistently recovered, with the correlation of the estimates ranging from 0.796 to 0.973, as compared to the MF result

Blind adaptive channel estimation in ofdm systems

We consider the problem of blind channel estimation in zero padding OFDM systems, and propose blind adaptive algorithms in order to identify the impulse response of the multipath channel. In particular, we develop RLS and LMS schemes that exhibit rapid convergence combined with low computational complexity and numerical stability. Both versions are obtained by properly modifying the orthogonal iteration method used in numerical analysis for the computation of singular vectors. With a number of simulation experiments we demonstrate the satisfactory performance of our adaptive schemes under diverse signaling conditions

Blind channel estimation and detection for space–time coded CDMA in ISI channels

In order to accommodate high data-rate applications, there is a significant interest in extending space-time (ST) coding, originally proposed for frequency-nonselective channels assumed known to the receiver, to unknown ISI (inter-symbol interference) channels. In this paper, we consider the problem of blind channel identification and linear multiuser receiver design for ST-coded CDMA (code-division multiple-access) systems operating in frequency-selective fading channels. We investigate the identifiability conditions and present a subspace-based blind channel estimator for such systems. To assess the performance of the proposed and other potential estimators, we derive an unconditional Cramer-Rao bound (CRB) which, similarly to the proposed blind channel estimator, does not assume the knowledge of the transmitted information symbols. We discuss various linear multiuser detection schemes that can be used in conjunction with the proposed channel estimator for symbol demodulation in ST-coded CDMA systems. Numerical examples are presented to illustrate the performance of the proposed channel estimator and linear detectors in multipath Rayleigh fading channels.