Blind Channel Estimation Research Articles

Blind-Channel Estimation for MIMO Systems With Structured Transmit Delay Scheme

This paper considers blind-channel estimation for multiple-input multiple-output (MIMO) systems with structured transmitter design. First, a structured transmit delay (STD) scheme is proposed for MIMO systems. Unlike existing transmit diversity approaches, in which different antennas transmit delayed, zero padded, or time-reversed versions of the same signal, in the proposed scheme, each antenna transmits an independent data stream, therefore promises higher data rate and more flexibility to transmitter design. Second, second-order statistics based blind-channel estimation algorithms are developed for MIMO systems with STD scheme. Channel identifiability is addressed for both correlation-based and subspace-based approaches. The proposed approaches involve no pre-equalization, have no limitations on channel zero locations, and do not rely on nonconstant modulus precoding. Third, when channel coding is employed, estimation accuracy can be further enhanced through ldquopostprocessingrdquo, in which channel estimation is refined by taking the tentative decisions from the channel decoder as pseudo-training symbols. Simulation examples are provided to demonstrate the robustness and effectiveness of the proposed approaches.

Novel Automatic Modulation Classification Using Cumulant Features for Communications via Multipath Channels

Nowadays, automatic modulation classification (AMC) plays an important role in both cooperative and non-cooperative communication applications. Very often, multipath fading channels result in the severe AMC performance degradation or induce large classification errors. The negative impacts of multipath fading channels on AMC have been discussed in the existing literature but no solution has ever been proposed so far to the best of our knowledge. In this paper, we propose a new robust AMC algorithm, which applies higher-order statistics (HOS) in a generic framework for blind channel estimation and pattern recognition. We also derive the Cramer-Rao lower bound for the fourth-order cumulant estimator when the AMC candidates are BPSK and QPSK over the additive white Gaussian noise channel, and it is a nearly minimum-variance estimator leading to robust AMC features in a wide variety of signal-to-noise ratios. The advantage of our new algorithm is that, by carefully designing the essential features needed for AMC, we do not really have to acquire the complete channel information and therefore it can be feasible without any a priori information in practice. The Monte Carlo simulation results show that our new AMC algorithm can achieve the much better classification accuracy than the existing AMC techniques.

Blind channel and symbol joint estimation in cooperative MIMO for wireless sensor network

In this paper, application of Sequential Quasi Monte Carlo (SQMC) to blind channel and symbol joint estimation in cooperative Multiple-Input Multiple-Output (MIMO) system is proposed, which does not need to transmit training symbol and can save the power and channel bandwidth. Additionally, an improved version of SQMC algorithm by taking advantage of current received signal is discussed. Simulation results show that the SQMC method outperforms the Sequential Monte Carlo (SMC) methods, and the incorporation of current received signal improves the performance of the SQMC obviously.

Non-Redundant Precoding-Based Blind and Semi-Blind Channel Estimation for MIMO Block Transmission With a Cyclic Prefix

By combining multiple-input-multiple-output (MIMO) communication with block transmission using a cyclic prefix (CP), MIMO block transmission systems can not only achieve high data rates but also simplify channel estimation and equalization. In this paper, to provide a bandwidth-efficient solution for channel estimation in MIMO block transmission systems with a CP, we present a framework for blind channel estimation based on a general non-redundant precoding. Using this framework, we propose a blind estimator exploiting a simplified non-redundant precoding that is robust against overestimates of a true MIMO channel order. Furthermore, in the case with the number of transmit antennas greater than that of receive antennas, we show under specific system conditions that the proposed blind algorithms can be used for estimation of the MIMO channel without oversampling the received signals. With the simplified precoding conditions established in this paper, the proposed method does not impose the strict identifiability conditions on the MIMO channel, which are required for the existing methods. Furthermore the proposed estimator achieves accurate channel estimation with a small number of symbol blocks. In addition, we derive a simplified precoder that is optimized in the sense of minimizing the impact of unknown additive noise. We discuss the tradeoff between channel estimation accuracy and bit error rate performance associated with the simplified precoder. Finally, we develop a technique for resolving the channel ambiguity in the proposed blind estimator to create a semi-blind channel estimator relying on only a few known symbols.

Comments on "Performance Analysis of a Deterministic Channel Estimator for Block Transmission Systems With Null Guard Intervals

In the above-mentioned paper, a Cramer-Rao bound was derived for the performance of a blind channel estimation algorithm. In this correspondence, an error in the bound is pointed out and corrected. It is observed here that the performance of the said algorithm does not achieve the Cramer-Rao bound.

Blind channel estimation for multiple input multiple output uplink guard-band assisted code division multiple access systems with layered space frequency equalisation

Single carrier (SC) code division multiple access (CDMA) with block transmission has been shown to be more effective while utilising a low-complexity equaliser to combat frequency-selective fading channels, when compared with conventional direct sequence CDMA technology. It also has lower peak-to-average power ratio and lower frequency sensitivity compared with multicarrier CDMA. The authors propose two blind channel estimation methods for uplink multiple input multiple output SC-CDMA systems with block transmisssion-one is the subspace-based method and the other is the so-called autocorrelation contribution method (ACM). Both the methods provide close performance to the case with perfect channel knowledge at high signal-to-noise ratio (SNR) without any training data required. It is shown that ACM yields a better performance than the subspace method at a lower SNR, and a similar performance at a high SNR, with the advantages of avoiding rank determination and noise power estimation as in the subspace method. In addition, the authors integrate layered space frequency equalisation with blind channel estimation, which provides improved performance over the conventional linear equalisation, by employing successive interference cancellation.

Two Blind Adaptive Mobile Receivers in Time-Hopping PAM UWB Impulse Radio System

This paper deals with the design of blind mobile station (MS) receiver for time-hopping (TH) ultrawide-band (UWB) impulse radio (IR) system employing antipodal pulse amplitude modulation (PAM). In the presence of multipath fading channel, batch-mode minimum output energy (MOE) receiver, as well as a blind channel estimator, is first developed. To reduce the computational complexity, we propose two blind adaptive algorithms to determine the weight vector of the MS receiver. The rational of the algorithms premises on iteratively maximizing the minimum possible receiver's output energy. The first (indirect) approach is derived by first developing an adaptive blind channel estimator, then the updated channel impulse response (IR) is used to calculate the MS receiver's weight vector. Meanwhile the second (direct) method jointly and iteratively optimizes the weight vector and channel IR to improve system performance. Simulation results demonstrate convergence of both algorithms.Moreover, the algorithms are shown to be robust to multiuser interference (MUI) and near-far problems.

Performance of blind channel estimation algorithms for space-frequency block coded multi-carrier code division multiple access systems

The problem of blind channel estimation for downlink space-frequency block coded multi-carrier code division multiple access (SFBC MC-CDMA) schemes is considered. For these schemes, the authors first develop a system model for complex modulated signals, which reduces the multichannel estimation problem to a single-input single-output problem. Then, they present an intuitive subspace-based channel estimation method along with the corresponding necessary and sufficient conditions under which the channel estimate is unique (within a complex scalar). Their studies highlight two interesting properties of SFBC MC-CDMA systems: (i) there is no antenna order ambiguity (also known as permutation ambiguity) even though only one spreading code is assigned to each user; (ii) channel identifiability is guaranteed, regardless of the channel zeros location. They also establish the unbiasedness of the channel estimates and derive closed-form expressions for the mean-square-error of the estimates as well as the corresponding Cramer-Rao bound (CRB). In the derivation of the CRB, they suggest a novel approach which assumes the knowledge of only the spreading code of desired user. This approach results in a tighter bound than the CRB derived based on the knowledge of all users' signatures.

Resolving Multidimensional Ambiguity in Blind Channel Estimation of MIMO-FIR Systems via Block Precoding

In this paper, we consider the identification problem of multiinput-multioutput (MIMO) finite-impulse-response systems via second-order statistics only. By assigning different block precoders to different transmitters, we develop a new technique that allows blind MIMO channel identification up to a scalar ambiguity for each transmitter. We provide sufficient conditions for removal of the matrix ambiguity for a specific set of precoding matrices and derive a general theorem for other kinds of precoding matrices based on a reasonable conjecture. This theorem is firmly tested via numerical examples. Two potential precoding schemes are proposed, considering different ways of eliminating interblock interference. Finally, numerical results are provided to verify our analysis.

Robust subspace blind channel estimation for cyclic prefixed MIMO ODFM systems: algorithm, identifiability and performance analysis

A novel subspace (SS) based blind channel estimation method for multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this work. With an appropriate re-modulation on the received signal blocks, the SS method can be effectively applied to the cyclic prefix (CP) based MIMO-OFDM system when the number of the receive antennas is no less than the number of transmit antennas. These features show great compatibility with the coming fourth generation (4G) wireless communication standards as well as most existing single-input single-output (SISO) OFDM standards, thus allow the proposed algorithm to be conveniently integrated into practical applications. Compared with the traditional SS method, the proposed algorithm exhibits many advantages such as robustness to channel order over-estimation, capability of guaranteeing the channel identifiability etc. Analytical expressions for the mean-square error (MSE) and the approximated Cramer-Rao bound (ACRB) of the proposed algorithm are derived in closed forms. Various numerical examples are conducted to corroborate the proposed studies.

Blind channel estimation for redundant precoded OFDM systems

Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal frequency-division multiplexing (OFDM) systems. A redundant linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Because of the introduced structure, the frequency-selective channel can be identified at the receiver based on autocorrelation operations, singular value decomposition (SVD), and by resolving the scalar ambiguity. The proposed channel estimation method has low computational complexity and requires no prior statistical information on channel or noise. And the proposed blind method has high spectral efficiency owing to exploiting no training sequence. Computer simulations confirm that this proposed blind channel estimation method can identify the frequency-selective channels perfectly and obtain a good performance.

FFT/IFFT Based Blind SIMO Channel Identification

This paper presents an FFT/IFFT based blind identification method for estimating the finite impulse response of single-input multiple-output channels driven by an unknown deterministic signal. The proposed algorithm successfully handles a very small size of received data, for which the existing blind channel estimation methods, including the subspace, cross-relation and shifted correlation algorithms, are known to be ineffective. Moreover, with no assumption of the precise knowledge of channel order, the proposed algorithm is capable of estimating channel parameters as well as detecting channel order. Simulations show that the proposed algorithm outper forms the existing methods in small sample size situations.

Performance Analysis of Generalized Zero-Padded Blind Channel Estimation Algorithms

In this letter, we analyze the performance of a recently reported generalized blind channel estimation algorithm. The algorithm has a parameter called repetition index, and it reduces to two previously reported special cases when the repetition index is chosen as unity and as the size of received blocks, respectively. The theoretical performance of the generalized algorithm is derived in high-SNR region for any given repetition index. A recently derived Cramer-Rao bound (CRB) is reviewed and used as a benchmark for the performance of the generalized algorithm. Both theory and simulation results suggest that the performance of the generalized algorithm is usually closer to the CRB when the repetition index is larger, but the performance does not achieve the CRB for any repetition index.

Deterministic Blind Channel Estimation for a Block Transmission System Using Fractional Sampling and Interpolation

This paper introduces a blind channel estimation method for a block transmission system using fractional sampling at a receiver. In most digital communication systems, low-pass filters are placed at a transmitter to confine the transmitting waveform to an allocated bandwidth and at a receiver to improve the signal-to-noise (SNR) power ratio. Consequently, if the received waveform is sampled with sufficiently fast rate, the resulting discrete-time signal is band-limited and exhibits a smooth waveform. The method exploits this property for estimating the channel impulse response, via an interpolation formula. The method does not require knowledge of input statistics or the autocorrelation of the received signal. It is free of channel order estimation and thus robust against its overestimation. Moreover, the algorithm is quite efficient because it does not need to compute eigenvalues of a matrix.

Blind Channel Estimation for Cyclic-Prefixed Single-Carrier Systems by Exploiting Real Symbol Characteristics

In this paper, we consider blind channel estimation for cyclic-prefixed single-carrier (CP-SC) systems via second-order statistics only. By exploiting the existence of real symbols in the transmitted data block, we develop a simple technique for blind channel estimation that does not need redundant precoding or virtual carriers. Hence, the proposed algorithm provides bandwidth efficiency. A side benefit of the proposed algorithm is that the phase ambiguity, which is an inherent problem in traditional blind channel estimation, is reduced to sign ambiguity only. This side benefit facilitates signal detection in digital communications where symbols are usually taken from a finite alphabet. Although the proposed method is mainly developed for channel estimation in single-input-single-output CP-SC systems, it can also be applied straightforwardly to single-input-multiple-output systems (either with CP-SC or other kinds) and multiple-input-multiple-output systems whenever real symbols exist or are deliberately inserted in the transmission.

BLIND CHANNEL ESTIMATION FOR LINEARLY PRECODED MIMO-OFDM SYSTEMS

We propose a non-redundant linear precoder for MIMO-OFDM systems that enables blind channel estimation. Due to the structure introduced by the precoding matrix, the channel can be estimated based on general SVD. The identifiability of the proposed algorithm is guaranteed even when the channel matrices share common zeros at subcarrier frequencies. The asymptotic performance of the proposed estimation method is presented. Computer experiments show that the performance of our proposed algorithm compares favorably to the training based LS algorithm.

Channel estimation for chip‐level Alamouti coded multi‐rate CDMA: blind subspace algorithms and performance analysis

AbstractIn this work we consider the problem of blind channel estimation for the downlink of a variable spreading gain (VSG) multi‐rate code‐division‐multiple‐access (MR CDMA) system which uses the orthogonal space‐time block coding (STBC) proposed by Alamouti. In contrast to traditional symbol‐level STBC CDMA systems, we consider a chip‐level ST block coding system for which we derive a simple subspace‐based blind channel estimation method. For the derived algorithm we investigate the necessary and sufficient conditions for the channel to be uniquely identifiable up to a complex multiplicative constant. We also analyse the behaviour of the channel estimation algorithm as a function of the data samples utilised, establishing its unbiasedness and providing a closed‐form expression for the mean‐square‐error (MSE) as well as the Cramer—Rao bound (CRB) for the channel estimation performance. Copyright © 2007 John Wiley & Sons, Ltd.

Blind Channel Estimation for Orthogonal STBC in MISO Systems

This paper presents a closed-form blind channel estimation scheme for orthogonal space-time block codes in multiple-input single-output (MISO) systems, with specific focus on Alamouti's code for two transmit antennas. The channel matrix is estimated from the eigenvalue decomposition of the fourth-order cumulant matrix of the received signal. Unlike previous blind estimation schemes for MISO systems, the proposed algorithm is tested with block and slowly fading channels. The proposed scheme performs very well in both cases. A single pilot tuple is required to correctly assign the estimated to the actual channels and to resolve the sign ambiguity common to all blind estimators. It is shown that this scheme outperforms the only other available blind channel estimation scheme for this scenario. To achieve good performance in terms of bit error rate, 100-300 sample points are sufficient to provide accurate channel estimates. The main disadvantage of the proposed scheme is the complexity associated with the estimation of fourth-order cumulants. This complexity is reduced by exploiting the symmetry inherent in the cumulant matrix.

Blind Channel Estimation for OFDM Systems via a Generalized Precoding

In this paper, we consider the problem of blind channel estimation for single-input-single-output (SISO) orthogonal frequency-division multiplexing (OFDM) system via second-order statistics only. Based on the assumption that the transmitted symbols are independent and identically distributed, we develop a simple blind channel estimation technique for OFDM systems by utilizing a generalized linear nonredundant block precoding. Instead of using partial information from the signal covariance matrix, as done in previous works where a specific precoder is designed and only one column of the signal covariance matrix is exploited, our work jointly considers all the information contained in the signal covariance matrix. Compared to the popular subspace-based blind channel estimation methods, the proposed algorithm is much more computationally efficient. A design criterion of the precoders by which the performance can be improved is provided, and the closed-form stochastic Crameacuter-Rao bound is derived. The numerical results clearly show the effectiveness of our proposed algorithm, as well as its improvement over the existing techniques

A ray-based blind channel estimation method in ocean sound channels. Application to high-frequency underwater telecommunications

A signal that travels through a sound channel is typically distorted when recorded by a remote listener because of interference arising from multiple propagation paths. We developed a ray-based blind channel estimation technique in ocean sound channels, i.e., using only records of the distorted signal along a transducer array. The technique yields broadband estimates of the source-to-array impulse response (or Green’s functions) synthesized directly from the recorded distorted signals. The technique relies on separating out the contribution of a propagating ray path having a phase that depends linearly on frequency. This technique was used to decode high-frequency underwater telecommunications sequences collected in 2005 off the West Coast of Italy, without any a priori knowledge of the channel impulse response. [Work supported by ONR.]