Blind Channel Estimation Technique Research Articles

Precoding Aided Data Correlation Scheme for Channel Estimation Technique in MIMO-OFDM System

Channel estimation is considered as an important phase in Multiple Input Multiple Output – Orthogonal Frequency Division Multiplexing (MIMO-OFDM) networks which can enhances the performance significantly. Channel estimation widely classified as pilot based, blind and semi-blind channel estimation. The pilot-based channel estimation decreases the data transmission rate and spectral efficiency. To overcome these issues of existing schemes, we present a novel blind channel estimation technique. According to proposed scheme, we transmit the data in a block-wise manner. The proposed scheme uses precoding technique to establish the correlation between these blocks. Further, we use channel correlation to solve the diagonal uncertainty of correlation matrix which helps to improve the system performance. We present a comparative analysis study which shows that proposed approach can achieve better performance in terms of Normalized Mean Square Error (NMSE) and Mean Square Error (MSE) when compared with existing techniques.

A Novel Adaptive Optimized Fast Blind Channel Estimation for Cyclic Prefix Assisted Space–Time Block Coded MIMO-OFDM Systems

In this paper an adaptive optimized fast blind channel estimation using cyclic prefix supported with Space Time Block Coded Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (STBC-MIMO-OFDM) system is presented. The main aspire of our technique is to support multiple users at the same time over same frequency band based on the Multi-Carrier Code-Division Multiple Access (MC-CDMA) approach. High complexity and low convergence is the main obstacle in earlier blind channel estimation techniques. Modified flower pollination algorithm is implemented to overcome this problem. The MC-CDMA approach is utilized to implement the blind channel estimation. The proposed MC-CDMA is used to reduce the error rate included in the Blind Channel Estimation. As a part of wireless communications, time block coding technique is utilized to transmit several copies of information across the number of antennas. To develop the consistency of data transfer different received data is used and then MFPA results in lower fuel cost compared to FPA. MFPA produces better results compared with previous methods.

Performance Evaluation of Different Channel Estimation Techniques Using OFDM System on Large and Small Scale Fading Channel Model

The development of internet related applications and their increasing demands have led to advancement in high speed communication systems. For the accomplishment of these increasing demands MIMO channels with multiple transmitting and receiving antennas have been devised. MIMO systems enhance the capacity using spatial multiplexing and interference reduction through spatial dimensioning. Furthermore, MIMO systems mutual with orthogonal frequency division multiplexing (MIMO-OFDM) improves system capacity and mitigation against fading. These systems are the basis of 4G and beyond wireless communication standards. This research work focus on improvement in channel estimation performance using various techniques on standard communication models. Semi blind channel estimation technique is employed for channel estimation, which includes use of training sequence in form of pilots. Block type arrangement is being used, since it’s based on frequency selective channels. LSE and MMSE estimations are the two basic estimation techniques which can be efficiently used to estimate channels in OFDM systems. For MMSE implementation information of noise variance and channel covariance is required. Furthermore it is extremely complex than LSE estimator. DFT and DCT based channel estimation methods are employed to increase the performance and diminish the complexity. Different interpolation methods are been used and analyzed for better performance. Number of subcarriers which also have an impact on estimation performance has also been discussed. Overall channel estimation performance have been examined for both large and small scale fading channel models.

One-Shot Blind Channel Estimation for OFDM Systems Over Frequency-Selective Fading Channels

This paper presents a blind channel estimation (BCE) technique for orthogonal frequency division multiplexing communications systems. The proposed system is based on modulating particular pairs of subcarriers using amplitude shift keying and phase shift keying, which enables the realization of a decision-directed one-shot BCE (OSBCE), with complexity and accuracy that are comparable to pilot-based channel estimation techniques. The performance of the proposed estimator is evaluated in terms of the mean squared error (MSE), where an accurate analytical expression is derived and verified using Monte Carlo simulation under various channel conditions. The obtained results show that the MSE of the proposed OSBCE is comparable to pilot-based estimators, which confirms the efficiency of the proposed OSBCE.

Optimised periodic precoder-based blind channel estimation for MIMO-OFDM systems

ABSTRACTIn modern wireless communication systems, multiple antennas at transmitter and receiver are employed along with orthogonal frequency-division multiplexing to achieve very high data rate with significant system reliability. To further enhance system performance, blind channel estimation techniques are employed whenever data symbols are transmitted in blocks. These estimation techniques are computationally expensive at almost all signal-to-noise ratio values. In this paper, periodic precoder-based blind channel estimation is used to tackle problems like complexity, channel order overestimation and bandwidth expansion. The system reliability can be improved, if precoder coefficients are chosen in such a way that they have no dependency or minimum correlation with noise coefficients. The overall bit error rate (BER) is derived and simulated with dependency on periodic sequence and channel estimation error. The simulation results shows that the presented precoding scheme performs better in terms of BER with minimum channel estimation error as compared to other state-of-the-art schemes.

A Robust Hybrid NDA Estimation Technique for SNR Estimation in OFDM System

Channel Estimation techniques play a very crucial role in characterizing the effect of the physical medium on the input sequence. Orthogonal Frequency division multiplexing (OFDM) Systems are especially suited for channel estimation. In this paper we have proposed a novel robust blind channel estimation technique. This technique is developed on the basis of the Envelope Based Estimator. A hybrid approach based on EM and simpler moments-based techniques is adopted. Modified moments based estimator is designed for this proposed work. In the adopted hybrid approach the SNR is estimated by the moments based estimators up to a certain threshold point, ρ0. EM estimator is used to estimate SNR greater than ρ0. Since the Phase Noise is a time varying process which changes the symbol from time to time and has a high deteriorating effect on higher order OFDM system. We have derived a Bayesian Cram´er- Rao Lower Bound Estimator for estimating phase noise.

An investigation into performance of MIMO wireless communication system under semi-blind channel estimation

A new approach to Semi–Blind Channel Estimation (SBCE) technique for Multiple Input Multiple Output (MIMO) wireless communication system is proposed in this paper. It combines the least squares (LS) and Minimum Mean Square Error (MMSE) Training–Based Channel Estimation (TBCE) scheme with whitening rotation–based SBCE scheme. In this approach, the singular value decomposition has to be applied only once, thereby reducing the computational complexity. The channel correlation matrix required by MMSE technique can be obtained based on latest channel conditions. The performance of this scheme is compared with whitening rotation–based SBCE under various parameters such as modulation schemes, Signal–to–Noise Ratio (SNR) and frame length. The performance of the new approach is found to be better in terms of Bit Error Rate (BER) for high SNR, higher modulation order and smaller frame lengths. With low SNR, lower modulation order and larger frame lengths, there is negligible reduction in performance.

Blind channel estimation for equalisation in dispersive fading channel

A new blind channel estimation technique is presented for non-linear/linear equalisation in a frequency-selective Rayleigh fading channel. At each symbol interval, a decision algorithm first makes a primary data estimate based on constrained linear minimum mean square error criterion, and then this is applied to subsequent channel estimation. Channel estimates are obtained in the form of two alternative, related methods: directly from the Wiener solution or Kalman-based recursion. The former performs better but requires more values from the normalised time-correlation function. The performance is evaluated by simulation, allowing fair comparison with the benchmark of equalised coherent detection; optimal uncoded orthogonal frequency division multiplexing with perfect channel state information at the receiver; the conventional decision-directed Kalman filtering which employs channel tracking with delay; and for the special case of flat fading, an optimised, pilot symbol-assisted modulation system.

OFDM With Iterative Blind Channel Estimation

A new blind channel estimation technique is presented for uncoded orthogonal frequency-division multiplexing (OFDM) systems. Instead of using pilots to sound the channel, a decision algorithm first makes primary estimates of the data symbol for each subcarrier based on a constrained linear minimum mean square error (MMSE) criterion. Then, these estimates are applied to optimal MMSE channel estimation. The technique requires only one value from the time–frequency correlation of the channel transfer function. Performance is evaluated by simulation so that comparison can be made with known optimal coherent/differential detection. Compared with known decision-directed Kalman-based estimation and two pilot-aided OFDM schemes (block pilots and comb pilots), the presented technique performs better for regions with mid to high signal-to-noise ratios (SNRs). Its robustness to the time variation of the channel is also quantified by simulation, showing only small degradation in performance relative to the quasistatic case of wireless local area network (WLAN) systems. Finally, the impact of covariance assumptions in the channel modeling is quantified using simulation, offering a feel for the performance with mismatch between the channel model and the receiver assumptions.

Coding-Assisted Blind MIMO Separation and Decoding

Despite the widespread use of forward-error correcting (FEC) coding, most multiple-input-multiple-output (MIMO) blind channel-estimation techniques ignore its presence and instead make the simplifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In this paper, we exploit the iterative channel estimation based on a posteriori information for blind MIMO separation and decoding. Experiments show improvements that are achievable by exploiting the existence of coding structures and that our technique can approach the performance of a Bahl-Cocke-Jelinek-Raviv (BCJR) equalizer with perfect channel-state information in a reasonable signal-to-noise ratio (SNR) range. In addition, by splitting the FEC codeword over multiple blocks, the impact in performance of a bad-conditioned channel matrix can be kept at a reasonable level.

Generalized Correlation Decomposition-Based Blind Channel Estimation in DS-CDMA Systems With Unknown Wide-Sense Stationary Noise

A new blind subspace-based channel estimation technique is proposed for direct-sequence code-division multiple access (DS-CDMA) systems operating in the presence of unknown wide-sense stationary noise. Unlike most of the blind techniques developed for unknown correlated noise environments so far, the proposed algorithm is applicable to an arbitrary symbol constellation and does not require any auxiliary antennas at the receiver or any prior knowledge of the interfering user spreading codes. Our approach exploits the centro-Hermitian property of the unknown noise covariance matrix and makes use of the generalized correlation decomposition (GCD) to obtain an accurate estimate of the noise subspace and, consequently, of the user-of- interest channel vector. We also obtain optimal values of the GCD weighting matrices which maximally preserve the orthogonality of the estimated noise subspace to the actual signal subspace in the high signal-to-noise ratio (SNR) regime. It is shown that such an optimal choice of the weighting matrices transforms GCD to an extended form of the conventional canonical correlation decomposition (CCD). Simulation results further demonstrate that if such an extended CCD-based approach is used to estimate the user-of-interest channel vector, then the estimation performance can be substantially improved as compared to earlier SVD-based blind channel estimation techniques.

Blind channel identification in Alamouti coded systems: a comparative study of eigendecomposition methods in indoor transmissions at 2.4 GHz

AbstractThis paper focuses on blind channel estimation in Alamouti coded systems with one receiving antenna working in indoor scenarios where the flat fading assumption is reasonable. A comparative study of several channel estimation techniques in both simulated and realistic scenarios is presented. The tested methods exploit the orthogonality property of the Alamouti coded channel matrix, and are based on the eigendecomposition of a square matrix made up of second‐order statistics (SOS) or higher order statistics (HOS) of the observed signals. An experimental evaluation is carried out on a testbed developed at the University of A Coruña (UDC) and operating at 2.4 GHz. The results show the superior performance of the SOS‐based blind channel estimation technique in both line of sight (LOS) and non‐LOS (NLOS) channels. Copyright © 2008 John Wiley & Sons, Ltd.

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.]

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

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 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

Adaptive rate coding using convolutional codes for asynchronous code division multiple access communications over slowly fading channels

This paper presents a method of code rate adaptation using punctured convolutional codes for direct sequence spread spectrum communication systems over slowly fading channels. A blind channel estimation technique is used to estimate the nature of the multi-user channel at the detector (before the decoder). The path gains obtained from the channel estimation technique are used to adapt the code rates. Punctured codes derived from a specific rate 1/2 ( M = 4) mother code are used to provide error protection corresponding to the actual channel state. The upper and lower bounds on the bit error probability and the upper bound on the error event probability are derived for hard-decision and soft-decision decoding over Rayleigh and Rician fading channels. The throughput gains obtained using the adaptive scheme and the performances of the punctured codes are studied.

Blind Channel Estimation for Space-Time Coded WCDMA

A new blind channel estimation technique is proposed for space-time coded wideband CDMA systems using aperiodic and possibly multirate spreading codes. Using a decorrelating front end, the received signal is projected onto a subspace from which channel parameters can be estimated up to a rotational ambiguity. Exploiting the subspace structure of the WCDMA signaling and the orthogonality of the unitary space-time codes, the proposed algorithm provides a blind channel estimate via least squares. A new identifiability condition is established under the assumption that the system is not heavily loaded. The mean square error of the estimated channel is compared with the Cramér-Rao bound, and the bit error rate (BER) performance of the proposed algorithm is compared with that of differential schemes.

A trellis-based technique for blind channel estimation and equalization

In this paper, we present a trellis-based blind channel estimation and equalization technique coupling two kinds of adaptive Viterbi algorithms. First, the initial blind channel estimation is accomplished by incorporating the list parallel Viterbi algorithm with the least mean square (LMS) updating approach. In this operation, multiple trellis mappings are preserved simultaneously and ranked in terms of path metrics. Equivalently, multiple channel estimates are maintained and updated once a single symbol is received. Second, the best channel estimate from the above operation will be adopted to set up the whole trellis. The conventional adaptive Viterbi algorithm is then applied to detect the signal and further update the channel estimate alternately. A small delay is introduced for the symbol detection and the decision feedback to smooth the noise impact. An automatic switch between the above two operations is also proposed by exploiting the evolution of path metrics and the linear constraint inherent in the trellis mapping. Simulation has shown an overall excellent performance of the proposed scheme in terms of mean square error (MSE) for channel estimation, robustness to the initial channel guess, computational complexity, and channel equalization.

Blind direct DFE estimation using multistep prediction

We propose a blind decision feedback equalizer (DFE) that is characterized by the fact that it does not require channel estimation. Because the output of the optimized multistep prediction error filter (PEF) can be represented as a product of the channel partial impulse response and the transmitted sequence, a backward multistep PEF can be used as the blind DFE feedforward filter. The corresponding feedback filter is obtained from the symbol-rate partial channel impulse response. The proposed algorithm has several advantages over existing blind channel estimation techniques, including stable performance without the necessity of exact channel order estimation.