Blind Channel Estimation Method Research Articles

Blind channel estimation for DCO-OFDM based vehicular visible light communication

Blind channel estimation (CE) methods for OFDM based RF communication provide high-rate transmission by eliminating pilot overhead in conventional pilot-based methods, at the cost of lower accuracy. However, there is no work on the blind CE for OFDM based visible light communication (VLC) systems. In this paper, we propose a novel blind CE method for vehicular VLC with the goal of improving CE accuracy based on the exploitation of the channel statistics derived, by utilizing extensive amount of data collected for different communication angles, distances, and ambient light conditions. First, the normalized channel frequency response (CFR) of the V2LC channel is demonstrated to be invariant of inter-vehicular distance, relative transmitter/receiver zenith angle and ambient light. Then, this channel characteristic is exploited in the blind CE to improve its accuracy with two-step estimation of normalization factor. Extensive simulations at different vehicle speeds show that the proposed method outperforms the pilot-based and superimposed training-based CE methods in terms of spectral efficiency both for all modulation schemes and at all relative speeds. The proposed blind channel estimation (CE) method provides 9.77% increase in the spectral efficiency, compared to the second best method, superimposed training-based CE, at 20 dB signal-to-noise ratio (SNR) and 160 km/h relative speed, for 64-Quadrature Amplitude Modulation (QAM) Direct Current-Biased Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM). Moreover, the real-time performance of the proposed blind CE is demonstrated for a realistic vehicle mobility scenario extracted from SUMO.

Scalar Ambiguity Estimation Based on Maximum Likelihood Criteria for Totally Blind Channel Estimation in Block Transmission Systems

This paper proposes a scalar ambiguity estimation method that sublimates the blind channel estimation method to totally blind estimation. Generally, the blind channel estimation method can identify the channel impulse response or channel frequency response up to scalar ambiguity. For coherent detection, the ambiguity should also be estimated. Exploiting the multiple modulation scheme, we estimate the scalar ambiguity for zero forcing equalization by maximum likelihood (ML). We also detect some equalized symbols fed into the ML estimation, which reduces the computational complexity of the proposed scalar ambiguity estimation. To efficiently reduce the complexity, we derive the Bayesian Cramér Rao lower bound (BCRB) of the ambiguity estimation. When evaluated in computational simulations, the performance of the proposed method achieved the BCRB performance at high signal-to-noise ratios. We also confirmed that when the proposed method is combined with the existing blind channel estimation, coherent detection is possible without any pilot symbols.

Adaptive Blind Channel Estimation for MIMO-OFDM Systems Based on PARAFAC

In order to track the changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is prior to estimate channel impulse response adaptively. In this paper, we proposed an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weight the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of third-order tensor which consists of the weighted OFDM data symbols. To reduce the computational load, we adopt a recursive singular value decomposition method for tensor decomposition; then, the channel parameters can be estimated adaptively. Simulation results validate the effectiveness of the proposed algorithm under diverse signalling conditions.

Joint Adaptive Blind Channel Estimation and Data Detection for MIMO-OFDM Systems

In order to track a changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is a priority to estimate channel impulse response adaptively. In this paper, we propose an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weigh the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of a third-order tensor, which consists of the weighted OFDM data symbols. By preserving the Khatri-Rao product, we used a recursive least squares solution to update the estimated subspace at each time instant, then the channel parameters can be estimated adaptively, and the algorithm achieves superior convergence performance. Simulation results validate the effectiveness of the proposed algorithm.

Application of Maximum Entropy Theorem in Channel Estimation

Scholars have been highly concerned with the blind channel estimation of multi-carrier modulation transmission systems, and the decoding process of block codes is usually closely related to channel parameters. Therefore, the accurate estimation of channel parameters is an important method to ensure communication accuracy. According to the transmission characteristics of multi-carrier modulated transmission channels, this paper uses the maximum likelihood theorem and the maximum entropy theorem to put forward a blind channel estimation method based on the proposed received signals. In order to verify the effect of this method, this research utilizes the BP decoding algorithm, which is used in LDPC coding, to calculate the symbol error rate and analyze the estimated effect of the transmission system. The simulation results show that the proposed method can estimate channel parameters effectively, and that the symbol error rate of LDPC decoding is almost similar to that of non-blind channel estimation. This implies that the proposed channel estimation method can effectively improve both channel utilization and transmission efficiency.

Spectral Efficient Blind Channel Estimation Technique for MIMO-OFDM Communications

<p><em>With emerge of increasing research in the domain of future wireless communications, massive MIMO (multiple inputs multiple outputs) attracted most of researchers interests. Massive MIMO is high-speed wireless communication standards. A channel estimation technology plays the essential role in the MIMO systems. Efficient channel estimation leads to spectral efficient wireless communications. The critics of Inter-Symbol Interference (ISI) are the challenging tasks while designing the channel estimation methods. To mitigate the challenges of ISI, we proposed the novel blind channel estimation method which based on Independent component analysis (ICA) in this paper. Proposed channel estimation it works for both blind interference cancellation and ISI cancellation. The proposed Hybrid ICA (HICA) method depends on pulse shape filtering and ambiguity removal to improve the spectral efficiency and reliability for MIMO communications. The Kurtosis operation is used to measure the complex data at first to estimate the common signals. Then we exploited the advantages of 3rd and 4th order Higher Order Statistics (HOS) to priorities the common signals during the channel estimation. In this paper, we present the detailed design and evaluation of HICA blind channel estimation method. We showed the simulation results of HICA against the state-of-art techniques for channel estimation using BER, MSE, and PAPR.</em><em></em></p>

Blind Channel Estimation for FBMC/OQAM Systems Based on Subspace Approach

The conventional channel estimation schemes for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems are mainly based on preamble methods. However, the utilization of preamble for channel estimation decreases the system’s spectrum efficiency. In this paper, we propose a modified subspace blind channel estimation method for FBMC/OQAM systems. The proposed method distinguishes itself from previously preamble based methods by utilizing spatial diversity technique to introduce data redundancy for blind channel estimation, which leads to high spectral utilization. Thus, the proposed method can provide significant root mean square error (RMSE) performance improvement compared to conventional preamble based methods at high SNRs. Simulation results verify the validity of the proposed method in FBMC/OQAM systems.

Performance Evaluation of Acoustic Model-Based Blind Channel Estimation in Ocean Waveguides

Blind channel estimation (BCE) which does not require the knowledge of the source signals becomes increasingly important in various underwater acoustic applications. Unlike the conventional methods that utilize the statistical properties of the received signals, this paper proposes an acoustic model-based BCE method that exploits the properties of the acoustic propagation and the acoustic environmental information. This method is implemented by localizing the source with a matched-field processing algorithm first, then, uses the physical model of the ocean waveguides to determine the channel impulse response. Its performance is investigated by making comparisons with the mode-based artificial time reversal and the ray-based synthetic time reversal methods, using the array data measured from the SWellEx-96 experiment at four source-array ranges. Cross-correlation coefficient and normalized projection misalignment are adopted to evaluate the performance of the proposed method, and the simulation results for different multipath channels confirm the effectiveness of the proposed method.

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service (DoS) attack, named the ‘primary user emulation attack (PUEA)’, exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response (CIR) between the secondary user (SU) and the signal source is used to determine whether the received signal is transmitted by the primary user (PU) or the primary user emulator (PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.

Passive characterization of underwater sound channel using ray-based blind deconvolution algorithm

Ray-based blind deconvolution (RBD) algorithm is a blind channel estimation method, which can estimate both the channel impulse response and the original signal broadcast from an unknown source. It is based on high-frequency ray assumption and requires only the elementary information of array geometry and sound speed at the array position. Its capability of estimating the channel in a passive manner can be used to infer the sound channel characteristics from a source of opportunity such as passing surface ship whose positioning information is available from geo-referencing systems like the Automatic Identification System. Recently, we applied the RBD algorithm to the shipping noise data recorded on vertical line arrays at multiple locations in shallow water and confirmed its applicability for channel estimation and performing environmental inversion. This presentation shows the channel impulse responses estimated from a variety of source-receiver geometry and discusses the characteristics of sound propagation as well as the environmental property such as bottom loss which can be observed using the RBD algorithm.

Blind Channel Estimation Using Wavelet Denoising of Independent Component Analysis for LTE

<p>A new proposal of blind channel estimation method for long term evoluation (LTE) based on combining advantages of denoising property of wavelet transform (WT) with blind estimation capability of independent component analysis (ICA) called wavelet denoising of ICA (WD-ICA) was presented. This new method increased the spectral efficiency compared to training based methods, and provided considerable performance enhancement over conventional ICA methods. The conventional blind channel estimation methods based on ICA were performed individually for each orthogonal frequency division multiplexing (OFDM) subcarrier. To reduce complexity of implementation of WD-ICA method, channel interpolation was used. This method was presented for multiple-input-multiple-output (MIMO) downlink LTE system. WD-ICA method was compared to conventional ICA methods and the Performance was evaluated by calculating normalized mean square error (NMSE) and bit error rate (BER). WD-ICA method as compared to the other known ICA channel estimation methods has lower complexity, lower value of NMSE, and lower value of BER, which indicates the superiority of the proposed method.</p>

Cumulants‐based modulation classification technique in multipath fading channels

Automatic modulation classification (AMC) is a classical topic in the signal classification field and is often performed when the modulation type is adaptive. For typical modulation types such as M-PSK and M-QAM, the fourth-order cumulant statistics are usually used for modulation classification. Besides, it is also known that the AMC performance can be seriously degraded by the effects of multipath fading in wireless channels when compared with the ideal white Gaussian noise channel. In this study, a new modulation classification method is proposed, exploring different features of normalised fourth-order cumulant statistics for a modified blind channel estimation method in the multipath fading channel. The relationship between the cumulants of the received signal and the multipath fading effects is established to cope with the channel impulse response in the new algorithm. Simulation results show that the performance of the proposed AMC method is much improved than that of previously proposed ones in terms of the probability of correct classification.

Blind Channel Estimation for MIMO-OFDM Systems With Low Order Signal Constellation

In this paper, we design a new blind channel estimation method for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems to cope with possible rank deficient signal covariance matrices when symbols are drawn from low order constellations, e.g., BPSK, QPSK, etc. By collecting the signal covariance matrices from a group of carefully selected subcarriers, the proposed method could identify the channel information from a small amount of received blocks. Moreover, the proposed method also outperforms the existing competitor in terms of both estimation performance and computational complexity. The numeral results are provided to corroborate the proposed studies.

One-Shot Blind CFO and Channel Estimation for OFDM With Multi-Antenna Receiver

In this paper, we design a new blind joint carrier frequency offset (CFO) and channel estimation method for orthogonal frequency-division multiplexing (OFDM) with multiantenna receiver. The proposed algorithm requires only one received OFDM block and thus belongs to the category of one-shot estimation methods. Other advantages of the proposed algorithm include 1) it supports fully loaded data carriers and is thus spectral efficient; 2) the channel from the transmitter to each receive antenna can be blindly estimated with only a scaling ambiguity; and 3) the algorithms outperforms the existing methods. Moreover, we derive the Cramer-Rao Bounds (CRB) of joint CFO and channel estimation in closed forms. Numeral results not only show the effectiveness of the proposed algorithm but also demonstrate its closed performance to CRB.

Blind Channel Estimation Based on Multilevel Lloyd-Max Iteration for Nonconstant Modulus Constellations

In wireless communications, knowledge of channel coefficients is required for coherent demodulation. Lloyd-Max iteration is an innovative blind channel estimation method for narrowband fading channels. In this paper, it is proved that blind channel estimation based on single-level Lloyd-Max (SL-LM) iteration is not reliable for nonconstant modulus constellations (NMC). Then, we introduce multilevel Lloyd-Max (ML-LM) iteration to solve this problem. Firstly, by dividing NMC into subsets, Lloyd-Max iteration is used in multilevel. Then, the estimation information is transmitted from one level to another. By doing this, accurate blind channel estimation for NMC is achieved. Moreover, when the number of received symbols is small, we propose the lacking constellations equalization algorithm to reduce the influence of lacking constellations. Finally, phase ambiguity of ML-LM iteration is also investigated in the paper. ML-LM iteration can be more robust to the phase of fading coefficient by dividing NMC into subsets properly. As the signal-to-noise ratio (SNR) increases, numerical results show that the proposed method’s mean-square error curve converges remarkably to the least squares (LS) bound with a small number of iterations.

Cross‐relation‐based frequency‐domain blind channel estimation with multiple antennas in orthogonal frequency division multiplexing systems

Frequency domain blind channel estimation methods for orthogonal frequency division multiplexing (OFDM) systems with multiple antennas are proposed, in which the cross relation between the channel gains and a single snapshot of the received signal on each subcarrier is utilised. Necessary and sufficient conditions for the identifiability of a single-input multiple-output OFDM channel estimator are derived and, furthermore, using a first-order perturbation analysis, the approximation of mean-squared-error (MSE) is analytically obtained, which shows that the proposed estimator is approximately unbiased at high signal-to-noise ratio. The proposed estimator exhibits lower MSEs than those of both the existing subspace-based and deterministic blind channel estimators and is less sensitive to the estimation error of the number of multipaths. Finally, the extension of the proposed channel estimation to multiple-input-multiple-output OFDM is presented.

On the blind channel identifiability of multiple-input multiple-output space-time block code systems using Joint Approximate Diagonalization of Eigenmatrices

Channel identifiability for multiple-input multiple-output space-time block code MIMO-STBC systems using Joint Approximate Diagonalization of Eigenmatrices JADE is studied in this paper. Compared with the previous blind MIMO-STBC channel estimation methods in literature, the method proposed in this paper is more suitable for non-cooperative scenario because it needs less prior information and can be applied to a general class of STBCs. The main contribution of the paper consists in the theoretical proof that, although the sources transmitted by different antennas of MIMO-STBC systems are not independent, they can be retrieved from the received data by directly using JADE in most cases. The conclusion is also demonstrated by a simulation. This shows that the classical JADE algorithm can be applied to a wider range of situations rather than strictly independent sources. Copyright © 2013 John Wiley & Sons, Ltd.

An Improved Subspace-Based Algorithm for Blind Channel Identification Using Few Received Blocks

In the last decade, several subspace-based algorithms for blind channel identification in zero-padded systems were introduced. These subspace-based methods are attractive because highly accurate estimates of the channel can be obtained by using only a few received blocks. However, they do not work when applied to the zero-padded orthogonal frequency division multiplexing systems (ZP-OFDM) with virtual carriers. In this paper, we propose two improvements on an earlier subspace-based blind channel estimation method for such systems. Firstly, we introduce a simple noise weighting approach. Unlike most of the earlier methods, the proposed weighting matrix is diagonal and it is independent of the channel noise variance and SNR. By doing so, the performance of previous work is significantly enhanced. Secondly, we extend the blind estimation method to ZP-OFDM systems with virtual carriers. Simulations are carried out to demonstrate the merits of the proposed method.

Design and Implementation of an Underlay Control Channel for Cognitive Radios

Implementation of any cognitive radio network requires an effective control channel that can operate under various modes of activity from the primary users. This paper reports the design and implementation of a filter bank multicarrier spread spectrum (FBMC-SS) system for use as the control channel in cognitive radio networks. The proposed design is based on a filtered multitone (FMT) implementation. Carrier and timing acquisition and tracking methods as well as a blind channel estimation method are developed for the proposed control channel. We also report an implementation of the proposed FBMC-SS system on a hardware platform; a FlexRIO FPGA module from National Instruments.

Blind Channel Estimation Based on the Lloyd-Max Algorithm in Narrowband Fading Channels and Partial-Band Jamming

In wireless communications, knowledge of the channel coefficients is required for coherent demodulation. In this work, a blind channel estimation method based on the Lloyd-Max algorithm is proposed for single-tap fading channels. The algorithm estimates the constellation points for the received signal using the Lloyd-Max algorithm. The algorithm is investigated for frequency hopping systems with small hop durations and operating under partial-band jamming for both detecting the jammer and estimating the channel. The performance of the Lloyd-Max channel estimation algorithm is compared to the performance of pilot-based channel estimation algorithms and non-coherent demodulation and decoding. A special concatenated channel code is constructed to work with the proposed blind channel estimation due to the phase ambiguity in estimates.