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Block diagram of MC-CDMA Receiver with the proposed channel estimator.
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Multicarrier code-division multiple access (MC-CDMA) combines multicarrier transmission with direct-sequence (DS) spread spectrum techniques. In this study, several possible channel models of MC-CDMA systems are considered as a multi-state switching Markov process to match the time-varying multipath fading channel. A novel multiple channel estimato...
Contexts in source publication
Context 1
... Y n is the output vector of the DFT, which is illustrated in Fig. 2; C is the normalized orthogonal code matrix of all users with the dimension N × N u ; d n is the symbol-mapped data of all users; H n denotes a block diagonal matrix of the subcarrier channel coefficients which are the DFT conversion of the channel in time domain; and V n is the frequency domain noise vector, which is the DFT output of ...
Context 2
... symbol-mapped data of all users; H n denotes a block diagonal matrix of the subcarrier channel coefficients which are the DFT conversion of the channel in time domain; and V n is the frequency domain noise vector, which is the DFT output of the channel noise in time domain. The architecture of the receiver for MC- CDMA systems is illustrated in Fig. 2, in which the received vector Y n is fed into the proposed channel estimator to generate the estimated channeî H n and the predicted channeîchanneî H n|n−1 , and then an MMSE equalizer employs the received vector Y n , predicted channeî H n|n−1 and spreading code matrix C to accurately detect the transmitted symbolsˆdsymbolsˆ symbolsˆd ...
Citations
... W i represents the model error, and it is a zero-mean, variance σ 2 w Gaussian complex white noise. According to the Jakes model, the time correlation coefficients a i,k can be expressed as [33]: ...
Channel estimation is a challenging problem for space time block coding (STBC) multipleinput and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems in dynamic environments. To handle this problem and improve the system performance, this paper proposes a Kalman filter (KF) based channel estimation method applied to 2 × 2 and 4 × 4 STBC MIMO-OFDM systems. The proposed method based on the dynamic tracking property of KF is well adopted for dynamic channel estimation. First, a new orthogonal space-time codeword is adopted, and the orthogonal pilot sequences are designed to suppress the interference among transmit antennas. Then, the prediction and update characteristics of KF are researched, and the state space model is established for STBC MIMO-OFDM system. Subsequently, the channel state information (CSI) is estimated iteratively according to the KF estimation equation. At last, to further improve the accuracy of KF channel estimation, the threshold is utilized to suppress the noise in the channel impulse response (CIR) estimated by KF method. Simulation results verify that the proposed KF channel estimation method with orthogonal pilots and STBC provides better bit error rate (BER) and normalized mean square error (NMSE) performance compared with other conventional channel estimation methods, and it can be effectively adapted to dynamic multipath propagation conditions with different low and high order modulations.
... Channel coefficients can be estimated through two-dimensional linear filtering [17], [18], [19]. Estimates of the channel impulse response can also be obtained by interpolation, through adaptive schemes [20] and using decisiondirected techniques in the frequency domain [21]. Optimal location of pilots is the subject of extensive research [22], [23], [24], [25], [26]. ...
This paper addresses pilot-assisted estimation offrequency-selective time-invariant channels in multicarrier Code Division Multiple Access communications systems (MC CDMA and MC DS-CDMA). Performance in terms of normalised mean square error (NMSE) is derived for two discrete channel frequency response estimators: a conventional estimator based on the minimum mean square error criterion, and an improved estimator exploiting subspace relationships between the frequency and impulse responses of the discrete channel. For MC DS-CDMA, NMSE performances of both estimators result in closed-form solutions. For MC CDMA, a closed-form solution is derived for the NMSE of the conventional estimator; upper and lower bounds are provided for the NMSE of the improved estimator. Furthermore, for the particular case of identically distributed discrete channels with common arbitrary power delay profile and uncorrelated weights, a closed-form expression for the NMSE of the improved estimator is also obtained. Numerical results illustrate the accuracy of the proposed NMSE expressions.
... In Chen and Liao (2007), a channel estimator based on multiple channel model, which includes several possible channel models based on different ranges of Doppler frequencies, is proposed for MC-CDMA systems. The estimated channel coefficients are then employed in a MMSE equaliser for symbol detection. ...
This paper deals with the joint estimation of rapidly time-varying and correlated Rayleigh fading channels in synchronous multi-carrier direct-sequence code-division-multiple-access (MC-DS-CDMA) systems. Usually, when the multiple carrier fading channels are modelled by autoregressive (AR) processes, they can be estimated separately by means of an optimal Kalman filter. However, a loss in performance can be expected when the channels are correlated. To take into account these correlations, the multiple carrier fading processes are stored in a vector, modelled as vector AR process, and estimated jointly by means of an optimal Kalman filter. Nevertheless, this requires the simultaneous estimation of the AR parameter matrices in the vector AR process. To avoid a non-linear approach such as the extended Kalman filter (EKF), this estimation issue can be solved by using dual Kalman filters. A comparative study on channel estimation is carried out between the proposed joint estimation scheme, the separate estimation counterpart and the standard least mean square (LMS) based estimator.
... We can write the amplitude fluctuation of the base band signal as follows τ ( s T is the sample duration) in frequencynonselective channel. In this paper, we implement Rayleigh fading simulator using 34 paths [36], [38]. Here we consider a slow fading channel and the fading factor is constant within the symbol duration. ...
This article describes linear and nonlinear Artificial Neural Network(ANN)-based predictors as Autoregressive Moving Average models with Auxiliary input (ARMAX) process for Signal to Interference plus Noise Ratio (SINR) prediction in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The Multi Layer Perceptron (MLP) neural network with nonlinear function is used as nonlinear neural network and Adaptive Linear (Adaline) predictor is used as linear predictor. The problem of complexity of the MLP and Adaline structures is solved by using the Minimum Mean Squared Error (MMSE) principle to select the optimal numbers of input and hidden nodes by try and error role. Simulation results show that both of MLP and Adaline optimal neural networks can track the effect of deep fading due to using a 1.8 GHZ carrier frequency at the urban mobile speeds of 10 km/h, 50 km/h and 120 km/h with tolerable estimation errors. Therefore, the neural network-based predictor is well suitable SINR-based predictor in closed-loop power control to combat multi path fading in CDMA systems.
... A channel-sounding approach is employed in which a train of pulses is periodically transmitted [5]. A multiple-channel model, which includes several possible channel models based on the different ranges of Doppler frequencies (or mobile velocities), is constructed to treat the timevarying fading channel [6]. In addition, a decision-directed channel estimation in the frequency domain using a Kalman-based filter has been proposed [1]. ...
... The optimal MMSE equalization for (26) with the channel prediction is [6] ...
... where σ 2 s = E{|S n (m)| 2 }, the channel predictionĤ n|n−1 (m) is obtained fromX n|n−1 in Table I, and the covariance of channel prediction error β n|n−1 (m) = E{|H n|n−1 (m)| 2 } = P n|n−1, (2,2) (m) is the element at the second row and second column of P n|n−1 (m) in Table I. Finally, the output of the MMSE equalizer will multiply with the Walsh-Hadamard code, and the MC-CDMA symbold n can be detected [6]. It is worthy noting that the conventional decisiondirected scheme in [1] adopts the previous estimates to perform the current MMSE equalization. ...
An unscented Kalman filter (UKF)-based channel-tracking method is proposed for a fast time-varying multipath fading channel in a multicarrier code-division multiple-access (MC-CDMA) system. The mobile radio channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the channel gain are simultaneously estimated by the proposed method. One-step-ahead prediction can also be obtained during channel estimation. It is useful for the decision-directed channel-tracking design, particularly in the fast-fading channel. Meanwhile, the estimated parameters can enhance the minimum mean-square error (MMSE) equalizer for symbol detection. The simulation results show that the enhanced equalizer based on the proposed estimation algorithm performs much better than that based on the conventional channel estimators in symbol error rate.
... Some of the references document the behavior of fixed wireless interfaces with the channel variation occurring due to moving scatterers [15]. Others are based on simulations [4,[16][17][18][19][20][21] or calculations [22][23][24] and not on measurements. Channel conditions for TETRA mobile radio use in forests were documented in [25]; however, this environment has different propagation properties. ...
... Channel conditions for TETRA mobile radio use in forests were documented in [25]; however, this environment has different propagation properties. Recent work on robust estimation of timevarying channels using various methods to adapt equalizers or filters was presented in [16][17][18][19][20][21][22]. These theoretical contributions are very valuable, but their aim is different from the goal of this paper: to investigate the performance of a robust tracking algorithm in an actual measurement scenario, involving a time-variant channel observed over a time period much longer than the channel coherence time. ...
In the 2.45GHz band, indoor wireless off-body data communication by a moving person can be problematic due to time-variant signal fading and the consequent variation in channel parameters. Off-body communication specifically suffers from the combined effects of fading, shadowing, and path loss due to time-variant multipath propagation in combination with shadowing by the human body. Measurements are performed to analyze the autocorrelation, coherence time, and power spectral density for a person equipped with a wearable receive system moving at different speeds for different configurations and antenna positions. Diversity reception with multiple textile antennas integrated in the clothing provides a means of improving the reliability of the link. For the dynamic channel estimation, a scheme using hard decision feedback after MRC with adaptive low-pass filtering is demonstrated to be successful in providing robust data detection for long data bursts, in the presence of dramatic channel variation.
... Other approaches [15,16] consider an explicit channel estimation based on channel sounding in which a "train of pulses" spaced by the maximum delay spread of the channel is transmitted instead. A multiple channel model, which includes several possible channel models based on the different ranges of Doppler frequencies (or mobile velocities), is constructed to treat the time-varying fading channel [17]. In addition, a decisiondirected channel estimation in the frequency domain using Kalman-based filter has been proposed [18]. ...
... The maximum-likelihood parameter estimation is to specify θ and σ 2 u to maximize the log-likelihood function in (17). Using the least-square (LS) criteria, we get the following estimation [28]: ...
A recursive maximum-likelihood (RML) algorithm for channel estimation under rapidly fading channel and colored noise in a multicarrier code-division multiple-access (MC-CDMA) system is proposed in this paper. A moving-average model with exogenous input (MAX) is given to describe the transmission channel and colored noise. Based on the pseudoregression method, the proposed RML algorithm can simultaneously estimate the parameters of channel and colored noise. Following the estimation results, these parameters can be used to enhance the minimum mean-square error (MMSE) equalizer. Considering high-speed mobile stations, a one-step linear trend predictor is added to improve symbol detection. Simulation results indicate that the proposed RML estimator can track the channel more precisely than the conventional estimator. Meanwhile, the performance of the proposed enhanced MMSE equalizer is robust to the rapidly Rayleigh fading channel under colored noise in the MC-CDMA systems.
... Theoretical fundamentals of linear and non-linear equalizers were developed in the 1970-1990 as summarized in tutorial reviews [1]. However, interest in the adaptive equalization is still noticeable in the scientific papers until now [2,3]. Indeed, in addition to the classical applications in the DSL modems [1] and wireless (radio) communications [4] adaptive equalization is proposed for underwater (acoustic) telemetry systems [5], for optical transceivers [6], for read channels in magnetic hard driver data disks [7], for terrestrial digital video broadcasting receivers [8], etc. ...
... Indeed, in addition to the classical applications in the DSL modems [1] and wireless (radio) communications [4] adaptive equalization is proposed for underwater (acoustic) telemetry systems [5], for optical transceivers [6], for read channels in magnetic hard driver data disks [7], for terrestrial digital video broadcasting receivers [8], etc. Even in the communication systems where channel distortions are in principal targeted by alternative solutions like spread spectrum modulation, OFDM or CDMA [4], adaptive equalizers are useful ever after [2]. ...
Hardware prototyping platform for the adaptive equalizer investigation is presented in the paper. The platform consist the equalizer, communication channel, excitation and signal acquisition means that are mapped to two Digital Spectrum Starter Kits based on Texas Instruments DSP and PC sound card. Simulink models of the equalizer, communication channel and excitation generator are compiled and executed by the processors of the DSK boards. The ability of the implemented equalizer to reconstruct shape of the excitation pulses distorted by the communication channel was demonstrated. The proposed adaptive equalization prototyping platform can be used as a supplement to simulation in education. Ill. 6, bibl. 10 (in English; summaries in English, Russian and Lithuanian).
... Among all blind channel identification methods, subspace (SS) methods are popular since they often lead to better performance than other approaches in terms of residual ISI or residual BER [10]- [13]. SS methods were also used in the blind channel identification of CDMA systems [17], [17]- [19]. However, the subspace methods have two major restric- tions [1]. ...
... Among all blind channel identification methods, subspace (SS) methods are popular since they often lead to better performance than other approaches in terms of residual ISI or residual BER [10]- [13]. SS methods were also used in the blind channel identification of CDMA systems [17], [17]- [19]. However, the subspace methods have two major restric- tions [1]. ...
Channel estimation and equalization techniques are crucial for the ubiquitous wireless communication systems. Conventional receivers for most wireless standards preset the channel length to the maximal expected duration of the channel impulse response for the adopted channel estimation and equalization algorithms. The excessive channel length often significantly increases the implementational complexity of the wireless receivers and leads to the redundant information which would induce the additional estimation errors. Moreover, such a scheme does not allow the dynamic memory allocation for variable channel lengths. This could further increase the power consumption and reduce the battery life of a mobile device. The knowledge of the actual channel length would, in principle, help the system designers decrease the complexity of the channel estimators using maximum likelihood (ML) and minimum-mean-square-error (MMSE) algorithms. In this paper, we address this important channel length estimation problem and propose a novel algorithm to estimate the channel length without the need of pilots or training sequence. In addition, we provide the analysis on the effectiveness of the proposed non-pilot-aided channel length estimator through Monte Carlo simulations.
Channel estimation is still a challenge for space time block coding (STBC) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems in time-varying environments. To estimate the channel state information (CSI) precisely without increasing complexity in any significant way, this paper utilizes the sparsity and the inherent temporal correlation of the time-varying wireless channel, and proposes a novel channel estimation method applied to STBC MIMO-OFDM systems. The proposed method consists of two schemes: adaptive multi-frame averaging (AMA) and improved mean square error (MSE) optimal threshold (IMOT). First, the temporal correlation of the time-varying channel is modeled by a linear Gauss-Markov (LGM) model, and the AMA scheme is incorporated to refine the initial estimated channel impulse response (CIR) through noise reduction. Based on the LGM model, the optimal average frame number is adaptively determined by minimizing the MSE of the denoised CIR. Then, the sparsity of the wireless channel is utilized to model the CIR as a sparse vector, and the IMOT scheme is performed to further remove the noise effect by discarding most of the noise-only CIR taps. Specifically, the IMOT scheme is achieved by recovering the CIR support across the optimal “tap-to-tap” threshold derived by minimizing the MSE of each CIR tap. Moreover, the prior confidence level of the tap to be active is calculated through multi-frame statistics to further improve the performance of the IMOT scheme. Simulation results verify that the proposed AMA-IMOT channel estimation method can achieve better performance than comparison methods.
