DFT-based Channel Estimation Research Articles

QR-based Channel Estimation for Orthogonal Frequency Division Multiplexing Systems

Channel estimation is the key technology for Orthogonal Frequency Division Multiplexing (OFDM), which has direct impact on the performance of OFDM. In this paper, we present a novel QR-based algorithm to update the channel impulse response(CIR) for DFT-based channel estimation. The discrete Fourier transform(DFT) estimation reduces the noise power that exists outside of the CIR part, because the estimated CIR from LS has most of its power concentrated on the first L samples. To reduce the noise power that exists inside of the first L samples, the CIR is further processed by QR decomposition in proposed algorithm. The simulation results show that the bit-error-rate(BER) of our estimator has reduced significantly compared with the conventional DFT-based channel estimator and LS-linear estimation.

An Improved DFT-Based Channel Estimation Algorithm for OFDM System on Time-Varying Multipath Fading Channels

An improved discrete Fourier transform DFT-based channel estimation for OFDM systems is proposed. Conventional DFT-based channel estimator improved its performance by suppressing noise, but it does not completely suppress noise. In order to overcome the disadvantage, this paper proposed a gate method without requiring any channel statistical information. This method comprehensively considersthe effects of the power of the strongest path and the noises. Computer simulation demonstrates the performance of the proposed algorithms in terms of bit error rate.

A Novel DFT-Based Channel Estimation for LTE-A Uplink

Conventional DFT-based channel estimations suppress the noise by a cut-off filter in time domain. However, the potentially suffer significant performance loss due to the energy leakage. In this paper, based on the detailed analysis of the channel impulse response (CIR) leakage in the LTE-A uplink system, a novel discrete Fourier transform (DFT)-based channel estimation algorithm is proposed. This algorithm estimates the average noise power in frequency domain to get a noise threshold, which is then used in time domain to eliminate the noise by DFT and reduce the spectrum leakage. The simulation results show that the proposed algorithm can effectively improve the BER performance, and has a moderate complexity compared to existing DFT based algorithms.

Channel Estimation in MIMO-OFDM System

There are no limit of human desire, so day by day we need much higher data speed to facilitate our need but every physical resource like frequency band, transmit signal strength are finite. Within the given limited resource, higher data speed is accomplished by new proficiency called Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM) system. MIMO-OFDM fulfills the high data rate requirement through spatial multiplexing gain and improved link reliability due to antenna diversity gain. With this technique, both interference reduction and maximum diversity gain are achieved by increasing number of antennae on either side. Received signal in MIMO-OFDM system is usually distorted by multipath fading. In order to recover the transmitted signal correctly, channel effect must be estimated and repaired at receiver. In this paper the performance evaluating parameter mean square error and symbol error rate of least square error, minimum mean square error and DFT based channel estimation methods are estimated and appropriate solution is recommended. Furthermore, comparison among their characteristics is simulated in MATLAB and useful conclusion is delineated. DOI: http://dx.doi.org/10.3126/njst.v14i2.10421 Nepal Journal of Science and Technology Vol. 14, No. 2 (2013) 97-102

Low-Complexity DFT-Based Channel Estimation with Leakage Nulling for OFDM Systems

In this letter, a low-complexity but near-optimal DFT-based channel estimator with leakage nulling is proposed for OFDM systems using virtual subcarriers. The proposed estimator is composed of a time-domain (TD) index set estimation considering the leakage effect followed by a low-complexity TD post-processing to suppress the leakage. The performance and complexity of the proposed channel estimator are analyzed and verified by computer simulation. Simulation results show that the proposed estimator outperforms conventional estimators and provides near-optimal performance while keeping the low complexity comparable to the simple DFT-based channel estimator.

DFT-based Cluster Analysis Channel Estimation Algorithm for OFDM Systems on Multipath Channels

In this paper, a enhanced DFT-based channel estimation for OFDM systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise beyond the length of the cyclic prefix (CP), so it does not completely suppress the noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In order to overcome the disadvantage, our proposed channel estimation can improve the performance by deciding significant channel taps adaptively. Significant channel taps are detected on the basis of cluster discriminant analysis. Simulation results demonstrate that the proposed algorithm outperforms the conventional DFT-based estimation in terms of BER and MSE performance.

An Improved DFT-Based Channel Estimation Algorithm for OFDM System in Non-sample-Spaced Multipath Channels

It is well known that channel impairment caused by multipath reflections can deeply degrade the transmission efficiency in wireless communication systems. The conventional DFT-based channel estimation methods improve the performance by neglecting nonsignificant channel taps. However, in multipath channels with non-sample-spaced time delays, this will cause power leakage and result in an error floor. In order to overcome this problem, based on the property of Channel impulse response, we describe a utility of channel estimation technology for OFDM systems using discriminant analysis. Usually, significant channel taps are detected on the basis of a predetermined threshold, so the optimal threshold value becomes a crucial factor. But it is difficult to decide channel taps that are approximately equal to the threshold value. To solve this disadvantage, the proposed algorithm improves performance by using Mahalanobis distance discriminant analysis for channel taps. This approach can mitigate the aliasing effect in the DFT-based channel estimator and reduce the leakage power efficiently when there is non-sample-spaced path delay. Simulation results show that the proposed channel estimators can eliminate the error floor substantially and its performance is better than the LS and conventional DFT estimators.

Improved Algorithm Based on the DFT Transform Channel Estimation and Threshold Filtering

In channel estimation, the complexity of the DFT-based channel estimation algorithm is lower than the MMSE algorithm, and the DFT-based algorithm performs better than the LS algorithm. However, due to that the traditional algorithms simply considered all the samples to be useful channel impulse response, ignoried the effect of noise. Therefore, the algorithm could be improved. This paper presents an improved algorithm based on twice noise estimation theory. The algorithm uses the sequence of points other than the cyclic prefix length to estimate the noise variance firstly, and then use the estimated noise variance to distinguish the noise samples within the cyclic prefix length. The computation of the new noise variance and noise mean through the new noise points as a threshold filters the impulse response of the channel in time domain and eliminates the impact of noise on the system further. The simulation result shows that the improved algorithm performs better than the traditional algorithm.

Channel Estimation Algorithm Using an Improved Dft for MimoOfdm Systems

The Improved DFT-based Channel Estimation Algorithm for MIMO-OFDM System uses the symmetric property to extend the LS estimate in frequency domain, and calculates the changing rate of the leakage energy, and selects useful paths by the changing rate.

Two Novel Channel Estimation for OFDM Systems by Time-Domain Cluster Discriminant Analysis Based on Parametric Channel Modeling

In this paper, we describe two novel channel estimation technologies for orthogonal frequency-division multiplexing mobile communication systems using cluster discriminant analysis for sparse multipath channels. The least-squares estimator has a merit of low complexity and simple structure; however one of its drawbacks is that it does not take into consideration the effect of noise. Conventional DFT-based channel estimator improved its performance by suppressing time domain noise, but it does not completely suppress the noise. In order to overcome this disadvantage, we propose two novel channel estimation algorithms for Orthogonal frequency division multiplexing systems based on cluster analysis and discriminant analysis. The cluster analysis can be used to cluster residual noise. Discriminant analysis can distinguish the noise and channel taps in time domain. Computer simulation demonstrates the performance of the proposed algorithms in terms of bit error rate and mean square error performance.

DFT-Based on Mahalanobis Distance Discriminant Analysis Method Channel Estimation Algorithm for OFDM Systems

An enhanced discrete Fourier transform DFT-based channel estimation for OFDM systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In order to overcome the disadvantage, our proposed channel estimation can improve the performance by deciding significant channel taps adaptively. Significant channel taps are detected on the basis of Mahalanobis distance discriminant analysis. Simulation results demonstrate that the proposed algorithm outperforms the conventional DFT-based estimation in terms of BER and MSE performance.

다속신호처리 기법을 이용한 LTE 시스템 채널 추정기법 설계

The Long Term Evolution (LTE) system is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the lattice-type pilot samples in the multipath fading channel environment. The estimation of the channel frequency response (CFR) makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time- and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. Any interpolation scheme could be adopted for this purpose. Depending on the requirements of the target system, we may choose a simple linear interpolation or a sophisticated one. For any choice of an interpolation scheme, these is a trade-off between estimation accuracy and numerical cost. For those wireless communication systems based on the OFDM and the preamble-type pilot structure, the DFT-based channel estimation and its variants have been successfully. Yet, it may not be suitable for the lattice-type pilot structure, since the pilot samples are not sufficient to provide an accurate estimate and it is known to be sensitive to the location as well as the length of the time-domain window. In this paper, we propose a simple interpolated based on the upsampling mechanism in the multirate signal processing. The proposed method provides an excellent alternative to the DFT-based methods in terms of numerical cost and accuracy. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification.

Performance of Robust OFDM Channel Estimation with Strong Interference Detector

In this letter, DFT-based channel estimation (CE) with a strong interference detector is proposed for OFDM systems. Computer simulations demonstrate that the proposed scheme achieves similar performance to an interference-free system and is a significant enhancement over conventional methods.

DFT-Based Channel Estimation with Symmetric Extension for OFDMA Systems

A novel partial frequency response channel estimator is proposed for OFDMA systems. First, the partial frequency response is obtained by least square (LS) method. The conventional discrete Fourier transform (DFT) method will eliminate the noise in time domain. However, after inverse discrete Fourier transform (IDFT) of partial frequency response, the channel impulse response will leak to all taps. As the leakage power and noise are mixed up, the conventional method will not only eliminate the noise, but also lose the useful leaked channel impulse response and result in mean square error (MSE) floor. In order to reduce MSE of the conventional DFT estimator, we have proposed the novel symmetric extension method to reduce the leakage power. The estimates of partial frequency response are extended symmetrically. After IDFT of the symmetric extended signal, the leakage power of channel impulse response is self-cancelled efficiently. Then, the noise power can be eliminated with very small leakage power loss. The computational complexity is very small, and the simulation results show that the accuracy of our estimator has increased significantly compared with the conventional DFT-based channel estimator.

A Refined Channel Estimation Method for STBC/OFDM Systems in High-Mobility Wireless Channels

In this paper, we investigate channel estimation for orthogonal frequency division multiplexing (OFDM) systems with space-time block code (STBC) in mobile wireless channels. Our proposed method consists of two-stage processing and is developed on the basis of the classical discrete Fourier transform (DFT)-based channel estimation method. In the initialization stage, we employ a multipath interference cancellation technique to estimate multipath delays and multipath complex gains. In the tracking stage, we develop a refined decision-feedback (DF) DFT-based channel estimation method in which a few pilot tones inserted in OFDM data symbols are applied to form an optimal gradient vector at the first iteration such that the error propagation effect is mitigated. In order to reduce computational complexity, an approximate weighting matrix is adopted to avoid matrix inversion. We demonstrate the proposed method through computer simulation of an STBC/OFDM system with two transmit antennas and a single receive antenna. The results show that our method outperforms the classical DFT-based method, the STBC-based minimum mean square error (MMSE) method, and the Kalman filtering method as well, and that significant signal-to-noise ratio (SNR) performance improvement can be achieved, especially when a high-level modulation scheme, e.g. 16QAM, is adopted in high-mobility environments.

A New DFT-Based Channel Estimation Approach for OFDM with Virtual Subcarriers by Leakage Estimation

Equidistance in pilot spacing is an essential condition for discrete Fourier transform (DFT)-based channel estimation in OFDM systems. However, virtual subcarriers break this condition, degrade the estimation performance, and cause the interference (called ''leakage') because the orthogonality of Fourier matrix is broken. To solve this problem, we first analyze the leakage using the DFT-inverse DFT process. The pilot subcarriers inside virtual subcarriers area are estimated by the inverse of the estimated leakage. Thus, the equidistance condition is satisfied. The proposed estimator operates well in realistic environment such as IEEE 802.16, and it is robust to an increase of virtual subcarriers.

Efficient DFT-based channel estimation for OFDM systems on multipath channels

An improved discrete Fourier transform (DFT)-based channel estimation for orthogonal frequency division multiplexing systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In contrast, our purposed channel estimation can improve the performance by deciding significant channel taps adaptively without requiring any channel statistical information. Significant channel taps are detected on the basis of a predetermined threshold. The optimal threshold to reduce the MSE of the estimation is also derived, and it is confirmed by computer simulation. Simulation results demonstrate that the proposed algorithm can improve the MSE performance ~6.5 dB compared with the conventional DFT-based estimation, and the MSE floor is not observed in any channels.

A novel uplink channel estimation in OFDM-CDMA systems

Orthogonal frequency division multiplexing-code division multiplex access (OFDM-CDMA) is one of the best candidates for the future broadband wireless multimedia communication systems. This paper proposes a novel channel estimation algorithm for OFDM-CDMA systems on the uplink. With reasonable constraint and well-designed preambles for each user, the DFT-based uplink channel estimation algorithm can achieve good estimation accuracy without sacrificing much system overhead. Computer simulation demonstrates effectiveness of this method and conclusion is followed.