DFT-based Channel Estimation Method Research Articles

DFT‐based channel estimation refinement by clustering in FBMC‐OQAM system

The conventional DFT-based channel estimation method can improve the performance of the least square (LS) or minimum mean square error (MMSE) channel estimation by removing the noise outside the maximum channel delay while the noise inside channel delay still remain. Here, a novel DFT-based pilot-aided channel estimation method for filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is proposed. Using clustering and discriminant analysis, this method can separate automatically the noise inside channel delay from channel impulse response (CIR) coefficient of the conventional DFT-based channel estimation. Theoretical analysis and simulation results show that the accuracy of channel estimation can be improved remarkably. Compared with conventional DFT-based channel estimation method and DFT-based channel estimation method with threshold, the proposed DFT-based channel estimation method with clustering has a better bit error ratio (BER) performance in additive white Gaussian noise (AWGN) channel and flat fading channel.

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

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.

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.