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.

OFDM usually incorporates pilot tones in the frequency domain (FD) or training symbols in the time-domain (TD) to facilitate channel estimation algorithms. TD channel estimation becomes more attractive in quasi-static channels because channel estimation scheme will optimize the spectral efficiency by re-using the training symbols designated for FD channel estimation. A channel estimation method based on time domain averaging algorithm is proposed. Due to the principle of centralized energy in time domain, the effective channel impulse response length can be detected by setting of threshold for the estimated channel impulse response length. Computer simulation demonstrates the performance of the proposed algorithms in terms of bit error rate performance.

3G standards such as TD-SCDMA use multi-user detection (MUD) at the base station to combat multi address interference (MAI) and inter-symbol interference (ISI). We review Cholesky factorization and Schur algorithm for Zero Forcing Block Linear Equalization. We compare the solutions of different algorithm for ZF-BLE by computation, and analyze the complexity of those methods.

Orthogonal frequency-division multiplexing (OFDM) combines the advantages of high performance and relatively low implementation complexity. However, for reliable coherent detection of the input signal, the OFDM receiver needs accurate channel information. The Doppler shift of fast-fading channels will generate inter-carrier interference (ICI) and, hence, degrade the performance of orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we present regularized total least-squares (RTLS) scheme to eliminate the ICI and noise. A closed-form mathematical expression has been derived to express the channel estimation. It has been shown that the proposed channel estimation and data detect can effectively eliminate the ICI effect.

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.