Novel Channel Estimation Method Based on Decision-Directed in OFDM

Based on the analysis of decision-directed （DD） channel estimation by using training symbols, a novel DD channel estimation method is proposed for orthogonal frequency division multiplexing （OFDM） system. The proposed algorithm takes the impact of decision error into account, and calculates the impact to next symbol duration channel state information. Analysis shows that the error propagation can be effectively restrained and the channel variation is tracked well. Simulation results demonstrate that both the signal error rate （SER） and the normalized mean square error （NMSE） performance of the proposed method are better than the traditional DD （DD＋ LS） and the maximum likelihood estimate （DD＋ MLE） method.

Semi-blind Adaptive Beamforming for High-throughput Quadrature Amplitude Modulation Systems

A semi-blind adaptive beamforming scheme is proposed for wireless systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna arrayts elements, are first utilised to provide a rough initial least squares estimate of the beamformer＇s weight vector. A concurrent constant modulus algorithm and soft decision-directed scheme is then applied to adapt the beamformer. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study.

Speech enhancement based on modified a priori SNR estimation

To solve the frame delay problem and match the previous frame,Plapous et al.[IEEE Transactions on Audio,Speech,and Language Processing,2006,14(6):2098–2108]introduced a novel approach called two-step noise reduction(TSNR)technique to improve the performance of the speech enhancement system.However,TSNR approach results in spectral peaks of short duration and the broken spectral outlier,which degrade the spectral characteristics of the speech.To solve this problem,a cepstral smoothing step is added in order to remove these spectral peaks brought by TSNR approach.Theory analysis shows that the proposed approach can effectively smooth the spectral peaks and keep the spectral outlier so as to protect the speech characteristics.Experiment results also show that the proposed approach can bring significant improvement compared to decision-directed(DD)and TSNR approaches,especially in non-stationary noisy environments.

Recursive Least Squares Semi-blind Beamforming for MIMO Using Decision Directed Adaptation and Constant Modulus Criterion

A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output （MIMO） induced and spacedivision multiple-access based wireless systems that employ high order phase shift keying signaling. A minimum number of training symbols, very close to the number of receiver antenna elements, are used to provide a rough initial least squares estimate of the beamformer＇s weight vector. A novel cost function combining the constant modulus criterion with decision-directed adaptation is adopted to adapt the beamformer weight vector. This cost function can be approximated as a quadratic form with a closed-form solution, based on which we then derive the recursive least squares （RLS） semi-blind adaptive beamforming algorithm. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study. Our proposed semi-blind RLS beamforming algorithm therefore provides an efficient detection scheme for the future generation of MIMO aided mobile communication systems.