Switching Equalization Algorithm Based on a New SNR Estimation Method

It is well-known that turbo equalization with the max-log-map （MLM） rather than the log-map （LM） algorithm is insensitive to signal to noise ratio （SNR） mismatch. As our first contribution, an improved MLM algorithm called scaled max-log-map （SMLM） algorithm is presented. Simulation results show that the SMLM scheme can dramatically outperform the MLM without sacrificing the robustness against SNR mismatch. Unfortunately, its performance is still inferior to that of the LM algorithm with exact SNR knowledge over the class of high-loss channels. As our second contribution, a switching turbo equalization scheme, which switches between the SMLM and LM schemes, is proposed to practically close the performance gap. It is based on a novel way to estimate the SNR from the reliability values of the extrinsic information of the SMLM algorithm.

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.

SNR estimation algorithm based on the preamble for wireless OFDM systems

Based on the analysis of the performance of Boumard＇s SNR method for wireless orthogonal frequency division multiplexing （OFDM） systems, a new estimation algorithm of the noise variance is proposed by only using the data samples of the two training symbols in the preamble, and the second order moment of these data samples is employed to estimate the signal power. The average SNR and the SNRs on the subchannels can all be estimated by the proposed algorithm, and its performance is independent of the channel＇s frequency selectivity. Simulation results show that the performance of the proposed method is highly improved and much better than that of Boumard＇s method.

An algorithm to solve autocorrelation matrix singular value based on SNR estimation

SNR estimation of communication signals is important to improve demodulation performance and channel quality of communication system,thus it is an important research issue of communication field.According to the core problem of autocorrelation matrix singular value in SNR estimation process,through making use of householder transforming autocorrelation matrix into tridiagonal matrix,and by using the relation of corresponding characteristic equation coefficients and singular value,a numerical algorithm is given to obtain autocorrelation matrix singular value,and the algorithm is used for SNR solving process.Theoretical analysis shows that the algorithm can satisfy the requirements in the aspect of constringency speed and stability.

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.

A NOVEL METHOD FOR ESTIMATING THE SNR OF UNKNOWN EMITTER SIGNAL

It is important to estimate the Signal-to-Noise Ratio(SNR) of unknown emitter signal accurately.In order to resolve the disadvantages of present algorithm,a novel method is proposed in this letter.We extract and normalize the information of zero frequency of received signal by the Wigner-Vile Distribution(WVD) transformation and then get the approximate power of original signal by mathematic transformation,at last,we get the estimate value of SNR by the known account formula of SNR.Simulation results show that it is correct and feasible.

Channel Estimation and Compensation for Underwater Acoustic Pipeline Communication

An estimation and compensation algorithm for underwater acoustic pipeline channel is investigated.A joint time-frequency adaptive signal-to-noise ratio（SNR）estimation based on the maximum likelihood method is introduced firstly,and the Cramer-Rao lower bound（CRLB）is proposed so as to evaluate the performance of the SNR estimation algorithm.For frequency-selective fading channel part,estimation and compensation are made to improve the robustness of the system on the basis of the LMS algorithm.Furthermore,real-time update iteration algorithm in the frequency domain is investigated to realize synchronous receiving and estimation.For verification,simulations and actual data tests were made,and the results show that the algorithm possesses great robustness,efficiency and accuracy inrealization of SNR estimation,signal detection and frequency impulse compensation for the channel.

Single-channel speech enhancement method based on masking properties and minimum statistics

A single-channel speech enhancement method of noisy speech signals at very low signal-to-noise ratios is presented, which is based on masking properties of the human auditory system and power spectral density estimation of non stationary noise. It allows for an automatic adaptation in time and frequency of the parametric enhancement system, and finds the best tradeoff among the amount of noise reduction, the speech distortion, and the level of musical residual noise based on a criterion correlated with perception and SNR. This leads to a significant reduction of the unnatural structure of the residual noise. The results with several noise types show that the enhanced speech is more pleasant to a human listener.

Sensitivity analysis of the channel estimation deviation to the MAP decoding algorithm

As a necessary input parameter for maximum a-posteriori(MAP)decoding algorithm,SNR is normally obtained from the channel estimation unit.Corresponding research indicated that SNR estimation deviation degraded the performance of Turbo decoding significantly.In this paper,MAP decoding algorithm with SNR estimation de-viation was investigated in detail,and the degradation mechanism of Turbo decoding was explained analytically.The theoretical analysis and computer simulation disclosed the specific reasons for the performance degradation when SNR estimation was less than the actual value,and for the higher sensitivity of SNR estimation to long-frame Turbo codes.