Research on Channel Equalization Algorithm in SC-FDE System

A lot of work has been done recently to develop algorithms that utilize the distributed structure of anad hocwireless sensor network to estimate a certain parameter of interest. One such algorithm is called diffusion least-mean squares (DLMS). This algorithm estimates the parameter of interest using the cooperation between neighboring sensors within the network. The present work proposes an improvement on the DLMS algorithm by using a variable step-size LMS (VSSLMS) algorithm. In this work, first, the well-known variants of VSSLMS algorithms are compared with each other in order to select the most suitable algorithm which provides the best trade-off between performance and complexity. Second, the detailed convergence and steady-state analyses of the selected VSSLMS algorithm are performed. Finally, extensive simulations are carried out to test the robustness of the proposed algorithm under different scenarios. Moreover, the simulation results are found to corroborate the theoretical findings very well.

The step size of least mean square (LMS) algorithm is significant for its performance. To be specific, small step size can get small excess mean square error but results in slow convergence. However, large step size may cause instability. Many variable step size least mean square (VSSLMS) algorithms have been developed to enhance the control performance. In this paper, a new VSSLMS was proposed based on Kwong’s algorithm to evaluate the robustness. The approximate analysis of dynamic and steady-state performance of this developed VSSLMS algorithm was given. An active vibration control system of piezoelectric cantilever beam was established to verify the performance of the VSSLMS algorithms. By comparing with the current VSSLMS algorithms, the proposed method has better performance in active vibration control applications.

This paper proposes a new application of fuzzy logic to variable step size least mean square (VS-LMS) adaptive beamforming algorithm in CDMA systems. The proposed algorithm adjusts the step size of the least mean square (LMS) by using the application of fuzzy logic in which the increase or decrease of step size depends on the fuzzy inference results of the mean square error (MSE). Computer simulation results show that the proposed algorithm has a better capacity of tracking compared with the conventional LMS algorithms and other variable step size LMS algorithms.

Vehicle interior noise is a harmful sound formed in the vehicle interior under the influence of engine noise, transmission system noise, and body radiation noise during vehicle operation. The intensity of noise in the vehicle increases with the increase of vehicle speed and engine speed, which worsens the operating environment of the vehicle and does harm to the mood, spirit, and physiology of drivers and passengers. Because the noise is difficult to identify in the process of vehicle vibration signal recognition, aiming at the problem of vehicle vibration signal detection under the background of strong noise, combined with the characteristics of vehicle vibration signal, the variable step size LMS algorithm is applied to vehicle noise and vibration signal recognition. In this paper, based on the signal eigenvalues obtained from the vibration signal characteristics in the noise and vibration signal, the eigenvalues of the vehicle noise can be extended from the frequency domain to the complex plane through the operation of the variable step size LMS, and the separation law corresponding to the extended vibration intensity can be used at the same time. It is used to obtain data by the signal variable step size LMS algorithm, and the obtained optimal separability feature is used as the characteristic parameter of the vibration signal. Finally, the results of an example analysis show that the algorithm proposed in this paper can be used to identify different types of vehicle noise and vibration signals, has a certain anti-interference performance against noise, and can improve the recognition rate of vehicle noise and vibration signals.

A novel variable step size least mean squares (VSS-LMS) algorithm employing cross correlation between channel output and error signal has been proposed as a solution to disadvantage of slow convergence of LMS algorithm. The new algorithm resolves the conflict between the convergence rate and precise of the fixed step-size conventional LMS algorithm. Computer simulations have been performed to verify the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed VSS-LMS algorithm has considerably better performance than conventional LMS, RLS, normalized LMS (N-LMS) and the other VSS-LMS algorithms.

This paper proposes a novel de-noising algorithm based on ensemble empirical mode decomposition (EEMD) and the variable step size least mean square (VS-LMS) adaptive filter. The noise of the high frequency part of spectrum will be removed through EEMD, and then the VS-LMS algorithm is utilized for overall de-noising. The EEMD combined with VS-LMS algorithm can not only preserve the detail and envelope of the effective signal, but also improve the system stability. When the method is used on pure R6G, the signal-to-noise ratio (SNR) of Raman spectrum is lower than 10 dB. The de-noising superiority of the proposed method in Raman spectrum can be verified by three evaluation standards of SNR, root mean square error (RMSE) and the correlation coefficient ρ.

A new strategy is proposed for deriving a variable step-size least mean squares (VSS-LMS) algorithm suited for the estimation of time-varying and frequency-selective communications channels modelled as wide sense stationary channels-uncorrelated scattering (WSS-US). The variable step size is obtained by minimising the analytical expression of the mean square weight estimation error as a function of time. Computer simulation results are presented which show that the new VSS-LMS algorithm so obtained produces performance gains in relation to the conventional LMS algorithm and for some channel models may also outperform the recursive least squares algorithm.

In code division multiple access (CDMA) systems transmitting over time-varying multipath channels, both intersymbol interference (ISI) and multiple access interference (MAI) arise. The conventional suboptimum receiver consisting of a bank of matched filters is often inefficient because interference is treated as noise. The optimum multi-user detector is too complex to be implemented at present. Four suboptimum detection techniques based on zero forcing (ZF) and minimum mean square error (MMSE) equalization with and without decision feedback (DF) are presented and compared. They combat both ISI and MAI. The computational complexity of all four equalizers is essentially the same and they are independent of the size of the data symbol alphabet. It is shown that all four equalizers considerably outperform the conventional receiver. The MMSE equalizers are superior to the corresponding ZF equalizers. Furthermore, the equalizers with DF perform better than the corresponding equalizers without DF. An algorithm termed channel sorting is introduced to reduce the impairing effect of error propagation on the equalizers with DF. >

In orthogonal frequency division multiplexing (OFDM), Fourier Transform (FT) is used as a modulation technique. To avoid inter-symbol interference (ISI) in OFDM by a time dispersive channel, a cyclic prefix (CP) is used which also reduces its spectral efficiency. wavelet packet transform (WPT) as a modulation scheme has been proposed for wireless communication. In this paper, WPT based OFDM is presented and proposed using minimum mean square error (MMSE) equalizer. Equalization is a major factor in wavelets. MMSE is proposed for wavelet based OFDM (WOFDM) based on WPT and compared with zero forcing equalizer (ZFE). The performance is measured for arbitrary magnitude finite impulse response (FIR) channels in the presence of additive white Gaussian noise (AWGN) and impulse noise. Simulation results show a clear improvement in bit error rate (BER) for MMSE over ZFE equalization technique in the presence of noise.

We examine through numerical simulations the performance of three equalizers for CDMA downlink in which the channel is frequency-selective: the traditional RAKE receiver, and chip-spaced MMSE (minimum mean square error) and ZF (zero-forcing) equalizers. These simulation results provide an upper-bound on average BER performance for users near a single transmitting base-station, in which the channel is assumed static and known. We present results for two channel models: a random 4-path multipath channel with delay spread of 10 micro seconds, and an empirically derived random multipath channel generated by the commercial software package SMRCIM. We compare the cases of diversity obtained by two spatially separated antennas to two virtual channels obtained through oversampling a single antenna's received signal. This simulation study has yielded the expected result that spatial diversity is preferable to diversity obtained via oversampling. Furthermore, the MMSE always out-performs both RAKE and ZF equalizers.

The time-varying impulse response of rapidly fading mobile communication channels is expanded over a basis of complex exponentials that arise due to Doppler effects encountered with multipath propagation. Blind methods are reviewed for estimating the bases' parameters and the model orders. Existing second-order methods are critiqued and novel algorithms are developed for blind identification, direct, zero-forcing equalization and minimum mean square error (MMSE) equalization by combining channel diversity with temporal (fractional sampling) and/or spatial diversity which becomes available with multiple receivers. Illustrative simulations are also presented.

This paper introduces four block joint detection (JD) receivers which combining the orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA) techniques, i.e., OFDM-CDMA receiver. The performance of the OFDM-CDMA receiver with orthogonal and non-orthogonal spreading sequences is investigated in mobile radio channels. The sequences considered as spreading codes are orthogonal Walsh-Hadamard, Orthogonal Gold, Gold and maximim length sequences or m - sequences. The JD algorithms for the OFDM- CDMA receiver are Zero Forcing Block Linear Equalizer (ZF- BLE), Minimum Mean Square Error Block Linear Equalizer (MMSE-BLE), with and without decision feedback (DF). Time- domain equalization does not require DFT or FFT operations and can be used to compensate the channel fading effect. Hence for hardware implementation, the time domain interpretation can lead to a more efficient structure when compared with the frequency domain approach. The bit error rate (BER) performance comparisons of different spreading codes and equalizers are shown in the simulations.

This paper presents the impact of synchronization errors on the performance of a downlink multicarrier two-dimensional spreading OFDM-CDMA system. This impact is measured by the degradation of the signal to interference and noise ratio (SINR) obtained after despreading and equalization. The contribution of this paper is twofold. First, we use some properties of random matrix and free probability theories to derive a new expression of the SINR. This expression is then independent of the actual value of the spreading codes while still accounting for the orthogonality between codes. This model is validated by means of Monte Carlo simulations. Secondly, the model is exploited to derive the SINR degradation of OFDM-CDMA systems due to synchronization errors which include a timing error, a carrier frequency offset, and a sampling frequency offset. It is also exploited to compare the sensitivities of MC-CDMA and MC-DS-CDMA systems to these errors in a frequency selective channel. This work is carried out for zero-forcing and minimum mean square error equalizers.

Recently, multicarrier modulations is becoming the chosen modulation technique for wireless communications. The Wavelet Packet Modulation (WPM) is applied as a novel alternative to the Orthogonal Frequency Division Multiplexing (OFDM). In this paper, Wavelet Packet Transform based multicarrier modulation is presented and introduced using both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) equalizers. They are proposed and compared for Wavelet based multicarrier modulation. First we have evaluated the performance of the classical OFDM and the WPT in term of Power Average Peak Ratio (PAPR). Second, the performances of proposed schemes are qualified for three types of wireless channels in the presence of Additive White Gaussian Noise (AWGN). Results of simulation illustrate a notable enhancement in Bit Error Rate (BER) for MMSE over ZFE equalization technique for different types of channel.

The aim of this research is to develop a non-linear blind estimator able to represents a Broadband Radio Access Networks (BRAN) channels. In the one hand, we have used Higher Order Statistics (HOS) theory to build our algorithm. Indeed, we develop a non-linear method based only on fourth order cumulants for identifying the diagonal parameters of quadratic systems. In the other hand, the developed approach is applied to estimate the experimental channels, BRAN A, C and E data normalized for MC-CDMA, in non-linear case. However, the estimated data will be used in the blind equalization. The simulation results in noisy environment and for different signal to noise ratio (SNR) show the accuracy of develop estimator blindly (i.e., without any information about the input) with non-Gaussian signal input. Furthermore, in part of blind equalization problem the obtained results, using Zero forcing (ZF) and Minimum Mean Square Error (MMSE) equalizers, demonstrate that the proposed algorithm is very adequate to correct channel distortion in term the Bit Error Rate (BER). Finally, these estimated data present a necessary asset for conducting validation experiments, and can be also used as a baseline.