Multi-modulus Blind Equalization Algorithm Research Articles

Robust multimodulus blind equalization algorithm for multilevel QAM signals in impulsive noise

As a blind equalization algorithm, the fractional lower-order statistics based multimodulus algorithm (FLOS-MMA) is suitable for equalizing multilevel quadrature amplitude modulation (QAM) signals in impulsive noise. However, the equalization performance of FLOS-MMA is severely degraded in strong impulsive noise because the first-order gradient of the cost function constrains the ability of FLOS to suppress large outliers in the equalizer output signal and is sensitive to large outliers in the equalizer input signal. To enhance the robustness of multimodulus blind equalization algorithm against impulsive noise, a FLOS based momentum fractional-order multimodulus algorithm (FLOS-MFOMMA) is proposed in this paper. The proposed algorithm mitigates the adverse effects of impulsive noise on the updating of equalizer coefficients by utilizing the fractional-order gradient and accelerates the convergence speed by incorporating a momentum term. Then, the steady-state excess mean square error and the computational complexity of FLOS-MFOMMA are analyzed theoretically. Finally, numerical simulations, for equalizing 16-QAM signals under impulsive noise environments, show that the proposed algorithm is superior to FLOS-MMA in terms of robustness and convergence speed.

OF-FSE: An Efficient Adaptive Equalization for QAM-Based UAV Modulation Systems

Quadrature amplitude modulation (QAM) is one of the essential components of unmanned 1 aerial vehicle (UAV) communications. However, the output signal accuracy of QAM deteriorates dramatically and even collapses in the case of UAVs in a harsh channel environment. This is due to the fractionally spaced equalization based on the multi-modulus blind equalization algorithm being implemented prior to carrier synchronization in QAM-based UAV modulation systems. The carrier frequency offset from the harsh channel signal thus contributes to the significantly degraded performance of MMA by suffering the fractionally spaced equalization. Therefore, in this paper, a novel offset feedback fractionally spaced equalization architecture for UAVs to eliminate the carrier frequency offset is first proposed. In this architecture, the carrier frequency offset allows estimated and incorporation into the input signal of fractionally spaced equalization to compensate for the offset. Moreover, a new multi-modulus decision-directed algorithm is presented for the novel architecture to improve the received signal accuracy of UAVs further. It enables adaptive optimization of the convergence process in accordance with the dynamic UAV communication environment employing the multi-modulus blind equalization algorithm and decision-directed blind equalization algorithm (MDD). Simulation results demonstrate the effectiveness of the OF-FSE framework in enabling the QAM-based UAV modulation systems operation in harsh channel scenarios. Moreover, the performance of the presented new MDD algorithm compared with baseline approaches is also confirmed.

Demultiplexing based on frequency-domain multimodulus blind equalization for mode division multiplexing system

In this paper, the frequency-domain multimodulus blind equalization algorithm (FD-MMA) is proposed to implement mode demultiplexing for a 2 × 2 mode division multiplexing system. The performance of this algorithm is compared with the time-domain MMA (TD-MMA) and frequency-domain decision-directed least mean square algorithm (FD-LMS). Compared with TD-MMA, the FD-MMA reduces the computational complexity significantly while maintaining the same performance. Compared with FD-LMS, the FD-MMA has a better performance in BER with similar computational complexity. As for 16QAM format, the average OSNR of FD-MMA improves 2.5 dB at a BER of 10−3; as for 64QAM, it has an improvement of 7 dB.

Multimodulus blind equalization algorithm based compensation for I/Q imbalance in OFDM optical fiber communication

The performance enhancement using multimodulus blind equalization algorithm for compensating in-phase/ quadrature-phase (I/Q) mismatch in orthogonal frequency division multiplexing optical communication system is investigated. The mathematical theory of I/Q imbalance is analyzed. Then, a compensation scheme with two-tap equalizer is implemented, with this scheme, the joint compensation of transmitter and receiver with optical channel that contains noise attenuation and chromatic dispersion is realized. Simulation shows that the performance degradation caused by I/Q imbalance can be compensated by the scheme with multimodulus blind equalization algorithm effectively regardless of the modulation order and channel distortion.

Mode demultiplexing based on multimodulus blind equalization algorithm

In this paper, the multimodulus blind equalization algorithm (MMA) is proposed to implement mode demultiplexing in 2×2 MDM system. The principle of MIMO equalization based on MMA has been illustrated. The performance of this algorithm is compared with the DD-LMS (Decision-directed Least Mean Square Algorithm). Simulation shows that the MMA algorithm successfully implements demultiplexing. When 4QAM, 16QAM and 64QAM modulation formats are used, the MMA algorithm achieves a good de-multiplexing performance without complex decision process. Furthermore, some properties such as transparent to modulation format and no need of phase estimation, make the algorithm more suitable for mode demultiplexing.

An Optimized Combination of Frequency Domain Adaptive Equalizers

In order to overcome the defects of the high computational loads and selecting the threshold of mean square error (MSE) for time domain decision-directed constant modulus blind equalization algorithm (DD+CMA), a frequency domain parallel decision multi-modulus blind equalization algorithm based on frequency domain MMA(FMMA) and frequency domain LMS (FLMS) algorithm is proposed. The proposed algorithm is composed of the FMMA and FLMS, and the FMMA and FLMS run automatically in soft switching parallel manner. In running process, it is not necessary to selecting the threshold of the MSE. Moreover, the computational loads can be reduced by circular convolution in the frequency domain signals instead of linear one of the time domain signals. Simulation results show that performance of the proposed algorithm outperforms the FLMS and the FMMA algorithm.

Improved weighted multi-modulus blind equalization algorithm based on non-linear function of weighting factor

In order to improve the blind equalization performance of the weighted multimode algorithm,an improved weighted multi-modulus blind equalization algorithm based on a non-linear function of weighting factor was proposed in this paper.The new algorithm used a nonlinear relationship between the mean square error and the weighting factor to improve the speed of convergence and improve the adaptive capacity to different signal-to-noise ratio.In the converging process of the algorithm,with the mean square error decreased,the value of the weighting factor increased gradually.It adjusted the modulus value of the algorithm dynamically,and made the error model match with the signal constellation accurately to reduce the steady-state mean square error.The theoretical analysis and simulation results show that the proposed algorithm reduces the steady-state mean square error,and improves the convergence rate.

Quadratic Inverse Function Tsallis Entropy Multi-modulus Blind Equalization Algorithm

In underwater acoustic communication systems, inter-symbol interference (ISI) caused by communication channel distortion is the main factor affecting the quality of communication. Aiming at the shortcomings of computational complexity, slow convergence rate, and poor stability of Multi-Modulus Algorithm (MMA), a quadratic inverse function Tsallis entropy of Cascade Multi-Modulus blind equalization Algorithm (TCMMA) was proposed. In the proposed algorithm, quadratic inverse function Tsallis entropy is fused with Parzen window probability density estimation method, and directly used as the cost function in cascade blind equalizer to reduce the residual mean square error, and the normalized wavelet transform is used to speed up the convergence speed. The simulation results with underwater acoustic channel show the superiority of the proposed algorithm. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2371

Orthogonal Wavelet Transform Dynamic Weighted Multi-Modulus Blind Equalization Algorithm Based on Dynamic Particle Swarm

For improving the equalization performance of higher-order QAM signals, orthogonal Wavelet transform dynamic Weighted Multi-Modulus blind equalization Algorithm based on the Dynamic Particle Swarm Optimization(DPSO-WWMMA) is proposed. In this proposed algorithm, dynamic particle swarm optimization algorithm and orthogonal wavelet transform are introduced into dynamic Weighted Multi-Modulus blind equalization Algorithm(WMMA). Accordingly, the equalizer weight vector can be optimized by Dynamic Particle Swarm Optimization(DPSO) algorithm, the autocorrelation of the input signals can be reduced via using orthogonal wavelet transform, and the WMMA is used to choose appropriate error model to match QAM constellations. The theoretical analyses and computer simulations in underwater acoustic channels indicate that the proposed algorithm can obtain the fastest convergence rate and the smallest steady mean square error in equalizing high-order QAM signals. So, the proposed algorithm has important reference value in the underwater acoustic communications.

Wavelet Hardware Switching Judgment Frequency Domain Weighted Multi-Modulus Blind Equalization Algorithm based on Lower Order Statistics

Wavelet Hardware Switching Judgment Frequency Domain Weighted Multi-Modulus Blind Equalization Algorithm based on Lower Order Statistics

Orthogonal wavelet transform weighted multi-modulus blind equalization algorithm based on quantum particle swarm optimization

When constant modulus blind equalization algorithm (CMA) is used to equalize high-order QAM signals, there occur the defects of the slow convergence rate and big steady mean square error. In order to overcome these disadvantages, orthogonal wavelet transform weighted multi-modulus blind equalization algorithm based on the quantum particle swarm optimization (QPSO-WTWMMA) is proposed. In this proposed algorithm, quantum particle swarm optimization algorithm and orthogonal wavelet transform are combined into weighted multi-modulus blind equalization algorithm (WMMA) according to the feature of higher-order QAM signal constellations. Accordingly, the equalizer weight vector can be optimized by QPSO algorithm, the autocorrelation of the input signals can be reduced via using orthogonal wavelet transform, and WMMA is used to choose appropriate error models to match QAM constellations. The theoretical analyses and the computer simulations in underwater acoustic channels indicate that the proposed algorithm can obtain the fastest convergence rate and the smallest steady mean square error in equalizing high-order QAM signals. So, the proposed algorithm has important reference value for the underwater acoustic communications.

Transmission of 32-Tb/s Capacity Over 580 km Using RZ-Shaped PDM-8QAM Modulation Format and Cascaded Multimodulus Blind Equalization Algorithm

In this paper, we propose a novel synthesizing method for high-speed 8-ary quadratic-amplitude modulation (QAM) optical signal generation using commercial optical modulators with binary electrical driving signals. Using this method, we successfully generated 114-Gb/s pulse-duration modulation (PDM)-8QAM optical signals. Intradyne detection of PDM-8QAM optical signals with robust blind polarization demultiplexing has been demonstrated by using a new cascaded multimodulus equalization algorithm. With return-to-zero-shaped PDM-8QAM modulation and the proposed blind polarization demultiplexing algorithm, we demonstrate transmission of a record 32-Tb/s fiber capacity (320 × 114 Gb/s) over 580 km of ultralow-loss single-mode fiber-28 fiber by utilizing C+L-band erbium-doped fiber-amplifier-only optical amplification and single-ended coherent detection technique at an information spectral efficiency of 4.0 bit/s·Hz.

Multimodulus blind equalization algorithm for cross quadrature amplitude modulation signals

The authors presented a modified multimodulus blind equalization algorithm for cross Quadrature Amplitude Modulation(QAM)signals.Based on Weighted Multimodulus Algorithm(WMMA),the proposed algorithm,which applied the improved method of Multimodulus Algorithm(MMA)to cross QAM signals,fully employed statistics of the symbols used in cross QAM signal constellations.With the help of piecewise linear moduli,it made a better match between error models and constellations.Additionally,this algorithm showed the relationship between Mean-Square Error(MSE)estimation and the weight term under various Signal-to-Noise Rate((SNR).The simulation results demonstrate that this algorithm provides superior steady-state performance,which makes it more suitable for cross QAM signals.

New multimodulus blind equalization algorithm with relaxation

A new multimodulus algorithm is presented for blind equalization of complex-valued communication channels. The proposed algorithm is obtained by solving a novel deterministic optimization criterion that constituted the dispersion minimization of a priori as well as a posteriori quantities, leading to an update equation having a particular zero-memory continuous nonlinearity. Analyses of automatic phase-recovery and interference cancellation capabilities of the proposed algorithm are provided