Blended CMA: smooth, adaptive transfer from CMA to DD-LMS

Litwin, L.; Zoltowski, M.D.; Endres, T.J.; Hulyalkar, S.N.

doi:10.1109/wcnc.1999.796764

Cited by 14 publications

(4 citation statements)

References 8 publications

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“…Constant modulus algorithm (CMA) proposed by Godard is the most common used blind equalization technique due to its good convergence performance [7]. Decision-Directed (DD) algorithm is often used when the eye pattern of the output is opened to some extent [8], it contains phase information and can improve the steady-state performance as well as correct the constellation phase rotation.…”

Section: Algorithmsmentioning

confidence: 99%

Investigation of 20Gb/s WDM-PON transmission over 40-km employing 16QAM signal with blind equalization

Zhang

Liu

et al. 2013

2013 8th International Conference on Communications and Networking in China (CHINACOM)

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We apply 16QAM into the downstream modulation in long reach WDM-PON and utilize blind equalization at the ONU receiver to improve the system performance. Simulation results indicate that, with the blind equalization, after transmission over 40-km single mode fiber (SMF) at the speed of 20Gb/s, BER is remained below 10 -3 at -17.2dBm receive sensibility. The results also show that the blind equalization is able to suppress the crosstalk between two adjacent WDM channels spacing 25GHz and thus improve the constellation phase rotation.

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Section: Algorithmsmentioning

confidence: 99%

Investigation of 20Gb/s WDM-PON transmission over 40-km employing 16QAM signal with blind equalization

Zhang

Liu

et al. 2013

2013 8th International Conference on Communications and Networking in China (CHINACOM)

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“…Moreover, PS might hinder the performance obtained by the existing DSP algorithms. Traditional time-domain blind equalization algorithms, including CMA [ 10 ] and the Decision-Directed Least Mean Square (DD-LMS) algorithm [ 11 ], are usually affected by the uneven occurrence probability of constellation points when working on PS-QAM signals [ 12 ]. The truncated PS-64QAM modulation format is designed to obtain a more suitable shaping depth, and make the shaped signal better suited to the CMA equalization [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

4Gbaud PS-16QAM D-Band Fiber-Wireless Transmission over 4.6 km by Using Balance Complex-Valued NN Equalizer with Random Oversampling

Xie

2023

Sensors

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D-band (110–170 GHz) is a promising direction for the future of 6th generation mobile networks (6G) for high-speed mobile communication since it has a large available bandwidth, and it can provide a peak rate of hundreds of Gbit/s. Compared with the traditional electrical approach, photonics millimeter wave (mm-wave) generation in D-band is more practical and effectively overcomes the bottleneck of electrical devices. However, long-distance D-band wireless transmission is still limited by some key factors such as large absorption loss and nonlinear noises. Deep neural network algorithms are regarded as an important technique to model the nonlinear wireless behavior, among which the study on complex-value equalization is critical, especially in coherent detection systems. Moreover, probabilistic shaping is useful to improve the transmission capacity but also causes an imbalanced machine learning issue. In this paper, we propose a novel complex-valued neural network equalizer coupled with balanced random oversampling (ROS). Thanks to the adaptive deep learning method for probabilistic shaping-quadrature amplitude modulation (PS-QAM), we successfully realize a 135 GHz 4Gbaud PS-16QAM with a shaping entropy of 3.56 bit/symbol wireless transmission over 4.6 km. The bit error ratio (BER) of 4Gbaud PS-16QAM can be decreased to a soft-decision forward error correction (SD-FEC) with a 25% overhead of 2×10−2. Therefore, we can achieve a net rate of an 11.4 Gbit/s D-band radio-over-fiber (ROF) delivery over 4.6 km air free wireless distance.

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“…However, a particular problem of the CMA is that its convergence rate may not be fast enough, and its steady-state mean square error (MSE) may not be low enough for the system to obtain adequate performance. Another problem of CMA is that it is only amplitude-dependent, and knowledge about the signal constellation is dismissed [2,[5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Steady-state MSE analysis of the multimodulus blind equalization algorithm in QAM communication systems

Rao

2011

SPIE Proceedings

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The constant modulus algorithm (CMA) for blind equalization requires a separate carrier-recovery system for phase recovery. A modified CMA, called the multimodulus algorithm (MMA), which may perform joint blind equalization and carrier recovery without the need for a separate carrier-recovery system for quadrature amplitude modulation (QAM) signal constellations. This letter mathematically analyzes the steady-state mean square error (MSE) of MMA. Analysis results indicate that MMA produces 50% fewer steady-state MSE than CMA.

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Blended CMA: smooth, adaptive transfer from CMA to DD-LMS

Cited by 14 publications

References 8 publications

Investigation of 20Gb/s WDM-PON transmission over 40-km employing 16QAM signal with blind equalization

Investigation of 20Gb/s WDM-PON transmission over 40-km employing 16QAM signal with blind equalization

4Gbaud PS-16QAM D-Band Fiber-Wireless Transmission over 4.6 km by Using Balance Complex-Valued NN Equalizer with Random Oversampling

Steady-state MSE analysis of the multimodulus blind equalization algorithm in QAM communication systems

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