New FSE Based on MCMA and PLL

2013 ◽  
Vol 760-762 ◽  
pp. 467-471
Author(s):  
Yan Liu ◽  
Yuan Min Li

In the digital transmission system, an efficient fractionally-spaced equalizer (FSE) for blind equalization based on modified constant modulus algorithm (MCMA) and phase locked loop (PLL) is proposed. Comparing with conventional FSE based on famous CMA, the proposed algorithm has not only lower steady-state mean square error and faster convergence rate but also the ability to recover carrier phase rotation. The efficiency of the method is proved by computer simulation.

2013 ◽  
Vol 760-762 ◽  
pp. 478-482
Author(s):  
Hui Juan Gao ◽  
Yan Liu

In the digital transmission system, constant modulus algorithm (CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constant modulus signals such as higher-order QAM signals, the CMA just achieve moderate steady-state mean square error (MSE). So a new dual-mode fractionally-spaced equalization (FSE) suitable for high-order QAM signals is proposed, which makes full use of the character which is that the high-order QAM signals have the different modulus. This algorithm uses the FSE based on CMA as the basal mode and in the second mode it uses the FSE based on variable modulus algorithm. The simulation results show that compared with CMA the proposed algorithm has faster convergence rate and lower steady-state mean square error.


2010 ◽  
Vol 108-111 ◽  
pp. 363-368 ◽  
Author(s):  
Wei Rao ◽  
Ye Cai Guo ◽  
Min Chen ◽  
Wen Qun Tan ◽  
Jian Bing Liu ◽  
...  

The paper proposes a concurrent constant modulus algorithm (CMA) and decision-directed (DD) scheme for fractionally-spaced blind equalization. The proposed algorithm makes full use of the advantages of CMA and DD algorithm. A novel rule to control the adjustment of DD’s tap weights vector is proposed which avoids the hard switch between CMA and DD in practice. Simulations with underwater acoustic channels are used to compare the proposed algorithm with the famous CMA. And the simulation results show that the proposed algorithm has faster convergence rate and lower steady state mean square error.


Author(s):  
Zhiyong Liu ◽  
Zhoumei Tan ◽  
Fan Bai

AbstractTo improve the transmission efficiency and facilitate the realization of the scheme, an adaptive modulation (AM) scheme based on the steady-state mean square error (SMSE) of blind equalization is proposed. In this scheme, the blind equalization is adopted and no training sequence is required. The adaptive modulation is implemented based on the SMSE of blind equalization. The channel state information doesn’t need to be assumed to know. To better realize the adjustment of modulation mode, the polynomial fitting is used to revise the estimated SNR based on the SMSE. In addition, we also adopted the adjustable tap-length blind equalization detector to obtain the SMSE, which can adaptively adjust the tap-length according to the specific underwater channel profile, and thus achieve better SMSE performance. Simulation results validate the feasibility of the proposed approaches. Simulation results also show the advantages of the proposed scheme against existing counterparts.


2014 ◽  
Vol 548-549 ◽  
pp. 766-770
Author(s):  
Ke Cheng Leng ◽  
Cheng Bie ◽  
Xi Gong ◽  
Ran Xu ◽  
Ye Cai Guo

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.


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