Fast Constant Modulus Algorithm Based on Exponential Variable Segment Error Function

2008 ◽  
Author(s):  
Wei Rao ◽  
Huijun Xu ◽  
Yecai Guo
Keyword(s):  
Error Function ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Variable Segment ◽  
Exponential Variable

Blind Adaptive Channel Equalization Using Modified CMA

2013 ◽  
Vol 658 ◽  
pp. 537-540
Author(s):  
Sun Shouyu
Keyword(s):  
Error Function ◽  
Channel Equalization ◽  
Convergence Time ◽  
Superior Performance ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Blind Channel Equalization ◽  
Blind Adaptive ◽  
Single User ◽  
Frequency Selective Channels

The constant modulus algorithm (CMA) equalizer is perhaps the best known and the most popular scheme for blind adaptive channel equalization. In this paper, a modified constant modulus algorithm (modified CMA or MCMA) is proposed by modifying its error function. We have discussed the MCMA to blind channel equalization for baud-rat sampling in single-user case. Computer simulations are provided for 8PSK signals in noise environments under frequency selective channels. Results demonstrate that the MCMA displays much superior performance to the CMA for both convergence-time and intersymbol interference (ISI) or mean square error (MSE).

Improved Constant Modulus Algorithm for Blind Equalization of QAM Signals

2014 ◽  
Vol 631-632 ◽  
pp. 824-829
Author(s):  
Emmanuel Anania Mwangosi ◽  
Cang Yan ◽  
Naveed Ur Rehman
Keyword(s):  
Steady State ◽  
Cost Function ◽  
Error Function ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Error Performance ◽  
New Approach ◽  
Slow Convergence ◽  
The Cost ◽  
State Error

The paper present new approach for improving the steady-state error performance of Constant Modulus Algorithm (CMA), it is well known that for higher level modulations such as QAM, CMA does not perform well. Several techniques have been proposed in recent years to deal with slow convergence and MSE performance of CMA. Constellation matched error has been seen to offer best performance by providing the cost function with the knowledge of the constellation symbols. New constellation match error function is studied, simulation is performed, it can be witnessed that 4dB improvement stead state error performance.

Constant Modulus Algorithm Based on Different Error Functions Weighted by Variable Coefficient

2011 ◽  
Vol 66-68 ◽  
pp. 1579-1585
Author(s):  
Qiao Xi Zhou ◽  
Ye Cai Guo
Keyword(s):  
Theoretical Analysis ◽  
Convergence Rate ◽  
Variable Coefficient ◽  
Gradient Descent ◽  
Error Function ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Error Functions

To improve equalization performance of the constant modulus algorithm (CMA), we study that error functions have an influence on the performance of the algorithm in this paper. Aiming at the character of different error functions, a new style of error function weighted by a variable coefficient is proposed. And a new CMA based on the new error function (VCMA) is proposed too. Because of variable-coefficient adjustability, the value of this new error function can become larger at the beginning of iteration and smaller at the end of iteration in the new algorithm. From gradient descent method, VCMA can have faster convergence rate and lower residual error than the CMA. Both theoretical analysis and experimental results have shown the effectiveness of the proposed algorithm.

Modified constant modulus algorithm based on bat algorithm

2021 ◽  
pp. 1-8
Author(s):  
Tongtong Xu ◽  
Zheng Xiang
Keyword(s):  
Communication Systems ◽  
Optimization Problems ◽  
Error Function ◽  
Bat Algorithm ◽  
Weight Vector ◽  
Wireless Channel ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Blind Channel Equalization ◽  
Almost All

In this work, modified constant modulus algorithm based on bat algorithm is proposed for wireless sensor communications systems. The bat algorithm is a swarm intelligence optimization algorithm, which mainly used to solve optimization problems. The proposed algorithm focused on modified constant modulus algorithm, which is also applicable to the constant modulus algorithm. The error function of blind equalization algorithm is used as the evaluation function of the bat algorithm, and then the initial value of the weight vector is calculated adaptively by the bat algorithm. Theoretical analysis is provided to illustrate that the proposed algorithm has a faster convergence speed than the original one and is suitable for almost all blind channel equalization algorithms. The simulation results support the newly proposed improved algorithm. The proposed algorithm could be applied to some more complex wireless channel environments to improve the reception performance of sensor communication systems.

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