A 60-GHz RoF System Employing Variable Step Size LMS Equalizer with Fast Convergence Speed

Author(s):  
Siming Liu ◽  
Guansheng Shen ◽  
Huiping Tian
2019 ◽  
Vol 67 (6) ◽  
pp. 405-414 ◽  
Author(s):  
Ningning Liu ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Hui Guo ◽  
Bin Gao ◽  
...  

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.


2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Lihua Yang ◽  
Shuyong Liu ◽  
Haipeng Zhang ◽  
Haiping Wu ◽  
Haifeng Li ◽  
...  

Active control is an effective way to suppress low-frequency mechanical vibration. However, with applications to submarine equipment, there are still some shortcomings due to vibration coupling and multifrequency complex excitation. In this paper, a novel hybrid improved adaptive control strategy, feedback and online identification filtered-x LMS, namely, FOFxlms, is proposed, which introduces the residual errors to correct variable step-size, uses the estimated primary path to improve online identification, and applies internal feedback to compensate for the feedforward control. Then the FOFxlms algorithm is applied to a double-layer vibration isolation system of submarine rotating equipment, and the simulation results show that the normalized variable step-size with residual error can effectively improve convergence speed, the internal feedback can efficaciously compensate for steady-state control accuracy, and the online identification can dynamically identify the time-varying characteristics of the secondary path. The vibration reduction efficiency of Fxlms, FFxlms, and FOFxlms increases for the fundamental frequency vibration; the control effect and convergence speed are also enhanced in turn.


2004 ◽  
Vol 17 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Karen Egiazarian ◽  
Pauli Kuosmanen ◽  
Ciprian Bilcu

Due to its simplicity the adaptive Least Mean Square (LMS) algorithm is widely used in Code-Division Multiple access (CDMA) detectors. However its convergence speed is highly dependent on the eigen value spread of the input covariance matrix. For highly correlated inputs the LMS algorithm has a slow convergence which require long training sequences and therefore low transmission speeds. Another drawback of the LMS is the trade-off between convergence speed and steady-state error since both are controlled by the same parameter, the step-size. In order to eliminate these drawbacks, the class of Variable Step-Size LMS (VSSLMS) algorithms was introduced. In this paper, we study the behavior of some algorithms belonging to the class of VSSLMS for training based multiuser detection in a CDMA system. We show that the proposed Complementary Pair Variable Step-Size LMS algorithms highly increase the speed of convergence while reducing the trade-off between the convergence speed and the output error.


This paper shows novel implementation of Constant Modulus Algorithm (CMA) using LMS update with variable step size (VSS). Fast convergence and good quality reception of 4-QAM has been achieved.


2012 ◽  
Vol 182-183 ◽  
pp. 1810-1815
Author(s):  
Shun Lan Liu ◽  
Lin Wang

A novel decision-directed Modified Constant Modulus Algorithm (DD-MCMA) was proposed firstly. Then a constellation matched error (CME) function was added to the cost function of DD-MCMA and CME-DD-MCMA algorithm was presented. Furthermore, we improve the CME-DD-MCMA by replacing the fixed step with variable step size, that is VSS-CME-DD-MCMA algorithm. The simulation results show that the proposed new blind equalization algorithms can tremendously accelerate the convergence speed and achieve lower residual inter-symbol interference (ISI) than MCMA, and among the three proposed algorithms, VSS-CME-DD-MCMA has the fastest convergence speed and the lowest residual ISI, but it has the largest computation complexity.


2005 ◽  
Vol 05 (03) ◽  
pp. L387-L395
Author(s):  
JIAN-DA WU ◽  
HAI-PING LIN ◽  
RAN-JEN HUNG

Acoustic feedback often limits the maximum usable gain of acoustic systems and degrades the overall system response. It is well known to be detrimental that the system stability and performance must be taken into account in system design. Most of the conventional methods for acoustic feedback cancellation in an acoustic system are based primarily on an adaptive filter with the least-mean-square (LMS) error algorithm. Unfortunately, convergence speed is often limited when a sound source or a filtering plant is varied, because the learning process of the adaptive algorithm fails to respond fast enough to changing operational conditions. This report proposes a variable step-size affine-projection algorithm (VSS APA) for acoustic feedback cancellation in audio systems. The proposed adaptive filter is based on the filtering affine-projection algorithm with variable step-size for improving convergence speed in acoustic feedback cancellation. A performance evaluation and simulation comparison has been conducted to compare the proposed algorithm and various traditional adaptive filtering algorithms.


2014 ◽  
Vol 513-517 ◽  
pp. 3736-3739 ◽  
Author(s):  
Xue Li Wu ◽  
Zi Zhong Tan ◽  
Liang Gao

. Aiming at the disadvantage of the variable step size LMS adaptive filtering algorithms' convergence speed contradicting its steady-state error, a novel non-liner functional relationship between μ (n) and error signal e (n) was established. On the basis of the functional relationship, a new algorithm of variable step size LMS adaptive filtering was presented. The step size factor of the new algorithm is adjusted by the absolute value of the product of the current and former errors. It also uses the absolute estimation error compensation terms disturbance to speed up the convergence of adaptive filter tap weight vector. At the same time, the algorithm considers the relationship between step length of the last iteration and the former M error signal. As a result the algorithm has higher convergence characteristic and small steady state error. The theoretical analysis and simulation results show that the new algorithm has faster convergence speed, lower steady state error and better performance of noise suppression, also show the overall performance of this algorithm exceeds some others condition.


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