Equaliser for digital communication

2012 20th Signal Processing and Communications Applications Conference (SIU)

2012

ÖZETÇEBu bildiride, en küçük ortalama kareler (Least Mean Squares, LMS) algoritmasının yavaş yakınsama dezavantajına bir çözüm olarak kanal çıkışı ve hata işareti arasındaki çapraz ilintiyi kullanan yeni bir değişken adım büyüklüklü LMS (Variable Step Size LMS, VSS-LMS) algoritması önerilmektedir. Yeni algoritma sabit adım büyüklüklü klasik LMS algoritmasının yakınsama hızı ve doğruluğu arasındaki uyumsuzluğa çözüm sunmaktadır. Önerilen yöntemin başarımını doğrulamak için frekans seçici Rayleigh sönümlemeli kanallarda bilgisayar benzetimleri yapılmaktadır. HIPERLAN/1 standardını kullanarak elde edilen benzetim sonuçları önerilen VSS-LMS algoritmasının klasik LMS, RLS, normalize edilmiş LMS (Normalized LMS, N-LMS) ve diğer VSS-LMS algoritmalarından daha iyi başarıma sahip olduğunu göstermektedir. ABSTRACT A novel variable step size least mean squares (VSS-LMS) algorithm employing cross correlation between channel output and error signal has been proposed as a solution to disadvantage of slow convergence of LMS algorithm. The new algorithm resolves the conflict between the convergence rate and precise of the fixed step-size conventional LMS algorithm. Computer simulations have been performed to verify the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed VSS-LMS algorithm has considerably better performance than conventional LMS, RLS, normalized LMS (N-LMS) and the other VSS-LMS algorithms.

Section: Lms Güncellemeunclassified

A novel Variable Step Size LMS algorithm employing cross correlation between channel output and error signal

Çakir

2012 20th Signal Processing and Communications Applications Conference (SIU)

2012

“…In order to mitigate the effects of these impairments, several channel estimation and equalization methods have been developed in the last few decades. One of the best ways to cancel these effects is to use an equalizer filter that eliminates the ISI while combining the multipath energy 1–3. In practice, linear transversal equalizers (LTE) and decision feedback equalizers (DFE) are the most common structures used 4, 5.…”

Section: Introductionmentioning

confidence: 99%

A novel variable step size adjustment method based on channel output autocorrelation for the LMS training algorithm

2011

Int J Communication

SUMMARYThe least mean squares (LMS) algorithm, the most commonly used channel estimation and equalization technique, converges very slowly. The convergence rate of the LMS algorithm is quite sensitive to the adjustment of the step-size parameter used in the update equation. Therefore, many studies have concentrated on adjusting the step-size parameter in order to improve the training speed and accuracy of the LMS algorithm. A novel approach in adjusting the step size of the LMS algorithm using the channel output autocorrelation (COA) has been proposed for application to unknown channel estimation or equalization in low-SNR in this paper. Computer simulations have been performed to illustrate the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed variable step size LMS (VSS-LMS) algorithm has considerably better performance than conventional LMS, recursive least squares (RLS), normalized LMS (N-LMS) and the other VSS-LMS algorithms.

“…One of the best ways to cancel these effects is to use an equalizer filter that eliminates the ISI while combining the multipath energy [1][2][3]. Future wireless communication systems are expected to support a wide range of high-quality services that require high data rates.…”

Section: Introductionmentioning

confidence: 99%

“…In order to mitigate the effects of these impairments, several channel estimation and equalization methods have been developed in the last few decades. One of the best ways to cancel these effects is to use an equalizer filter that eliminates the ISI while combining the multipath energy [1][2][3]. In practice, linear transversal equalizers (LTE) and decision feedback equalizers (DFE) are the most common structures used [4,5].…”

Section: Introductionmentioning

confidence: 99%

A novel variable step size adjustment method based on channel output autocorrelation for the LMS training algorithm

2010 IEEE 18th Signal Processing and Communications Applications Conference

2010

The least mean squares (LMS) algorithm, the most commonly used channel estimation and equalization technique, converges very slowly. The convergence rate of the LMS algorithm is quite sensitive to the adjustment of the step-size parameter used in the update equation. Therefore, many studies have concentrated on adjusting the step-size parameter in order to improve the training speed and accuracy of the LMS algorithm. A novel approach in adjusting the step size of the LMS algorithm using the channel output autocorrelation (COA) has been proposed for application to unknown channel estimation or equalization in low-SNR in this paper. Computer simulations have been performed to illustrate the performance of the proposed method in frequency selective Rayleigh fading channels. The obtained simulation results using HIPERLAN/1 standard have demonstrated that the proposed variable step size LMS (VSS-LMS) algorithm has considerably better performance than conventional LMS, recursive least squares (RLS), normalized LMS (N-LMS) and the other VSS-LMS algorithms.