Block LMS Research Articles

A reduced structure of the passband fractionally spaced equalizer

In this letter, we propose a reduced structure for realization of a passband fractionally spaced equalizer (FSE) using the block LMS (BLMS) algorithm. Since this structure consists of one real transversal filter, its complexity is considerably simpler than existing equalizer structures. The passband FSE using the real passband input converges to the same steady-state value as that of the FSE with the complex analytic input, but its convergence time takes twice as long.

Block realization of multirate adaptive digital filters

In this paper, we study multirate transversal adaptive digital filters (ADF's) based on the block least-mean-square (BLMS) algorithms. These include an ADF with decimation (ADFD) and an ADF with interpolation (ADFI). We first formulate these filters based on the block mean-squared error (BMSE) criterion and derive BLMS multi-rate weight-adjustment algorithms, and then study efficient realization of those filters. It is shown that the BLMS ADFD can be realized efficiently in the direct form or in the filter-bank structure both using the fast Fourier transform (FFT) and an appropriate sectioning procedure. According to our analysis of computational complexity, the FFT realization of the BLMS ADFD in the filter-bank structure is more efficient than in the direct form, and the two structures using the FFT become more efficient in comparison to the LMS ADFD as the number of weights increases. Unlike the direct form realization, the filter-bank realization of the BLMS ADFD using the FFT becomes more efficient as the decimation ratio increases. Similar results have been obtained for the BLMS ADFI. Finally, we investigate by computer simulation the effects of different weight-adjustment algorithms and several system parameters on the performances of ADFD's. The results of simulation indicate that, as expected, the convergence speed of the BLMS ADFD can be significantly improved by self-orthogonalization of weight adjustment in the frequency domain. Furthermore, the convergence factor of the self-orthogonalizing BLMS ADFD can be chosen such that the steady-state performance of the new ADFD is the same as that of the existing LMS ADFD.

A frequency-weighted block LMS algorithm and its application to speech processing

In this letter, we propose a frequency-weighted block LMS (FWBLMS) algorithm that is based on minimization of the frequency-weighted block mean-squared error. The FWBLMS algorithm has an important advantage over the time-domain LMS algorithm in that it can be designed with different frequency weighting on error signal depending on the relative significance of various frequency bands. Application of the FWBLMS algorithm in adaptive linear prediction of speech is discussed.

A reduced structure of the frequency-domain block LMS adaptive digital filter

In this letter, it is shown that the frequency-domain block LMS (FBLMS) adaptive digital filter (ADF) for the block length of one reduces to the frequency-domain LMS (FLMS) ADF. Using the relation between the two convergence factors of the FBLMS and FLMS ADFs, it is possible to predict the steady-state performance of the former from that of the latter.