| Article Details : |
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| | | Article Name : | | | New Approach of Performance Analysis of RLS
Adaptive Filter Using a Block-wise Processing | | Author Name : | | | HAMZÉ HAIDAR ALAEDDINE, ALAA A. GHAITH, MOSTAFA AL-SAHILI, MOUENES FADLALLAH | | Publisher : | | | Bridge Center | | Article URL : |  | | | Abstract : | | | This paper presents an efficient implementation of adaptive
filtering for echo cancelers for teleconference systems during single-talk
situation. The problem of echo cancellation is recurrent for all modern
communication systems. The general solution consists to estimate the
room impulse response and reproduce the echo signal in order to
subtract it from the received signal and then reduce its effect at the farend user side and consequently improves the conversation quality.
Several types of adaptive algorithms exist in the estimation process.
The most popular echo canceler (EC) uses Least Mean Squares (LMS)
or Recursive Least Squares (RLS) adaptive filter. In practice, the
choice of an algorithm must be made bearing in mind some
fundamental aspects:
- Faster convergence in the presence of large variations in the
far-end speech: the acoustic echo cancellation system must provide an
echo reduction of about 24 dB for delays lower than 25 ms and of
about 40 dB for delays exceeding 25 ms. - Reduced computational complexity algorithms.
The literature shows that the RLS algorithm is more efficient
than the LMS algorithm. It allows to reach an echo reduction of 46 dB
which is large enough than the required threshold. Moreover, it
presents a faster convergence compared to the LMS algorithm during
single-talk situation. However, the implementation of the RLS
algorithm applied to acoustic echo cancellation system has shown the
disadvantage of requiring a strong computational complexity. To
reduce the computational cost of this algorithm, we propose a new
version of the RLS algorithm based on the Fast Fourier Transform
(FFT) and on the recursive operation over a block of N samples instead
of one sample.
Simulation results show that the proposed algorithm has a
faster adaptation convergence, during single-talk situation, and reduce
considerably the hardware resources needed for the implementation
and the execution time in terms of N.
| | Keywords : | | | Acoustic Echo Cancellation, Adaptive Filter, Adaptive
algorithm, LMS Algorithm, RLS Algorithm. |
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