Recently a framework has been introduced within which a large number of classical and modern adaptive filter algorithms can be viewed as special cases. Variable Step-Size (VSS) normalized least mean square (VSSNLMS) and VSS Affine Projection Algorithms (VSSAPA) are two particular examples of the adaptive algorithms that can be covered by this generic adaptive filter. In this paper, we introduce a new VSS Partial Rank (VSSPR) adaptive algorithm based on the generic VSS adaptive filter and use it for channel equalization. The proposed algorithm performs very well in attenuating noise and inter-symbol interference (ISI) in comparison with the standard NLMS and the recently introduced AP algorithms.
In this paper, we propose novel low-complexity adaptive channel estimation techniques for mobile wireless channels in presence of Rayleigh fading, carrier frequency offsets (CFO) and random channel variations. We show that the selective partial update of the estimated channel tap-weight vector offers a better trade-off between the performance and computational complexity, compared to the full update of the estimated channel tap-weight vector. We evaluate the mean-square weight error of the proposed methods and demonstrate the usefulness of its via simulation studies.Index Terms-Adaptive filter, channel estimation, carrier frequency offsets, mean-square weight error, multipath channel, Rayleigh fading.
In many application of noise cancellation, the changes in signal characteristics could be quite fast. This requires the utilization of adaptive algorithms, which converge rapidly. Least Mean Squares (LMS) adaptive filters have been used in a wide range of signal processing application. The Recursive Least Squares (RLS) algorithm has established itself as the "ultimate" adaptive filtering algorithm in the sense that it is the adaptive filter exhibiting the best convergence behavior. Unfortunately, practical implementations of the algorithm are often associated with high computational complexity and/or poor numerical properties. Recently adaptive filtering was presented that was based on Matching Pursuits, have a nice tradeoff between complexity and the convergence speed. This paper describes a new approach for noise cancellation in speech enhancement using the new adaptive filtering algorithm named fast affine projection algorithm (FAPA). The simulation results demonstrate the good performance of the FAPA in attenuating the noise.
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