Subband Filtering Techniques Research Articles

Combined Subband-Subcarrier Spectral Shaping in Multi-Carrier Modulation Under the Excess Frame Length Constraint

This paper investigates spectral shaping of multi-carrier-modulation waveforms based on combination of Nyquist windowing and subband filtering. The combined windowing/filtering allows simultaneous control on both subcarrier and subband spectra. When compared with the existing Nyquist windowing or subband filtering techniques under a fixed excess frame length constraint, the proposed scheme offers reduced sensitivity to carrier frequency and symbol timing offsets. Establishing an analytical tool based on the error spectrum stack consisting of the error signals evaluated at different signal delay positions, we explore the window-filter trade-off and provide the minimum interference power solution for given ranges of carrier frequency and symbol timing offsets. Our design targets low-latency applications having no provisions for high-precision synchronization and having potential need for spectrum aggregation.

Improvements and analysis of nonlinear parallel behavioral models

This article performs an analysis of current limitations regarding the extraction of parallel behavioral models to reproduce the power amplifier (PA) nonlinear behavior and its dynamics. To overcome these limitations, a general preprocessing block that clearly improves the identification capabilities shown by classical parallel structures is proposed. It follows the principle of separating both static and dynamic nonlinear behavior of the PA to obtain a better identification performance. A comparison with common parallel configurations using linear estimation is performed, to highlight the benefits of using the preprocessing structure. Furthermore, a new nonlinear parallel structure using sub-band filtering techniques is also proposed. For the models extraction and comparison, four types of noise-free simulated data presenting different levels of nonlinearities and memory, as well as a measured signal obtained from a laboratory amplifier have been considered. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.

Digital subband filtering predistorter architecture for wireless transmitters

In this paper, a new architecture for baseband digital predistortion dedicated to wide-band transmissions is presented. The proposed predistorter consists of a cascade of a static lookup-table-based predistorter and a subband filtering block. The subband filtering technique is used to improve the correction bandwidth limitation of conventional architectures. The cases of four- and eight-subband decomposition were considered and compared to the case where the full-band signal is processed. This revealed that the subband processing results in a better sensitivity and an independent tuning ability of the predistorter at each subband. In addition, it was shown that, in the proposed predistorter, the computational complexity and the required processing speed are reduced proportionally to the number of subbands. Moreover, in an adaptive digital predistortion context, a quicker convergence can be achieved. Experimental validation of the subband-based predistortion concept was successfully carried on a 100-W peak envelop power lateral double diffused metal-oxide semiconductor power amplifier.

Directional clutter removal of aerial digital images using X-ray wavelet transform and Markov random field

Aerial images are one of the primary data sources for underwater oceanographic studies. These images are often corrupted by clutter induced by surface water waves. Removal of the wave clutter from these images is an important preprocessing step for accurate assessment of information. In this paper, we introduce a novel technique combining the X-ray wavelet transform (XWT) with Markov random field (MRF) for directional noise removal. Surface water waves are classified according to their features into two types: ripple wave (long-wave) and spark wave (short-wave). We show in our numerical experiments that by performing XWT along the direction of wave propagation, the wave clutter can he successfully detected. To remove long-waves, resampling and subband filtering techniques are used. To remove short-waves, on the other hand, a spectral-spatial maximum exclusive mean (SMEM) filter is used in this study. Finally, because of the directional characteristic of the clutter, nonisotropic MRF is introduced into the post-processing step to refine the output. Experimental results show that one can remove both kinds of wave clutter with only small background distortion using the proposed hybrid algorithm.