Wireless LAN (WLAN) systems transmit and receive via a common frequency band. In this band, signals of other wireless applications operate on a WLAN beamformer as interferences, and so the problem in adaptive antenna is increasing the canceling performance in the presence of moving interference sources. The performance of conventional adaptive beamformer is severely degraded and the robust adaptive beamformer must be equipped with additional sensors to obtain desired performances. Therefore, in order to avoid having to install additional sensors, an efficient algorithm is necessary. In this paper, we introduce a fast adaptive algorithm with variable forgetting factor, which does not require any further additional modifications. Through computer simulations, we can obtain better performances than those of other techniques under a variety of operating conditions.

In this letter, a new extended recursive least squares (RLS) algorithm is proposed for the identification of fading channels. We extend the standard RLS algorithm by converting the linear regression model into a state-space model. The unknown terms of the extended model are obtained by estimating the values which minimize the mean squared error (MSE). The proposed algorithm has lower computational complexity than the Kalman filter combined with the hypermodel described in, and exhibits superior performance in simulation than the existing RLS algorithms, namely the exponentially weighted RLS algorithm with a fixed forgetting factor (EW-RLS), and the RLS algorithm with a variable forgetting factor (VFF-RLS).

Ryu et al.'s recent paper proposed a multiple target angle-tracking algorithm without data association. This algorithm, however, shows degraded performance on evasive maneuvering targets, because the estimated signal subspace is degraded in the algorithm. In this paper, we propose a new algorithm where, VFF-PASTd (Variable Forgetting Factor PASTd) algorithm is applied to the Ryu's algorithm to effectively handle the evasive target tracking with better time-varying signal subspace.

Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.

We propose a new context-adaptive arithmetic coding (CAAC) scheme for lossless bit rate reduction of parametric stereo (PS) in enhanced aacPlus. Based on the probability analysis of stereo parameters indexes in PS, we propose a stereo band-dependent CAAC scheme for PS. We also propose a new coding structure of the scheme which is simple but effective. The proposed scheme has normal and memory-reduced versions, which are superior to the original and conventional schemes and guarantees significant bit rate reduction of PS. The proposed scheme can be an alternative to the original PS coding scheme at low bit rate, where coding efficiency is very important.

In this Letter, we propose a new adaptive step-size widely linear constant modulus algorithm (CMA) in DS-CDMA systems especially for time-varying interference environments. The widely linear estimation enables CMA to produce better output signal to interference plus noise ratio (SINR) and the adaptive step-size tackles the time-varying interference environment effectively. The simulations confirm that the proposed algorithm shows better performance in a DS-CDMA system employing a BPSK modulation than other algorithms without use of widely linear processing.

In loudspeaker-based 3D audio systems, there are some acoustic crosstalk cancellation methods to enlarge the 'sweet spot' around a fixed listener position. However, these methods have common defect that most of them can be applied only to the specific narrow frequency band. In this letter, we propose the more robust acoustic crosstalk cancellation method so that we can cancel the crosstalk signal in far wider frequency band and enlarge 'sweet spot. ' For this goal, we apply a sum and difference filter to the conventional three loudspeaker-based 3D audio system.

In this letter, we propose a robust adaptive filter with a Variable Forgetting Factor (VFF) for impulsive noise suppression. The proposed method can restrict the perturbation of the parameters using M-estimator and adaptively reduce the error propagation caused by the impulsive noise using VFF. Simulations show that the performance of the proposed algorithm is less vulnerable to the impulsive noise than those of the conventional Kalman filter based algorithms.

An efficient method is proposed for reconstructing speakerphone-mode cellular phone sound. The overall transfer function from digital PCM signals stored in a cellular phone to dummy head-recorded signals is modeled as a combination of a cellular phone transfer function (CPTF) and a cellular phone-to-listener transfer function (CPLTF). The CPTF represents the linear and nonlinear characteristics of a cellular phone and is modeled by the Volterra model. The CPLTF represents the effect of the path from a cellular phone to a dummy head and is measured. Listening tests show the effectiveness of the proposed method. An application scenario of the proposed method is also addressed for sound quality assessment of cellular phones in speakerphone mode.

We propose an iterative frequency estimation method for accuracy improvement of discrete Fourier transform (DFT) phase-based methods. It iterates frequency estimation and phase calculation based on the DFT phase-based methods, which maximizes the signal-to-noise floor ratio at the frequency estimation position. We apply it to three methods, the phase difference estimation, the derivative estimation, and the arctan estimation, which are known to be among the best DFT phase-based methods. Experimental results show that the proposed method shows meaningful reductions of the frequency estimation error compared to the conventional methods especially at low signal-to-noise ratio.