A signal eigenvalue sensitivity analysis for subspace-based methods that exploit the shift-invariance property present in the signal subspace is considered. It is proved that signal eigenvalues are rather insensitive to small perturbations in the data provided the dimension of the problem is large enough and the eigenvalues themselves are not extremely close to each other. In addition, bounds o...

In our earlier work [1, 2], we developed a robust detector for multipath constrained environments when the transmitted signal is known. In this paper, we extend these results to the case where the transmitted signal is a random process. The approach in [1, 2] is to replace the orthogonal projection on the multipath signal subspace S by the orthogonal projection on a representation subspace G, s...

Introduction: It is shown in [1] that the weighted subspace fitting (WSF) method, a minimising technique, always outperforms the deterministic maximum likelihood (DML) estimator for the problem of the direction-of-arrival (DOA) estimation. However, the WSF estimator is still subject to high computational cost, partially attributable to the estimation of the signal subspace. In this Letter, the ...

In this paper, we introduce subspace-frequently hypercyclic operators. We show that these operators are subspace-hypercyclic and there are subspace-hypercyclic  operators that are not subspace-frequently hypercyclic. There is a criterion like to subspace-hypercyclicity criterion that implies subspace-frequent hypercyclicity and if an operator $T$ satisfies this criterion, then $Toplus T$ is sub...

This paper presents a blind adaptive detector for asynchronous DS-CDMA in multipath channels. The receiver exploits the underlying subspace structure for recursive estimation of the desired signal vector, and eliminates the need of explicit channel or delay estimation. The detector is constrained to the signal subspace (hence reduced rank), leading to computational efficiency while also benefit...

A novel adaptive beamforming algorithm against large direction-of-arrival (DOA) mismatch without using optimization toolboxes is proposed. In contrast to previous works, this new beamformer employs two reconstructed matrices, the interference-plus-noise covariance matrix and the desired signal-plus-noise covariance matrix, instead of their real sample covariance matrix, respectively. These reco...

This paper describes a block-by-block basis image enhancement algorithm which uses the signal subspace method to enhance images corrupted by uncorrelated additive noise. The enhancement is performed by eliminating the noise components in the noise subspace and estimating the clean image from the remaining components in the signal subspace.

A novel subspace projection approach was proposed to improve the robustness of adaptive beamforming and direction finding algorithms. The cost function of the signal subspace scaled multiple signal classification (SSMUSIC) is minimized in the uncertainty set of the signal steering vector, the optimal solution to the optimization problem is that the assumed steering vector can be modified as the...

A novel approach to the adaptive transmission to combat fast fading effect in mobile wireless systems is presented. In this approach, the downlink beamforming weights of the base station antennas are generated based on the orthogonal basis of the uplink signal subspace. The signal intended for a particular mobile user is transmitted through its corresponding signal subspace. Due to the stabilit...

say, the center frequency of the spectrum of the signals, and transform the subspace at each frequency bin into the subspace created by the span of the location vectors at the focusing frequency. Then, they use a high-resolmion algorithm such as MUSIC [SI to estimate the DOA's of the sources. They show that focusing reduces the resolution threshold signal-to-noise ratio (SMZ), which is defined ...