Hongxing Zou

Joint Information- and Jamming-Beamforming for Physical Layer Security With Full Duplex Base Station

In this paper, we design joint information beamforming and jamming beamforming to guarantee both transmit security and receive security for a full-duplex base-station (FD-BS). Specifically, we aim to maximize the secret transmit rate while constrain the secret receive rate to be greater than a predefined bound. When FD-BS is equipped with a single transmit antenna, we derive the optimal solutions in closed-form, and interestingly, the results say that simultaneous information and jamming transmission cannot be optimal. When FD-BS is equipped with multiple transmit antennas, we convert the original nonconvex problem into a sequence of subproblems where the semidefinite programming (SDP) relaxation can be applied to efficiently find the optimal solutions. We strictly prove that such a relaxation does not change the optimality for these subproblems. Then the global optimal solutions of the original nonconvex problem can be obtained via a one-dimensional search. Simulation results are provided to verify the efficiency of the proposed algorithms.

Parametric TFR via windowed exponential frequency modulated atoms

We propose a new atom, namely, the dilated and translated windowed exponential frequency modulated functions (FM/sup m/let) for compactly characterizing both the signals time-invariant and time-varying spectral contents. The superiority of the proposed method to some existing time-frequency distributions (TFDs) is demonstrated using a bat sonar signal.

Steady-motion-based Dopplerlet transform: application to the estimation of range and speed of a moving sound source

New results on the recently introduced steady-motion-based Dopplerlet transform is presented and an estimation scheme for both range and speed of moving sound source using Dopplerlet transform is considered. First, we derive the real, discrete, and real discrete Dopplerlet transforms from their complex counterpart. Second, we reformulate some of the existing integral transformations within the framework of the Dopplerlet transform. Finally, we provide the application results. Experimental results with real underwater acoustic data and land acoustic data, as well as Monte Carlo simulation results with computer-generated data, have confirmed the veracity and practical usefulness of the estimation scheme advocated.

A Novel Orthonormalization Matrix Based Fast and Stable DPM Algorithm for Principal and Minor Subspace Tracking

We note that the well-known Fast Rayleighs quotient-based Adaptive Noise Subspace (FRANS), FRANS with Householder transformation (HFRANS), and fast data projection method (FDPM) algorithms all inherit from the data projection method (DPM) algorithm, but with different orthonormalization matrices. Starting from the DPM, we analyze the orthonormalization matrices of all these algorithms and develop a novel orthonormalization matrix for our algorithm. Based on this novel orthonormalization matrix, a fast and stable implementation of the DPM algorithm which has the merits of both the FRANS and FDPM approaches is investigated for principal and minor subspace tracking. The proposed algorithm can switch between the principal and minor subspace tracking with a simple sign change of its step size parameter. Moreover, it reaches the 3np lower bound of the dominant complexity and guarantees the orthonormality of the tracked subspace. The numerical stability of our algorithm is established theoretically and tested numerically. The strengths and weaknesses of the proposed algorithm to some existing subspace tracking algorithms are demonstrated using a de facto benchmark example. Simulation results are presented to demonstrate the effectiveness of the tracking algorithm advocated.

Fast communication: Interference cancellation in GPS receiver using noise subspace tracking algorithm

In this paper, we address the problem of interference cancellation in global positioning system (GPS) receiver using a two-step approach: subspace projection technique and maximum signal-to-noise ratio (MSNR) beamforming. The interference signals can be effectively suppressed by projecting the received signal on the noise subspace. Here noise subspace tracking algorithm is employed to estimate the noise subspace directly. We then apply a beamformer to maximize the signal-to-noise ratio of the interference-free signal. Simulation results show that our approach can effectively eliminate the strong interference and enhance the performance of the GPS receiver.

Fast communication: Near-field multiple source localization using joint diagonalization

A new near-field multiple source localization algorithm for joint range and direction-of-arrival (DOA) estimation is proposed. Via joint diagonalization of a set of matrices, the array manifold matrix is estimated and the automatically paired DOA and range parameters are obtained subsequently. The proposed algorithm does not require any search over the parameter space or any additional 2-D parameter paring procedure or high-order statistics (HOS) computation compared with the existing near-field source localization methods. Simulation results validate that the root mean square errors (RMSEs) of the estimated DOA and range parameters are close to the Cramer-Rao bounds (CRBs).

Acceleration-based Dopplerlet transform-Part II: Implementations and applications to passive motion parameter estimation of moving sound source

The acceleration-based Dopplerlet transform developed in Part I is applied to passive estimation of the motion parameters of moving sound sources. The problems considered are: (1) accuracies of the estimated Dopplerlet parameters; (2) application-specific fast implementation. The experimental results using synthetic, land, air and underwater acoustic signals are presented to validate the acceleration-based Dopplerlet transform and to verify the effectiveness of the passive estimation scheme using a single sensor.

Acceleration-based Dopplerlet transform-Part I: Theory

Steady-motion-based Dopplerlet transform has been recently proposed and applied to the estimation of range and speed of moving sound source. In this paper, we develop a new Dopplerlet by introducing acceleration into its definition. Compared with the steady-motion-based Dopplerlet, the acceleration-based Dopplerlet can simultaneously exploit the information of range, speed and acceleration of a moving sound source and can better capture the true time-varying nature of the Doppler-like signals. Part I concerns the fundamentals of the proposed transform, while Part II is devoted to the implementations and applications.

Stable and Orthonormal OJA Algorithm With Low Complexity

In this letter, a stable and orthonormal version of the OJA algorithm (SOOJA) is investigated for principal and minor subspace extraction and tracking. The new algorithm presented here guarantees the orthonormality of the weight matrix at each iteration through a novel orthonormalization method. Moreover, it obtains both a high numerical stability and a low computational complexity. The superiority of the proposed algorithm to some existing subspace tracking algorithms is demonstrated using a classical example. Simulation results confirm the veracity of the subspace tracking algorithm advocated.

Variable partial-update NLMS algorithms with data-selective updating

We note that some existing algorithms are based on the normalized least-mean square (NLMS) algorithm and aim to reduce the computational complexity of NLMS all inherited from the solution of the same optimization problem, but with different constraints. A new constraint is analyzed to substitute an extra searching technique in the set-membership partial-update NLMS algorithm (SM-PU-NLMS) which aims to get a variable number of updating coefficients for a further reduction of computational complexity. We get a closed form expression of the new constraint without extra searching technique to generate a novel set-membership variable-partial-update NLMS (SM-VPU-NLMS) algorithm. Note that the SM-VPU-NLMS algorithm obtains a faster convergence and a smaller mean-squared error (MSE) than the existing SM-PU-NLMS. It is pointed out that the closed form expression can also be applied to the conventional variable-step-size partial-update NLMS (VSS-PU-NLMS) algorithm. The novel variable-step-size variable-partial-update NLMS (VSS-VPU-NLMS) algorithm is also verified to get a further computational complexity reduction. Simulation results verify that our analysis is reasonable and effective.