Elemental Power Constraint Research Articles

Waveform covariance matrix design using Fourier series coefficients

Multiple-input multiple-output (MIMO) radars may outperform other radar systems such as phased array radars, in terms of higher resolution, better detection probability in the presence of interferences, better parameter identifiability and more flexibility in beampattern design. Waveform covariance matrix design, because of its role in the beampattern synthesis process, is one of the most important problems in MIMO radar systems. In this study, the authors have proposed a closed-form solution based on Fourier series coefficients to design a covariance matrix. The resulting covariance matrix fulfils the practical constraints, i.e. positive semi-definiteness and the uniform elemental power constraint. It also provides performance similar to that of iterative methods, while requires lower computation time and provides better mean square error with respect to other existing closed-form methods. Eigenvalue decomposition is also utilised to convert the possible resulted pseudo-covariance matrices (pseudo-CM), which are not guaranteed to be positive semidefinite, into a covariance matrix. Simulation results show the performance of the proposed method.

Sparsity-aware transmit beamspace design for FDA-MIMO radar

Frequency diverse array (FDA) can produce a range-angle-dependent beampattern due to the employment of a small frequency increment across the array elements. By utilizing this characteristic, this letter devises an FDA and multiple-input multiple-output hybrid radar to jointly estimate the ranges and angles of multiple targets via optimal transmit beamspace design. A uniform elemental power constraint is adopted as the optimization criterion is to minimize the mutual coherence of the sensing matrix using a sparse model and to achieve high-resolution estimation in both range and angle dimensions. A cyclic optimization approach based on power method-like is further developed to solve the non-convex design problem. The excellent performance of the proposed approach is demonstrated via computer simulations.

Fourier-Based Transmit Beampattern Design Using MIMO Radar

In multiple-input multiple-output (MIMO) radar settings, it is often desirable to transmit power only to a given location or set of locations defined by a beampattern. Transmit waveform design is a topic that has received much attention recently, involving synthesis of both the signal covariance matrix, R, as well as the actual waveforms. Current methods involve a two-step process of designing R via iterative solutions and then using R to generate waveforms that fulfill practical constraints such as having a constant-envelope or drawing from a finite alphabet. In this paper, a closed-form method to design R for a uniform linear array is proposed that utilizes the discrete Fourier transform (DFT) coefficients and Toeplitz matrices. The resulting covariance matrix fulfills the practical constraints such as positive semidefiniteness and the uniform elemental power constraint and provides performance similar to that of iterative methods, which require a much greater computation time. Next, a transmit architecture is presented that exploits the orthogonality of frequencies at discrete DFT values to transmit a sum of orthogonal signals from each antenna. The resulting waveforms provide a lower mean-square error than current methods at a much lower computational cost, and a simulated detection scenario demonstrates the performance advantages achieved.

Waveform Diversity Based Ultrasound System for Hyperthermia Treatment of Breast Cancer

In this letter, we present a new waveform-diversity-based ultrasound hyperthermia technique for the treatment of breast cancer. Waveform diversity offers a new paradigm for beampattern design. By choosing a proper covariance matrix of the transmitted waveforms under the uniform elemental power constraint, the ultrasound system can provide a focal spot matched to the entire tumor region, and meanwhile, minimize the impact to the surrounding healthy breast tissues. As shown in our 2-D numerical simulations, this method has better acoustic power deposition than the existing methods, and can provide the necessary temperature gradients required for the effective hyperthermia treatment of breast cancer.

MIMO Transmit Beamforming Under Uniform Elemental Power Constraint

We consider multi-input multi-output (MIMO) transmit beamforming under the uniform elemental power constraint. This is a nonconvex optimization problem, and it is usually difficult to find the optimal transmit beamformer. First, we show that for the multi-input single-output (MISO) case, the optimal solution has a closed-form expression. Then we propose a cyclic algorithm for the MIMO case which uses the closed-form MISO optimal solution iteratively. The cyclic algorithm has a low computational complexity and is locally convergent under mild conditions. Moreover, we consider finite-rate feedback methods needed for transmit beamforming. We propose a simple scalar quantization method, as well as a novel vector quantization method. For the latter method, the codebook is constructed under the uniform elemental power constraint and the method is referred as VQ-UEP. We analyze VQ-UEP performance for the MISO case. Specifically, we obtain an approximate expression for the average degradation of the receive signal-to-noise ratio (SNR) caused by VQ-UEP. Numerical examples are provided to demonstrate the effectiveness of our proposed transmit beamformer designs and the finite-rate feedback techniques.

Waveform Diversity Based Ultrasound System for Hyperthermia Treatment of Breast Cancer

In this letter, we present a new waveform-diversity-based ultrasound hyperthermia technique for the treatment of breast cancer. Waveform diversity offers a new paradigm for beampattern design. By choosing a proper covariance matrix of the transmitted waveforms under the uniform elemental power constraint, the ultrasound system can provide a focal spot matched to the entire tumor region, and meanwhile, minimize the impact to the surrounding healthy breast tissues. As shown in our 2-D numerical simulations, this method has better acoustic power deposition than the existing methods, and can provide the necessary temperature gradients required for the effective hyperthermia treatment of breast cancer.

Maximum-SNR spatial-temporal formatting designs for MIMO channels

We consider a communication scenario involving an m /spl times/ n multiple input multiple output (MIMO) flat fading channel whose input is a symbol stream multiplied prior to transmission by an n /spl times/ n spatial-temporal formatting matrix X and whose output is fed into an m /spl times/ n linear combiner Z. We show how to choose the matrices X and Z to maximize the signal-to-noise ratio (SNR) of the linear combiner output data that are used for detection, under the total power constraint (TPC), the elemental power constraint (EPC), or the total and elemental power constraint (TEPC). The TEPC design (considered here for the first time) is shown to include the TPC and EPC designs (previously considered by the authors) as special cases and, hence, to provide a theoretically and practically interesting unifying framework. We make use of this framework to discuss various tradeoffs of the three space-time formatting designs considered, such as transmission rate and requirements for channel state information at the transmission side. Additionally, we show that the EPC design, which is the only one of the aforementioned designs that does not require channel information at the transmission side, is also the maximum SNR design in the worst channel case under a TPC.