Minimum Power Distortionless Response Research Articles

Maximum likelihood estimation of direction of arrival using an acoustic vector-sensor

A vector-sensor consisting of a monopole sensor collocated with orthogonally oriented dipole sensors is used for direction of arrival (DOA) estimation in the presence of an isotropic noise-field or internal device noise. A maximum likelihood (ML) DOA estimator is derived and subsequently shown to be a special case of DOA estimation by means of a search for the direction of maximum steered response power (SRP). The problem of SRP maximization with respect to a vector-sensor can be solved with a computationally inexpensive algorithm. The ML estimator achieves asymptotic efficiency and thus outperforms existing estimators with respect to the mean square angular error (MSAE) measure. The beampattern associated with the ML estimator is shown to be identical to that used by the minimum power distortionless response beamformer for the purpose of signal enhancement.

Minimum geometric power distortionless response beamforming against heavy-tailed noise of unknown statistics

Minimum geometric power distortionless response beamforming against heavy-tailed noise of unknown statistics

Capacity and Error Performance of Reduced-Rank Transmitter Multiuser Preprocessing Based on Minimum Power Distortionless Response

In this contribution we first derive a transmitter multiuser preprocessing (TMP) scheme for a general multiuser multiple-input-multiple-output (MIMO) system based on the minimum power distortionless response (MPDR) criterion, which minimizes the power in the context of a given downlink mobile terminal (MT) under the distortionless condition. This optimization problem results in a solution, which has the same form as the minimum mean-square error (MMSE) multiuser detection (MUD). Hence, we then extend the well-known rank-reduction techniques in MMSE-MUD to the MPDR-TMP in order to mitigate the possible implementation problems of the MPDRTMP. In our study three classes of rank-reduction algorithms are considered, which are derived, respectively, based on the eigen-analysis methods of principal components (PC) and crossspectral metrics (CSMs) as well as on the Taylor polynomial approximation (TPA) approach, which does not depend on the eigen-analysis. In this contribution both the capacity and error performance of a downlink space-division multiple-access (SDMA) system is investigated, when either the full-rank or reduced-rank MPDR-TMP is invoked. From our study and simulation results, it can be shown that the MPDR-TMP scheme is highly efficient for achieving the capacity and for suppressing the multiuser interference (MUI). The reduced-rank techniques can be employed by the MPDR-TMP, so as to reduce its implementation complexity while achieving the near full-rank performance of the full-rank MPDR-TMP.