Optimization of generalized mean square error in signal processing and communication
نویسندگان
چکیده
Two matrix optimization problems are analyzed. These problems arise in signal processing and communication. In the first problem, the trace of the mean square error matrix is minimized, subject to a power constraint. The solution is the training sequence, which yields the best estimate of a communication channel. The solution is expressed in terms of the eigenvalues and eigenvectors of correlation and covariance matrices describing the communication, and an unknown permutation. Our analysis exhibits the optimal permutation when the power is either very large or very small. Based on the structure of the optimal permutation in these limiting cases, we propose a small class of permutations to focus on when computing the optimal permutation for arbitrary power. In numerical experiments, with randomly generated matrices, the optimal solution is contained in the proposed permutation class with high probability. The second problem is connected with the optimization of the sum capacity of a communication channel. The second problem, which is obtained from the first by replacing the trace operator in the objective function by the determinant, minimizes the product of eigenvalues, while the first problem minimizes the sum of eigenvalues. For small values of the power, both problems have the same solution. As the power increases, the solutions are different, since the permutation matrix appearing in the solution of the trace problem is not This material is based upon work supported by the National Science Foundation under Grants 0203270 and ANI0020287. ∗ Corresponding author. Tel.: +1 352 392 0281; fax: +1 352 392 8357. E-mail addresses: [email protected] (W.W. Hager), [email protected] (Y. Liu), [email protected] (T.F. Wong). URL: http://www.math.ufl.edu/∼hager (W.W. Hager). 0024-3795/$ see front matter ( 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.laa.2005.12.024 816 W.W. Hager et al. / Linear Algebra and its Applications 416 (2006) 815–834 present in the solution of the determinant problem. For large power, the ordering of the eigenvectors in the solution of the trace problem is the opposite of the ordering in the determinant problem. © 2006 Elsevier Inc. All rights reserved. AMS classification: 60G35; 93E10; 94A15
منابع مشابه
Non-Blind Beamforming Generalized Receiver with DOA Estimation in MIMO Wireless Communication Systems
We investigate the generalized receiver (GR) constructed based on the generalized approach to signal processing in noise employing non-blind beamforming algorithms and direction of arrival (DOA) estimation, which is implemented by multiple-input multiple-output (MIMO) wireless communication systems. We compare three non-blind beamforming algorithms, namely, the least mean square (LMS), the recu...
متن کاملOptimization of Generalized Discrete Fourier Transform for CDMA
Generalized Discrete Fourier Transform (GDFT) with non-linear phase is a complex valued, constant modulus orthogonal function set. GDFT can be effectively used in several engineering applications, including discrete multi-tone (DMT), orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA) communication systems. The constant modulus transforms like discrete Fou...
متن کاملWideband LSF quantization by generalized voronoi codes
Presented a method for quantizing the wideband line spectrum frequencies (LSF) with a specific class of near-ellipsoidal lattice codes referred to as “generalized Voronoi codes”. Optimization procedures are described with respect to a weighted mean-square error (WMSE). The lattices D16, RE16 or R 16 are applied to quantize the LSF with no frequency splitting. Results indicate that near-ellipsoi...
متن کاملFast Reconstruction of SAR Images with Phase Error Using Sparse Representation
In the past years, a number of algorithms have been introduced for synthesis aperture radar (SAR) imaging. However, they all suffer from the same problem: The data size to process is considerably large. In recent years, compressive sensing and sparse representation of the signal in SAR has gained a significant research interest. This method offers the advantage of reducing the sampling rate, bu...
متن کاملBiomedical Image Denoising Based on Hybrid Optimization Algorithm and Sequential Filters
Background: Nowadays, image de-noising plays a very important role in medical analysis applications and pre-processing step. Many filters were designed for image processing, assuming a specific noise distribution, so the images which are acquired by different medical imaging modalities must be out of the noise. Objectives: This study has focused on the sequence filters which are selected ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006