Institute for Systems Research
Permanent URI for this communityhttp://hdl.handle.net/1903/4375
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Item Joint Optimal Power Control and Beamforming in Wireless Networks Using Antenna Arrays(1997) Rashid-Farrokhi, F.; Tassiulas, L.; Liu, K.J. Ray; ISR; CSHCNThe interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to increase the capacity in wireless communication networks. The MVDR (Minimum Variance Distortionless Responses) beamformer maximizes the Carrier to Interference Ratio (CIR) when it is employed in the receiver of a wireless link. In a system with omnidirectional antennas, power control algorithms are used to maximize CIR as well. In this paper we consider a system with beamforming capabilities in the receiver, and power control. an iterative algorithm is proposed to jointly update the transmission powers and the beamformer weights so that the coverage to the jointly optimal beamforming and transmission power vector. The algorithm is distributed and uses only local interference measurements. In an uplink transmission scenario it is shown how base assignment can be incorporated in addition to beamforming and power control such that a globally optimum solution is obtained. the network capacity increase and the saving in mobile power achieved by beamforming are evaluated through numerical study.Item Fast Blind Adaptive Algorithms for Equalization and Diversity Reception in Wireless Communications Using Antenna Arrays(1996) Li, Ye; Liu, K.J. Ray; ISRTo combat the multipath and time-variant fading of wireless communication channels, antenna arrays are usually used to improve the quality and increase the capacity of communication service. This paper investigates the fast blind adaptive algorithms for the equalization and diversity combining in wireless communication systems using antenna arrays. Two second- order statistics based algorithms, SOSA and MSOS, for equalization and diversity combining are proposed and their convergence in noiseless and noisy channels is analyzed. Since the proposed algorithms use only second-order statistics or correlation of the channel outputs, they converge faster than the higher-order statistics based algorithms, which is also confirmed by computer simulations examples.Item Fractal Modeling and Segmentation for the Enhancement of Microcalcifications in Digital Mammograms(1996) Li, Huai; Liu, K.J. Ray; Lo, Shih-Chung B.; ISRThe objective of this research is to model the mammographic parenchymal, ductal patterns and enhance the microcalcifications using deterministic fractal approach. According to the theory of deterministic fractal geometry, images can be modeled by deterministic fractal objects which are attractors of sets of two dimensional affine transformations. The Iterated Functions Systems and the Collage Theorem are the mathematical foundations of fractal image modeling. In this paper, a methodology based on fractal image modeling is developed to analyze and extract various mammographic textures. We show that general mammographic parenchymal and ductal patterns can be well modeled by a set of parameters of affine transformations. Therefore, microcalcifications can be enhanced by taking the difference between the original image and the modeled image. Our results are compared with those of the partial wavelet reconstruction and morphological operation approaches. The results demonstrate that the fractal modeling method is an effective way to enhance microcalcifications, and thereby facilitate the radiologists' diagnosis. It may also be able to improve detection and classification of microcalcifications in a computer system.Item A Structured Low Rank Matrix Pencil for Spectral Estimation and System Identification(1996) Razavilar, J.; Li, Ye; Liu, K.J. Ray; ISRIn this paper we propose a new parameter estimation algorithm for damped sinusoidal signals. Parameter estimation for damped sinusoidal signals with additive white noise is a problem of significant interests in many signal processing applications, such as analysis of NMR data and system identification. The proposed algorithm estimates the signal parameters using a matrix pencil constructed from the measured data. To reduce the noise effect, rank deficient Hankel approximation of prediction matrix is used. We show that the performance of the estimation can be significantly improved by structured low rank approximation of the prediction matrix. Computer simulations also show that the noise threshold of our new matrix pencil algorithm is significantly low than those of the existing algorithms.Item Simultaneous Diversity Combining and Decoding for Fast Time- Varying Mobile Radio Channels(1996) Wang, H.; Liu, K.J. Ray; ISRIn slowly time-varying mobile radio channels, adaptive diversity combining can reduce multipath fading of desired signal and suppress interfering signals. However, for fast time-varying fading channels, there exist no effective techniques to achieve the same results. The continued use of decision directed adaptive array algorithms will cause error propagation. This paper presents a novel adaptive diversity combining technique with QRD- RLS based parallel weights tracking and a proposed M-D decoder. With moderate increase in complexity, this system significantly reduces error propagation in the decision directed array systems while maintaining the same tracking speed. Its effectiveness and much better performance then that of the conventional technique has been confirmed by computer simulation.Item Blind Adaptive Equalization of SIMO Channels Based on Second- Order Statistics(1996) Li, Ye; Liu, K.J. Ray; ISRThis article investigates blind adaptive equalization for single- input/multiple-output (SIMO) channels. A second-order statistics based algorithm (SOSA) and a modified second-order statistics based algorithm (MSOSA) for equalization of SIMO channels are presented. Computer simulation demonstrates that the new algorithms converge faster than fractionally spaced constant- modulus algorithm (FS-CMA). The proposed algorithms can be applied in wireless communication systems with antenna arrays to combat the multipath fading.Item Blind MIMO FIR Channel Identification Based on Second-Order Statistics with Multiple Signals Recovery(1996) Li, Ye; Liu, K.J. Ray; ISRTo separate and recover multiple signals in data communications, antenna arrays and acoustic sensor arrays, the impulse responses of multiple-input/multiple-output (MIMO) channels have to be identified explicitly or implicitly. This paper deals with the blind identification of MIMO FIR channels based on second-order statistics of the channel outputs. We first investigate the identifiability of MIMO FIR channels, and obtain a necessary and sufficient condition for MIMO FIR channels to be identifiable up to a unitary matrix using second-order statistics. Then, we extend the identification algorithms for single-input/multiple- output (SIMO) FIR channels, such as the algebraic algorithm and the subspace algorithm to the identification of MIMO FIR channels. We also present the application of the above blind identification algorithms to the separation of multiple signals in digital communication systems. Finally, we demonstrate the effectiveness of the algorithms presented in this paper by computer simulationsItem Exact Subpixel Motion Estimation in DCT Domain(1996) Koc, Ut-Va; Liu, K.J. Ray; ISRCurrently existing subpixel motion estimation algorithms require interpolation of inter-pixel values which undesirably increases the overall complexity and data flow and deteriorates estimation accuracy. In this paper, we develop DCT-based techniques to estimate subpel motion at different desired subpel levels of accuracy in DCT domain without interpolation. We show that subpixel motion information is preserved in the DCT of a shifted signal under some condition in the form of pseudo phases and establish subpel sinusoidal orthogonal principles to extract this information. Though applicable to other areas as well, the resulted algorithm from these techniques for video coding are flexible and scalable in terms of estimation accuracy with very low computational complexity O(N2) compared to O(N4) for Full Search Block Matching Approach and its subpixel versions. Above all, motion estimation in DCT domain instead of spatial domain simplifies the conventional hybrid DCT-based video coder, especially the heavily loaded feedback loop in the conventional design, resulting in a fully DCT-based high-throughput video codec. In addition, the computation of pseudo phases is local and thus a highly parallel architecture is feasible for the DCT- based algorithms. Finally simulation on video sequences of different characteristics shows comparable performance of the proposed algorithms to block matching approaches.Item Adaptive Blind Multi-Channel Equalization for Multiple Signals Separation(1995) Li, Ye; Liu, K.J. Ray; ISRThis paper investigates adaptive blind equalization for multiple- input and multiple-output (MIMO) channels and its application to blind separation of multiple signals received by antenna arrays in communication systems. The performance analysis is presented for the CMA equalizer used in MIMO channels. Our analysis results indicate that a double infinite-length MIMO-CMA equalizer can recover one of the input signals, remove the intersymbol interference (ISI), and suppress the rest signals. In particular, for the MIMO FIR channels satisfying certain conditions, the MIMO-CMA FIR equalizer is able to remove the ISI and co-channel interference regardless of the initial setting of the blind equalizer. To recover all input signals simultaneously, a novel MIMO channel blind equalization algorithm is developed in this paper. The global convergence of the new algorithm for MIMO channels is proved. Hence, the new blind equalization algorithm for MIMO channels can be applied to separate and equalize the signals received by antenna arrays in communication systems. Finally, computer simulations are presented to confirm our analysis and illustrate the performance of the new algorithm.Item Two-Dimensional Spatial Smoothing for Multipath Coherent Signal Identification and Separation(1995) Wang, H.; Liu, K.J. Ray; ISRThe existing spatial smoothing (SS) technique, although it is effective in decorrelating coherent signals, is considered applicable only to uniformly spaced linear arrays which are very sensitive to the directions-of-arrival (DOAs) and can be used to estimate azimuth angles only. To significantly improve the robustness of DOA estimation and of beamforming and to estimate both azimuth and elevation angles in a 3D multipath mobile radio environment, we developed techniques for applying SS to arrays of nonlinear geometry. We found and proved the necessary and sufficient conditions on an array configuration for applying SS. This array must have an orientational invariance structure with an ambiguity free center array, and the number of subarrays must be larger than or equal to the size of the largest group of coherent signals. We also studied the cause of ambiguities in a multipath environment. We found the necessary and sufficient conditions for a three-sensor array manifold to be ambiguity free and identified several higher order ambiguity situations. If an array is also central symmetric, the forward/backward spatial smoothing can be used to improve the resolution. Finally, we expanded the application of our technique not only to MUSIC and adaptive beamforming algorithms but also to ESPRIT algorithms. All the predicted results are verified by simulations.