Institute for Systems Research
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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 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 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.Item A Fast Minimal-Symbol Subspace Approach to Blind Identification and Equalization(1995) Sampath, B.; Li, Ye; Liu, K.J. Ray; ISRA subspace-based blind channel identification algorithm using only the fact that the received signal can be oversampled is proposed. No direct use is made of the statistics of the input sequence or even of the fact that the symbols are from a finite set and therefore this algorithm can be used to identify even channels in which arbitrary symbols are sent. A modification of this algorithm which uses the extra information in the more common case when the symbols are from a finite set is also presented. This LS-Subspace algorithm operates directly on the data domain and therefore avoids the problems associated with other algorithms which use the statistical information contained in the received signal. In the noiseless case, it is possible for the proposed Basic Subspace algorithm to identify the channel exactly using the least number of symbols that can possibly be used. Thus, if the length of the impulse response of a channel is JT, T being the symbol interval, then it is possible to use this algorithm to identify the channel using an observation interval of just (J + 3)T. In the noisy case, simulations have shown that almost exact identification can be obtained by using a few more symbols than the theoretical minimum. This is orders of magnitude better than the other blind algorithms. Moreover, this algorithm is computationally very efficient and has no convergence problems.Item Improved Parameter Estimation Schemes for Damped Sinusoidal Signals Based on Low-Rank Hankel Approximation(1995) Li, Ye; Liu, K.J. Ray; Razavilar, J.; ISRThe parameter estimation of damped sinusoidal signals is an important issue in spectral analysis and many applications. The existing algorithms, such as the KT algorithms [8] and the TLS algorithms [13], are based on the low-rank approximation of prediction matrix, which ignores the Hankel property of the prediction matrix. We will prove in this paper that the performance of parameter estimation can be improved if both rank- deficient and Hankel properties of the prediction matrix are exploited in the matrix approximation. Based on this idea, a modified KT (MKT) algorithm and a super resolution algorithm- damped MUSIC (DMUSIC) algorithm are proposed. Computer simulation results demonstrate that, compared with the original KT algorithm, the MKT and MUSIC algorithms have about 5dB lower noise threshold and can estimate the parameters of signal with larger damping factors.Item Coherent Signal Processing Using Arrays of Arbitrary Geometry(1994) Wang, H.; Liu, K.J. Ray; ISRThe existing spatial smoothing (SS) technique, although it is effective in decorrelating coherent signals, can only be applied to uniformly spaced linear arrays which are very sensitive to the directions-of-arrival (DOA's) and can be used to estimate arimuth angles only. To significantly improve the robustness of DOA estimation and of beamforming and to estimate both arimuth and elevation angles, we developed techniques for applying SS to arrays of arbitrary geometry. We found that an array must have an orientational invariance structure with an ambiguity free center array for applying SS. We also study the cause of ambiguities in a multiple signal environment and find the necessary and sufficient conditions for an array manifold to be ambiguity free. If an array is also central symmetric, the forward/backward spatial smoothing can be used to improve the resolution. Finally, we expand the application of our technique not only to MUSIC and adaptive beamforming algorithms but also to ESPRIT algorithm. All the predicted results are verified by simulations.Item Real-Time Algorithm-Based Fault-Tolerance for QRD Recursive Least-Squares Systolic Array: A Graceful Degradation Approach(1991) Liu, K.J. Ray; Yao, K.; ISRIn this paper, we propose a new algorithm-based fault-tolerant method derived from the inherent nature of the QR lease-squares systolic algorithm. Since the residuals of different desired responses can be computed simultaneously, an artificial desired response can be designed to detect an error produced by a faulty processor. We show that if the artificial desired response is designed as some proper combinations of the input data, the output residual of the system will be zero if there is no fault. However, any occurring fault in the system will cause the residual to be non-zero and the fault can be detected in realtime. Once the fault has been detected, the system enters into the fault diagnosis phase from the concurrent error detection phase. Two methods, the flushing fault location and the checksum encoding methods, can be used to diagnose the location of the faulty row. When the faulty row is determined, this row and the associated column with the same boundary cell are eliminated by a reconfiguration operation. Then the system degrades in a graceful manner which is generally acceptable for many least-squares applications. Those eliminated processors enter into a self-checking phase, and when the transient fault condition is removed, a reconfiguration is performed to resume the normal full order operation. The analysis of error propagation and recovery latency is also considered in this paper.Item Dynamic Range, Stability, and Fault-tolerant Capability of Finite-precision RLS Systolic Array Based on Givens Rotations(1990) Liu, K.J. Ray; Hsieh, S.F.; Yao, K.; Chiu, Ching-Te; ISRThe QRD RLS algorithm is generally recognized as having good numerical properties under finite-precision implementation. Also, it is very suitable for VLSI implementation since it can be easily mapped onto a systolic array. However, it is still unclear how to obtain the dynamic range of the algorithm such that a wordlength can be chosen to ensure correct operations of the algorithm. In this paper, we first propose a quasi-steady state model by observing the rotation parameters generated by boundary cells will eventually reach quasi steady-state regardless of the input data statistics if l is close to one. With this model, we can obtain upper bounds of the dynamic range of processing cells. Thus, the wordlength can be obtained from upper bounds of the dynamic range to prevent overflow and to ensure correct operations of the QRD RLS algorithm. Then we reconsider the stability problem under quantization effects with more general analysis and obtain tighter bounds than given in a previous work [13]. Finally, two fault-tolerant problems, the missing error detection and the false alarm effect, the arise under finite- precision implementation are considered. Detail analysis on preventing missing error detection with a false alarm free condition is presented.