Blind separation of synchronous co-channel digital signals using an antenna array. I. Algorithms
TL;DR: A maximum-likelihood approach for separating and estimating multiple synchronous digital signals arriving at an antenna array at a cell site and a signal detection technique based on the finite alphabet property that is different from a standard linear combiner are introduced.
Abstract: We propose a maximum-likelihood (ML) approach for separating and estimating multiple synchronous digital signals arriving at an antenna array at a cell site. The spatial response of the array is assumed to be known imprecisely or unknown. We exploit the finite alphabet property of digital signals to simultaneously estimate the array response and the symbol sequence for each signal. Uniqueness of the estimates is established for BPSK signals. We introduce a signal detection technique based on the finite alphabet property that is different from a standard linear combiner. Computationally efficient algorithms for both block and recursive estimation of the signals are presented. This new approach is applicable to an unknown array geometry and propagation environment, which is particularly useful In wireless communication systems. Simulation results demonstrate its promising performance.
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TL;DR: This article focuses largely on the receive (mobile-to-base station) time-division multiple access (TDMA) (nonspread modulation) application for high-mobility networks and describes a large cell propagation channel and develops a signal model incorporating channel effects.
Abstract: Space-time processing can improve network capacity, coverage, and quality by reducing co-channel interference (CCI) while enhancing diversity and array gain. This article focuses largely on the receive (mobile-to-base station) time-division multiple access (TDMA) (nonspread modulation) application for high-mobility networks. We describe a large (macro) cell propagation channel and discuss different physical effects such as path loss, fading delay spread, angle spread, and Doppler spread. We also develop a signal model incorporating channel effects. Both forward-link (transmit) and reverse-link (receive) channels are considered and the relationship between the two is discussed. Single- and multiuser models are treated for four important space-time processing problems, and the underlying spatial and temporal structure are discussed as are different algorithmic approaches to reverse link space-time professing with blind and nonblind methods for single- and multiple-user cases. We cover forward-link space-time algorithms and we outline methods for estimation of multipath parameters. We also discuss applications of space-time processing to CDMA, applications of space-time techniques to current cellular systems, and industry trends.
1,062 citations
01 Jul 1997
TL;DR: This paper presents an overview of mobile communications as well as details of how an array may be used in various mobile communications systems, including land-mobile, indoor-radio, and satellite-based systems.
Abstract: The demand for wireless mobile communications services is growing at an explosive rate, with the anticipation that communication to a mobile device anywhere on the globe at all times will be available in the near future. An array of antennas mounted on vehicles, ships, aircraft, satellites, and base stations is expected to play an important role in fulfilling the increased demand of channel requirement for these services, as well as for the realization of the dream that a portable communications device the size of a wristwatch be available at an affordable cost for such services. This paper is the first of a two-part study. It provides a comprehensive treatment, at a level appropriate to nonspecialists, of the use of an antenna array to enhance the efficiency of mobile communications systems. It presents an overview of mobile communications as well as details of how an array may be used in various mobile communications systems, including land-mobile, indoor-radio, and satellite-based systems. It discusses advantages of an array of antennas in a mobile communications system, highlights improvements that are possible by using multiple antennas compared to a single antenna in a system, and provides details on the feasibility of antenna arrays for mobile communications applications.
1,052 citations
21 Apr 1997
TL;DR: This paper reviews space-time signal processing in mobile wireless communications and focuses on antenna arrays deployed at the base stations since such applications are of current practical interest.
Abstract: This paper reviews space-time signal processing in mobile wireless communications. Space-time processing refers to the signal processing performed in the spatial and temporal domain on signals received at or transmitted from an antenna array, in order to improve performance of wireless networks. We focus on antenna arrays deployed at the base stations since such applications are of current practical interest.
693 citations
TL;DR: This link facilitates the derivation of powerful identifiability results for MI-SAP, shows that the uniqueness of single- and multiple-invariance ESPRIT stems from uniqueness of low-rank decomposition of three-way arrays, and allows tapping on the available expertise for fitting the PARAFAC model.
Abstract: This paper links multiple invariance sensor array processing (MI-SAP) to parallel factor (PARAFAC) analysis, which is a tool rooted in psychometrics and chemometrics. PARAFAC is a common name for low-rank decomposition of three- and higher way arrays. This link facilitates the derivation of powerful identifiability results for MI-SAP, shows that the uniqueness of single- and multiple-invariance ESPRIT stems from uniqueness of low-rank decomposition of three-way arrays, and allows tapping on the available expertise for fitting the PARAFAC model. The results are applicable to both data-domain and subspace MI-SAP formulations. The paper also includes a constructive uniqueness proof for a special PARAFAC model.
625 citations
Cites background from "Blind separation of synchronous co-..."
...ILSP [33] is actually not an ALS algorithm...
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...ILSP [33] is actually not an ALS algorithm because it uses a two-step finite-alphabet update procedure that is not optimal in the conditional LS sense, and hence, convergence is not guaranteed....
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...The so-called ILSE algorithm is one well-known example [33]....
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01 Oct 1998
TL;DR: A review of blind channel estimation algorithms is presented, from the (second-order) moment-based methods to the maximum likelihood approaches, under both statistical and deterministic signal models.
Abstract: A review of blind channel estimation algorithms is presented. From the (second-order) moment-based methods to the maximum likelihood approaches, under both statistical and deterministic signal models. We outline basic ideas behind several new developments, the assumptions and identifiability conditions required by these approaches, and the algorithm characteristics and their performance. This review serves as an introductory reference for this currently active research area.
609 citations
References
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TL;DR: Simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented.
Abstract: A new approach is presented to the problem of detecting the number of signals in a multichannel time-series, based on the application of the information theoretic criteria for model selection introduced by Akaike (AIC) and by Schwartz and Rissanen (MDL). Unlike the conventional hypothesis testing based approach, the new approach does not requite any subjective threshold settings; the number of signals is obtained merely by minimizing the AIC or the MDL criteria. Simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented.
3,341 citations
TL;DR: Algorithms are presented which make extensive use of well-known reliable linear least squares techniques, and numerical results and comparisons are given.
Abstract: For given data ($t_i\ , y_i), i=1, \ldots ,m$ , we consider the least squares fit of nonlinear models of the form F($\underset ~\to a\ , \underset ~\to \alpha\ ; t) = \sum_{j=1}^{n}\ g_j (\underset ~\to a ) \varphi_j (\underset ~\to \alpha\ ; t) , \underset ~\to a\ \epsilon R^s\ , \underset ~\to \alpha\ \epsilon R^k\ $ For this purpose we study the minimization of the nonlinear functional r($\underset ~\to a\ , \underset ~\to \alpha ) = \sum_{i=1}^{m} {(y_i - F(\underset ~\to a , \underset ~\to \alpha , t_i))}^2$ It is shown that by defining the matrix ${ \{\Phi (\underset ~\to \alpha\} }_{i,j} = \varphi_j (\underset ~\to \alpha ; t_i)$ , and the modified functional $r_2(\underset ~\to \alpha ) = \l\ \underset ~\to y\ - \Phi (\underset ~\to \alpha )\Phi^+(\underset ~\to \alpha ) \underset ~\to y \l_2^2$, it is possible to optimize first with respect to the parameters $\underset ~\to \alpha$ , and then to obtain, a posteriori, the optimal parameters $\overset ^\to {\underset ~\to a}$ The matrix $\Phi^+(\underset ~\to \alpha$) is the Moore-Penrose generalized inverse of $\Phi (\underset ~\to \alpha$), and we develop formulas for its Frechet derivative under the hypothesis that $\Phi (\underset ~\to \alpha$) is of constant (though not necessarily full) rank From these formulas we readily obtain the derivatives of the orthogonal projectors associated with $\Phi (\underset ~\to \alpha$), and also that of the functional $r_2(\underset ~\to \alpha$) Detailed algorithms are presented which make extensive use of well-known reliable linear least squares techniques, and numerical results and comparisons are given These results are generalizations of those of H D Scolnik [1971]
1,153 citations
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01 Jan 1981
1,133 citations
01 Jan 1973
TL;DR: In this paper, the least square fit of nonlinear models of the form {(0t, Yi), l,, m, qgj, ti, and the modified functional r2( 0t (lY O(0 t)/(0)yl)22) is considered.
Abstract: For given data (t, Yi), l, , m, we consider the least squares fit ofnonlinear models of the form It is shown that by defining the matrix {(0t)}i, qgj(0t; ti), and the modified functional r2(0t (lY O(0t)/(0t)yl)22, it is possible to optimize first with respect to the parameters 0t, and then to obtain, a posteriori, the optimal parameters . The matrix (0t) is the Moore-Penrose generalized inverse of O(t). We develop formulas for the Fr6chet derivative of orthogonal projectors associated with and also for /(0t), under the hypothesis that O(0t) is of constant (though not necessarily full) rank. Detailed algorithms are presented which make extensive use ofwell-known reliable linear least squares techniques, and numerical results and comparisons are given. These results are generalizations of those of H. D. Scolnik (20) and Guttman, Pereyra and Scolnik (9).
1,083 citations