Amit Mathur

Nonlinear techniques for the joint estimation of cochannel signals

Cochannel interference occurs when two or more signals overlap in frequency and are present concurrently. Unlike in spread-spectrum multiple-access systems where the different users necessarily share the same channel, cochannel interference is a severe hindrance to frequency- and time-division multiple-access communications, and is typically minimized by interference rejection/suppression techniques. Rather than using interference suppression, we are interested in the joint estimation of the information-bearing narrow-band cochannel signals. Novel joint estimators are proposed that employ a single-input demodulator with oversampling to compensate for timing uncertainties. Assuming finite impulse-response channel characteristics, maximum likelihood (ML) and maximum a posteriori (MAP) criteria are used to derive cochannel detectors of varying complexities and degrees of performance. In particular, a (suboptimal) two-stage joint MAP symbol detector (JMAPSD) is introduced that has a lower complexity than the single-stage estimators while accruing only a marginal loss in error-rate performance at high signal-to-interference ratios. Assuming only reliable estimates of the primary and secondary signal powers, a blind adaptive JMAPSD algorithm for a priori unknown channels is also derived. The performance of these nonlinear joint estimation algorithms is studied through example computer simulations for two cochannel sources.

Steady-state analysis of the multistage constant modulus array

The multistage constant modulus (CM) array is a cascade adaptive beamforming system that can recover several narrowband cochannel signals without training. We examine its steady-state properties at convergence using a stochastic analysis and computer simulations. Based on a Wiener model of convergence for the gradient adaptive algorithms, closed-form expressions are derived for the CM array and canceller weight vectors, as well as the effective source direction vectors at all stages along the cascade system. The signal-capture and direction-finding capabilities of the system are also discussed. Computer simulations for stationary and fading sources are presented to confirm the theoretical results and to illustrate the rapid convergence behavior of the adaptive algorithms.

A variable step-size CM array algorithm for fast fading channels

A new constant modulus (CM) array algorithm with a time-varying step size is presented. It is designed for use in a cascade multistage system where each beamformer stage recovers one cochannel source. We assume that each source has a small angular spread and that the antenna elements are closely spaced. For this scenario, the new algorithm ensures that a stage tracks the same source during fast fading conditions, thus yielding reliable source estimation in a nonstationary environment. We present the cost function associated with the algorithm and compare it with that of the original CM array. Computer simulations for Rayleigh fading channels are presented to illustrate the improved tracking behavior of the multistage CM array.

A blind adaptive MAP algorithm for the recovery of cochannel signals

This paper describes a blind adaptive algorithm for the recovery of cochannel data signals in the presence of intersymbol interference. Assuming unknown finite impulse response channel characteristics, the principle of maximum a posteriori symbol detection (MAPSD) is employed to jointly estimate the channels and the transmitted data. In order to reduce the complexity of this joint blind MAPSD algorithm, a cascaded multistage structure is proposed whereby each stage recovers one of the cochannel sources. This suboptimal approach is expected to perform well when the cochannel signals have sufficiently different power levels. Computer simulations for a primary signal and a single interferer illustrate the rapid convergence properties of the algorithm.<<ETX>>

Cochannel signal recovery using the MUSIC algorithm and the constant modulus array

We describe an approach to cochannel signal recovery for correlated sources that is based on the the MUSIC (multiple signal classification) algorithm and the constant modulus (CM) array. The MUSIC algorithm provides estimates of the source angles of arrival, which are used to initialize a parallel bank of CM arrays. These adaptive beamformers are updated by the constant modulus algorithm (CMA) to capture and track the source signals, even when they are highly correlated. Computer simulations are presented to illustrate the transient behavior of the proposed algorithm.<<ETX>>

Misadjustment and tracking analysis of the constant modulus array

The constant modulus (CM) array is a blind adaptive beamformer that can separate cochannel signals. A follow-on adaptive signal canceler may be used to perform direction finding of the source captured by the array. In this paper, we analyze the convergence and tracking properties of the CM array using a least-mean-square approximation. Expressions are derived for the misadjustment of the adaptive algorithms, and a tracking model is developed that accurately predicts the behavior of the system during fades. It is demonstrated that the adaptive canceler contributes more to the overall misadjustment than does the adaptive CM beamformer. Computer simulations are presented to illustrate the transient properties of the system and to verify the analytical results.

Adaptive MAPSD algorithms for symbol and timing recovery of mobile radio TDMA signals

Dual-mode adaptive algorithms with rapid convergence properties are presented for the equalization of frequency selective fading channels and the recovery of time-division multiple access (TDMA) mobile radio signals. The dual-mode structure consists of an auxiliary adaptive filter that estimates the channel during the training cycle. The converged filter weights are used to initialize a parallel bank of filters that are adapted blindly during the data cycle. When the symbol timing is known, this filter bank generates error residuals that are used to perform approximate maximum a posteriori symbol detection (MAPSD) and provide reliable decisions of the transmitted signal. For channels with timing jitter, joint estimation of the channel parameters and the symbol timing using an extended Kalman filter algorithm is proposed. Various methods are described to reduce the computational complexity of the MAP detector, usually at the cost of some performance degradation. Also, a blind MAPSD algorithm for combining signals from spatially diverse receivers is derived. This diversity MAPSD (DMAPSD) algorithm, which can be easily modified for the dual-mode TDMA application, maintains a global set of MAP metrics even while blindly tracking the individual spatial channels using local error estimates. The performance of these single-channel and diversity MAPSD dual-mode algorithms are studied via computer simulations for various channel models, including a mobile radio channel simulator for the IS-54 digital cellular TDMA standard.

Estimation of correlated cochannel signals using the constant modulus array

The steady-state behavior of the cascade multistage constant modulus (CM) array is analyzed for correlated cochannel signals. It is demonstrated that the capture performance of the cascade system gradually deteriorates with increasing source cross-correlation. To overcome this loss, we consider using a parallel version of the multistage CM array that is appropriately initialized by a direction-finding algorithm. The proposed method of initialization is based on a single-stage CM array and a signal canceller adapted in tandem. Computer simulations are presented to illustrate the signal capture properties of the parallel multistage CM array.

A blind adaptive antenna system for the estimation of mutually correlated cochannel sources

The constant modulus (CM) array is an adaptive beamformer that blindly recovers a cochannel source without requiring array calibration. An adaptive signal canceller removes the captured source from the array input, after which the remaining cochannel signals can be processed by a series of similar CM array stages. This multistage cascade CM array may experience a loss in performance when the sources are correlated. In this paper, we propose a modified system based on a parallel architecture. The cascade CM array is employed to appropriately initialize the parallel stages, which in turn recover the cochannel sources. Computer simulations are presented to illustrate the transient and steady-state behaviour of the proposed system.

A modified CM array algorithm for fading channels

A new constant modulus (CM) array algorithm with a time-varying step size is presented. It is designed for use in a multistage system where each stage recovers one cochannel signal. The new algorithm ensures that a stage tracks the same source during fast fading conditions (such as those found in mobile radio communications), thus yielding reliable signal estimation in a nonstationary environment. We present the cost function associated with the algorithm and compare it to that of the original CM array. Computer simulations for Rayleigh fading channels are presented to illustrate the improved tracking behavior of the multistage CM array system.