Absfracf-We present a study of a matrix pencil method for estimating parameters (frequencies and damping factors) of exponentially damped and/or undamped sinusoids in noise. Comparison of this method to a polynomial method (SVD-Prony method) shows that the matrix pencil method and the polynomial method are two special cases of a matrix prediction approach but the pencil method is more efficient in computation and less restrictive about signal poles. I t is found through perturbation analysis and simulation that, for signals with unknown damping factors, the pencil method is less sensitive to noise than the polynomial method. I n Appendix A, a new expression of the Cramer-Ran bound for the exponential signals i s presented.

Abstract-Given a multiple-antenna source and a multipleantenna destination, a multiple-antenna relay between the source and the destination is desirable under useful circumstances. A non-regenerative multiple-antenna relay, also called nonregenerative MIMO (multi-input multi-output) relay, is designed to optimize the capacity between the source and the destination. Without a direct link between the source and the destination, the optimal canonical coordinates of the relay matrix are first established, and the optimal power allocations along these coordinates are then found. The system capacity with the optimal relay matrix is shown to be significantly higher than those with heuristic relay matrices. When a direct link is present, upper and lower bounds of the optimal system capacity are discussed.Index Terms-Multiple-antenna relay, MIMO relay, nonregenerative relay, capacity analysis, optimal canonical coordinates, optimal power allocation.

A generalized pencil-of-function (GPOF) method for extracting the poles of an EM system from its transient response is developed. The GPOF method needs the solution of a generalized eigenvalue problem to find the poles. This is in contrast to the conventional Prony and pencil-of-function methods which yield the solution in two steps, namely, the solution of an ill-conditioned matrix equation and finding the roots of a polynomial. Subspace decomposition is also used to optimize the performance of the GPOF method. The GPOF method has advantages over the Prony method in both computation and noise sensitivity, and approaches the Cramer-Rao bound when the signal-to-noise ratio (SNR) is above threshold. An application of the GPOF method to a thin-wire target is also presented.

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Blind system identification (BSI) is a fundamental signal processing technology aimed at retrieving a system's unknown information from its output only. This technology has a wide range of possible applications such as mobile communications, speech reverberation cancellation, and blind image restoration. This paper reviews a number of recently developed concepts and techniques for BSI, which include the concept of blind system identifiability in a deterministic framework, the blind techniques of maximum likelihood and subspace for estimating the system's impulse response, and other techniques for direct estimation of the system input.