39,100 research outputs found
Time delay estimation in stationary and non-stationary environments
We develop computationally efficient iterative algorithms for finding the Maximum Likelihood
estimates of the delay and spectral parameters of a noise-like Gaussian signal radiated from a
common point source and observed by two or more spatially separated receivers. We first consider
the stationary case in which the source is stationary (not moving) and the observed signals are modeled
as wide sense stationary processes. We then extend the scope by considering a non-stationary
(moving) source radiating a possible non-stationary stochastic signal. In that context, we address the
practical problem of estimation given discrete-time observations. We also present efficient methods
for calculating the Jog-likelihood gradient (score), the Hessian, and the Fisher's information matrix
under stationary and non-stationary conditions.Funding was provided by the Naval Air Systems Command
through contract Number N00014-85-K-0272
Code-timing synchronization in DS-CDMA systems using space-time diversity
The synchronization of a desired user transmitting a known training sequence in a direct-sequence (DS) asynchronous code-division multiple-access (CDMA) sys-tem is addressed. It is assumed that the receiver consists of an arbitrary antenna array and works in a near-far, frequency-nonselective, slowly fading channel. The estimator that we propose is derived by applying the maximum likelihood (ML) principle to a signal model in which the contribution of all the interfering compo-nents (e.g., multiple-access interference, external interference and noise) is modeled as a Gaussian term with an unknown and arbitrary space-time correlation matrix. The main contribution of this paper is the fact that the estimator makes eÆcient use of the structure of the signals in both the space and time domains. Its perfor-mance is compared with the Cramer-Rao Bound, and with the performance of other methods proposed recently that also employ an antenna array but only exploit the structure of the signals in one of the two domains, while using the other simply as a means of path diversity. It is shown that the use of the temporal and spatial structures is necessary to achieve synchronization in heavily loaded systems or in the presence of directional external interference.Peer ReviewedPostprint (published version
Comparison of SAGE and classical multi-antenna algorithms for multipath mitigation in real-world environment
The performance of the Space Alternating Generalized Expectation Maximisation (SAGE) algorithm for multipath mitigation is assessed in this paper. Numerical simulations have already proven the potential of SAGE in navigation context, but practical aspects of the implementation of such a technique in a GNSS receiver are the topic for further investigation. In this paper, we will present the first results of SAGE implementation in a real world environmen
Power delay profile and noise variance estimation for OFDM
In this letter, we present cyclic-prefix (CP) based noise-variance and power-delay-profile estimators for Orthogonal Frequency Division Multiplexing (OFDM) systems. Signal correlation due to the use of the CP is exploited without requiring additional pilot symbols. A heuristic estimator and a class of approximate maximum likelihood (ML) estimators are proposed. The proposed algorithms can be applied to both unitary and non-unitary constellations. These algorithms can be readily used for applications such as minimum mean-square error (MMSE) channel estimation
Multipath Parameter Estimation from OFDM Signals in Mobile Channels
We study multipath parameter estimation from orthogonal frequency division
multiplex signals transmitted over doubly dispersive mobile radio channels. We
are interested in cases where the transmission is long enough to suffer time
selectivity, but short enough such that the time variation can be accurately
modeled as depending only on per-tap linear phase variations due to Doppler
effects. We therefore concentrate on the estimation of the complex gain, delay
and Doppler offset of each tap of the multipath channel impulse response. We
show that the frequency domain channel coefficients for an entire packet can be
expressed as the superimposition of two-dimensional complex sinusoids. The
maximum likelihood estimate requires solution of a multidimensional non-linear
least squares problem, which is computationally infeasible in practice. We
therefore propose a low complexity suboptimal solution based on iterative
successive and parallel cancellation. First, initial delay/Doppler estimates
are obtained via successive cancellation. These estimates are then refined
using an iterative parallel cancellation procedure. We demonstrate via Monte
Carlo simulations that the root mean squared error statistics of our estimator
are very close to the Cramer-Rao lower bound of a single two-dimensional
sinusoid in Gaussian noise.Comment: Submitted to IEEE Transactions on Wireless Communications (26 pages,
9 figures and 3 tables
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