250 research outputs found
Performance Analysis and Optimal Power Allocation for Linear Receivers Based on Superimposed Training
In this paper, we derive a performance comparison between two training-based
schemes for Multiple-Input Multiple-Output (MIMO) systems. The two schemes are
thetime-division multiplexing scheme and the recently proposed data-dependent
superimposed pilot scheme. For both schemes, a closed-form expressions for the
Bit Error Rate (BER) is provided. We also determine, for both schemes, the
optimal allocation of power between pilot and data that minimizes the BER
Structure-Based Subspace Method for Multi-Channel Blind System Identification
In this work, a novel subspace-based method for blind identification of
multichannel finite impulse response (FIR) systems is presented. Here, we
exploit directly the impeded Toeplitz channel structure in the signal linear
model to build a quadratic form whose minimization leads to the desired channel
estimation up to a scalar factor. This method can be extended to estimate any
predefined linear structure, e.g. Hankel, that is usually encountered in linear
systems. Simulation findings are provided to highlight the appealing advantages
of the new structure-based subspace (SSS) method over the standard subspace
(SS) method in certain adverse identification scenarii.Comment: 5 pages, Submitted to IEEE Signal Processing Letters, January 201
Exact Conditional and Unconditional Cram\`er-Rao Bounds for Near Field Localization
This paper considers the Cram\`er-Rao lower Bound (CRB) for the source
localization problem in the near field. More specifically, we use the exact
expression of the delay parameter for the CRB derivation and show how this
exact CRB can be significantly different from the one given in the literature
and based on an approximate time delay expression (usually considered in the
Fresnel region). This CRB derivation is then generalized by considering the
exact expression of the received power profile (i.e., variable gain case)
which, to our best knowledge, has been ignored in the literature. Finally, we
exploit the CRB expression to introduce the new concept of Near Field
Localization (NFL) region for a target localization performance associated to
the application at hand. We illustrate the usefulness of the proposed CRB
derivation and its developments as well as the NFL region concept through
numerical simulations in different scenarios
Audio Modeling based on Delayed Sinusoids
International audienceIn this work, we present an evolution of the DDS (Damped & Delayed Sinusoidal) model introduced within the framework of the general signal modeling. This model is named the Partial Damped & Delayed Sinusoidal (PDDS) model and takes into account a single time delay parameter for a set (sum) of damped sinusoids. This modi- ÂŻcation is more consistent with the transient audio modeling problem. We show the validity of this approach by compari- son with the well-known EDS (Exponentially Damped Sinu- soids) approach. Finally, the performances of three model high-resolution parameter estimation algorithms are com- pared on synthetic fast time-varying signals and on two typ- ical audio transients
Asymptotic Performance for Delayed Exponential Process
International audienceThe damped and delayed sinusoidal (DDS) model can be defined as the sum of sinusoids whose waveforms can be damped and delayed. This model is suitable for compactly modeling short time events. This property is closely related to its ability to reduce the time-support of each sinusoidal component. In this correspondence, we derive exact and approximate asymptotic Cramér–Rao bounds (CRBs) for the DDS model. This analysis shows that this model has better, or at least similar, theoretical performance than the well-known exponentially damped sinusoidal (EDS) model. In particular, the performance in the DDS case is significantly improved compared to that of the EDS for closely spaced sinusoids thanks to the nonzero time delays. Consequently, we can exploit the advantageous properties of the DDS model and, in the same time, we can keep high theoretical model parameter estimation accuracy
Damped and delayed sinuosidal model for transient modeling
International audienceIn this work, we present the Damped and De- layed Sinusoidal (DDS) model, a generalization of the sinu- soidal model. This model takes into account an angular fre- quency, a damping factor, a phase, an amplitude and a time- delay parameter for each component. Two algorithms are introduced for the DDS parameter estimation using a sub- band processing approach. Finally, we derive the Cramer- Rao Bound (CRB) expression for the DDS model and a simulation-based performance analysis in the context of a noisy fast time-varying synthetic signal and in the audio transient signal modeling context
COMMON POLE ESTIMATION WITH AN ORTHOGONAL VECTOR METHOD
International audienceIn some applications as in biomedical analysis, we encounter the problem of estimating the common poles (angularfrequency and damping-factor) in a multi-channel set-up composed as the sum of Exponentially Damped Sinusoids. In this contribution, we propose a new subspace algorithm belonging to the family of the Orthogonal Vector Methods which solves the considered estimation problem. In particular, we expose a root-MUSIC algorithm which deals with damped components for an algorithmic cost comparable to the root- MUSIC for constant modulus components. Finally, we show by means of an example, that the proposed method is efficient, especially for low SNRs
- …