Impact of Imperfect Parameter Estimation on the Performance of Multi-User ARGOS Receivers

In this paper, we analyze the performance of Successive Interference Cancelation (SIC) receivers in the context of the ARGOS satellite system. Multi-user SIC receivers are studied in presence of imperfect estimates of signal parameters. We derive performance graphs that show the parameter ranges over which a successful demodulation of all users is possible. First, the graphs are derived in the context of perfect parameter estimation. Then, imperfect parameter estimation is considered. Erroneous estimations affect both the amplitude and the time delay of the received signal. Carrier frequencies are assumed to be accurately measured by the receiver. ARGOS SIC receivers are shown to be both robust to imperfect amplitude estimation and sensitive to imperfect time delay estimation

Parameter Estimation for a Sinusoidal Signal with a Time-Varying Amplitude

This paper addresses the parameter estimation problem of a non-stationary sinusoidal signal with a timevarying amplitude, which is given by a known function of time multiplied by an unknown constant coefficient. A robust estimation algorithm is proposed for identifying the unknown frequency and the amplitude coefficient in real-time. The estimation algorithm is constructed based on the Volterra integral operator with suitably designed kernels and sliding mode adaptation laws. It is shown that the parameter estimation error converges to zero within an arbitrarily small finite time, and the robustness against bounded additive disturbances is certified by bounded-input-bounded-output arguments. The effectiveness of the estimation technique is evaluated and compared with other existing tools through numerical simulations

Algebraic parameter estimation of a biased sinusoidal waveform signal from noisy data

International audienceThe amplitude, frequency and phase of a biased and noisy sum of two complex exponential sinusoidal signals are estimated via new algebraic techniques providing a robust estimation within a fraction of the signal period. The methods that are popular today do not seem able to achieve such performances. The efficiency of our approach is illustrated by several computer simulations

Robust Pilot Decontamination Based on Joint Angle and Power Domain Discrimination

We address the problem of noise and interference corrupted channel estimation in massive MIMO systems. Interference, which originates from pilot reuse (or contamination), can in principle be discriminated on the basis of the distributions of path angles and amplitudes. In this paper we propose novel robust channel estimation algorithms exploiting path diversity in both angle and power domains, relying on a suitable combination of the spatial filtering and amplitude based projection. The proposed approaches are able to cope with a wide range of system and topology scenarios, including those where, unlike in previous works, interference channel may overlap with desired channels in terms of multipath angles of arrival or exceed them in terms of received power. In particular we establish analytically the conditions under which the proposed channel estimator is fully decontaminated. Simulation results confirm the overall system gains when using the new methods.Comment: 14 pages, 5 figures, accepted for publication in IEEE Transactions on Signal Processin

Estimation algébrique des paramètres intrinsèques d'un signal sinusoïdal biaisé en environnement bruité

International audienceThe amplitude, frequency and phase of a biased and noisy sinusoidal signal are estimated via algebraic techniques. The methods which are popular today seem unable to obtain a robust estimation of those parameters within a fraction of the signal's period. The e ciency of our approach is illustrated by several computer simulations.L'amplitude, la fréquence et la phase d'un signal sinusoïdal, biaisé et bruité, sont estimées par des techniques algébriques. Les méthodes d'aujourd'hui ne semblent pas capables de fournir ces paramètres de façon robuste en une fraction de période du signal. Plusieurs simulations numériques confirment l'intérêt de notre approche

Adaptive Waveforms for Flow Velocity Estimation Using Acoustic Signals

International audienceIn this paper, we introduce a general framework for waveform design and signal processing, dedicated to the study of turbulent flow phenomena. In a bi-static configuration, by transmitting a specific waveform with a predefined instantaneous frequency law (IFL), within the bounds of the Kolmogorov spectrum, the turbulent media will modify the IFL at the receiving side. We propose a new methodology to estimate this change and to exploit it for velocity estimation using acoustic signals. In this way, the amplitude based velocity estimation techniques can be substituted by non stationary time - frequency signal processing. This technique proves to be more robust in terms of interferences and can provide a more detailed representation of any turbulent environment

Frequency-Locked Loop Based Estimation of Single-Phase Grid Voltage Parameters

Estimation of amplitude, instantaneous phase, and frequency of a single-phase grid voltage signal are studied in this letter. The proposed approach uses a novel circular limit cycle oscillator (CLO) coupled with a frequency-locked loop. Due to the nonlinear structure of the CLO, the proposed frequency adaptive CLO technique is robust against various perturbations faced in the practical settings, e.g., the discontinuous jump of phase, frequency, and amplitude. The global stability analysis of the CLO and local stability analysis of the frequency adaptive CLO are performed. Experimental results demonstrate the effectiveness of the proposed technique over a very recent technique proposed in the literature