Phase noise mitigation in the autocorrelation estimates with data windowing: The case of two close sinusoids

14th European Signal Processing Conference, EUSIPCO 2006; Florence; Italy; 4 September 2006 through 8 September 2006We address the phase noise and the superresolution problem in Toeplitz matrix-based spectral estimates. The Toeplitz autocorrelation (AC) matrix approach in spectral estimation brings in an order of magnitude computational advantage while the price paid is the phase noise that becomes effective at high signal-to-noise ratios (SNR). This noise can be mitigated with windowing the data though some concomitant loss in resolution occurs. The trade-offs between additive noise SNR, resolvability of sinusoids closer than the resolution limit, and behavior of the estimated AC lags and tone frequencies are investigated

Removal of the phase noise in the autocorrelation estimates with data windowing

13th European Signal Processing Conference, EUSIPCO 2005; Antalya; Turkey; 4 September 2005 through 8 September 2005The sinusoidal frequency estimation from short data records based on Toeplitz autocorrelation (AC) matrix estimates suffer from phase noise. This effect becomes prominent especially when additive noise vanishes becoming a nuisance, that is at high signal-to-noise ratios (SNR). Based on both analytic derivation of the AC lag terms and simulation experiments, we show that data windowing can mitigate the limitations caused by the phase noise. Thus with proper windowing, the variance of the frequency estimate is no more limited by phase noise, but it continues to decrease linearly with the SNR. The cases of the Pisarenko frequency estimator and of MUSIC, both for the single sinusoid case, are analyzed in detail

Frequency Estimation Of Single-Tone Sinusoids Under Additive And Phase Noise

We investigate the performance of main frequency estimation methods for a single-component complex sinusoid under complex additive white Gaussian noise (AWGN) as well as phase noise (PN). Two methods are under test: Maximum Likelihood (ML) method using Fast Fourier Transform (FFT), and the autocorrelation method (Corr). Simulation results showed that FFT-method has superior performance as compared to the Corr-method in the presence of additive white Gaussian noise (affecting the amplitude) and phase noise, with almost 20dB difference

Enhancing the Instantaneous Dynamic Range of Electronic Warfare Receivers Using Statistical Signal Processing

Accurately processing multiple, time-coincident signals presents a challenge to Electronic Warfare (EW) receivers, especially if the signals are close in frequency and/or mismatched in amplitude. The metric that quantifies an EW receiver\u27s ability to measure time-coincident signals is the Instantaneous Dynamic Range (IDR), defined for a given frequency estimation accuracy, a given frequency separation and a given SNR as the maximum signal amplitude ratio that can be accommodated. Using a two sinusoid time-series model, this thesis analyzes IDR for ideal intercept and parametric digital EW receivers. In general, the number of signals contained in the EW receiver measurement interval is unknown. Thus, the non-parametric Discrete Fourier Transform (DFT) is employed in an EW intercept receiver with the associated amplitude dependent spectral leakage which limits IDR. A novel method to improve the DFT-based intercept receiver IDR by compensating for the high amplitude signal\u27s spectral leakage using computationally efficient 3 bin interpolation algorithms is proposed and analyzed. For a desired frequency estimation accuracy of 1.5 bins, the method achieves an IDR of 57 dB with little frequency separation dependence when the signals are separated by more than 2 bins with a low amplitude signal SNR of 10 dB. For situations where the number of signals contained in the measurement interval is known, the IDR of an Iterative Generalized Least Squares (IGLS) algorithm-based parametric receiver is analyzed. A real and complex signal IDR Cramer-Rao Bound (IDR-CRB) is derived for parametric receivers by extending results contained in Rife. For tight frequency estimate requirements (these requirements depend on the number of measurement samples), the IDR-CRB yields achievable bounds. For less stringent frequency estimate requirements, the IDR-CRB is unrealisti

Detection and cancellation of sinusoidal fading power variation in wireless communication systems

Fading channel estimation in wireless communication systems depends on an expected model for fading and any assumptions made about the channel itself. The bit error rate (BER) performance of the communication system is affected by how closely these assumptions made in designing the estimation technique match the deployment environment. Any unforeseen disturbances or hindrances in the environment deteriorate the BER performance of the system when the estimation system is not designed to combat such disturbances. To deal with such unforeseen obstacles, additional mathematical models can be proposed to model such disturbances and then the estimation techniques can either be reinforced with modular systems which work with the proposed models, or be redesigned as a whole with the help of actual observed data of the disturbances. The current thesis deals with such a scenario where sinusoidal variation is expected in the received power in addition to fading. A mathematical model of such power variation is assumed and a modular scheme is proposed to detect and combat the sinusoidal variation. The proposed scheme is tested by employing it in a simulated Multiple Input Multiple Output (MIMO) wireless communication system which adopts Space Time Block Coding (STBC) techniques --Abstract, page iii

SDPLL-Based Frequency Estimation of a Sinusoid in Colored Noise

The problem of frequency estimation of a single sinusoid observed in colored noise is addressed. Our estimator is based on the operation of the sinusoidal digital phase-locked loop (SDPLL) which carries the frequency information in its phase error after the noisy sinusoid has been acquired by the SDPLL. We show by computer simulations that this frequency estimator beats the Cramer-Rao bound (CRB) on the frequency error variance for moderate and high SNRs when the colored noise has a general low-pass filtered (LPF) characteristic, thereby outperforming, in terms of frequency error variance, several existing techniques some of which are, in addition, computationally demanding. Moreover, the present approach generalizes on existing work that addresses different methods of sinusoid frequency estimation involving specific colored noise models such as the moving average (MA) noise model. An insightful theoretical analysis is presented to support the practical findings

Wavelet Domain Communication System (WDCS): Packet-Based Wavelet Spectral Estimation and M-ARY Signaling

A recently proposed Wavelet Domain Communication System (WDCS) using transform domain processing demonstrated excellent interference avoidance capability under adverse environmental conditions. This work extends previous results by: 1) incorporating a wavelet packet decomposition technique, 2) demonstrating M-Ary signaling capability, and 3) providing increased adaptivity over a larger class of interference signals. The newly proposed packet-based WDCS is modeled and its performance characterized using MATLAB®. In addition, the WDCS response to two scenarios simulating Doppler effects and physical separation of transceivers are obtained. The fundamental metric for analysis and performance evaluation is bit error rate (Pb). Relative to the previous non-packet WDCS, the proposed packet-based WDCS provides improved/comparable bit error performance in several interference scenarios single-tone, multiple-tone, swept-tone, and partial band interference is considered. Interference avoidance capability was characterized for a bit energy-to-noise power level (Eb/N0) of 4.0 dB and interference energy-to-signal energy (I/E) ratios ranging from 0.0 dB to 16.0 dB. For binary, 4-Ary, and 8-Ary CSK data modulations, the packet-based WDCS exhibited average Pb improvements of 6.7, 9.2, and 12.0 dB, respectively, for partial band and swept-tone interference. For single and multiple-tone interference, improvements of 8.0, 12.4, and 15.7 dB were realized. Furthermore, bit error sensitivity analyses indicate the WDCS communicates effectively under non-ideal real-world conditions (transceivers located in dissimilar environments) while exhibiting average Pb improvements of 5.4, 5.1, and 5.8 dB, relative to systems having no interference suppression

Filtering techniques for mitigating microwave oven interference on 802.11b wireless local area networks

Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 165-169).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.With the increasing popularity and assimilation of wireless devices into the everyday lives of people, the issue of their feasibility for coexisting with other radio frequency (RF) devices arises. Particularly strong interferers for the IEEE 802.11b standard are microwave ovens, since both operate at 2.4 GHz. The interference mitigation techniques all exploit the differences between the interference and the signal, since the former is sinusoidal in nature while the latter can be viewed as noise. The first mitigation filter operates in the frequency domain and filters the received signal's Fast Fourier Transform (FFT) sequence by detecting and removing peak sinusoidal components over the flat 3- dB bandwidth of the signal. The second is a Least Mean Square (LMS) Adaptive filter that produces an estimate of the interference through a recursive approximation method and subtracts it out from the received signal. The third and last is the Adaptive Notch Filter (ANF) which implements a lattice structure and has a time-varying notch frequency parameter that converges to and tracks the frequency of the interference in the received signal. The three filters are shown to produce improvements in the bit error rate (BER) and frame error rate (FER) performance of the receiver under various relative strengths of the signal with respect to the interference.by Lorenzo M. Lorilla.M.Eng.and S.B

Fast channel estimation in the transformed spatial domain for analog millimeter wave systems

Fast channel estimation in millimeter-wave (mmWave) systems is a fundamental enabler of high-gain beamforming, which boosts coverage and capacity. The channel estimation stage typically involves an initial beam training process where a subset of the possible beam directions at the transmitter and receiver is scanned along a predefined codebook. Unfortunately, the high number of transmit and receive antennas deployed in mmWave systems increase the complexity of the beam selection and channel estimation tasks. In this work, we tackle the channel estimation problem in analog systems from a different perspective than used by previous works. In particular, we propose to move the channel estimation problem from the angular domain into the transformed spatial domain, in which estimating the angles of arrivals and departures corresponds to estimating the angular frequencies of paths constituting the mmWave channel. The proposed approach, referred to as transformed spatial domain channel estimation (TSDCE) algorithm, exhibits robustness to additive white Gaussian noise by combining low-rank approximations and sample autocorrelation functions for each path in the transformed spatial domain. Numerical results evaluate the mean square error of the channel estimation and the direction of arrival estimation capability. TSDCE significantly reduces the first, while exhibiting a remarkably low computational complexity compared with well-known benchmarking schemes