A Consistent OFDM Carrier Frequency Offset Estimator Based on Distinctively Spaced Pilot Tones

A pilot-tone-based maximum likelihood estimator (PBMLE) for carrier frequency offset (CFO) in orthogonal frequency-division multiplexing (OFDM) systems is proposed. To obtain a consistent estimate of the CFO over a frequency-selective fading channel, the proposed method employs a preamble comprising distinctively spaced pilot tones. As a result of this preamble configuration, a large estimation range equal to the bandwidth of the OFDM signal can be achieved. Different from previous ad hoc pilot-tone-based CFO estimators, the PBMLE exploits the relationship between the CFO and the periodogram of the preamble. Analysis shows that the proposed PBMLE is asymptotically unbiased and efficient. To realize this PBMLE in practice, a suboptimal estimator is also introduced, in which a zero-padded fast Fourier transform is invoked and the CFO estimation is split into two phases: coarse and fine estimation. Coarse estimation is obtained through the correlation between the received preamble and its original pattern, whereas fine estimation is obtained by exploiting the magnitude attenuation in the vicinities of those CFO-shifted pilot tones. Both analytical investigations and computer simulations indicate that the accuracy of this simplified suboptimal estimator is proportional to the oversize ratio of zero padding. When the oversize ratio is sufficiently high, the performance of the suboptimal estimator approaches that of the proposed PBMLE.published_or_final_versio

FPGA Implementation of an FFT-Based Carrier Frequency Estimation Algorithm

Carrier synchronization is an essential part of digital communication systems. In essence, carrier synchronization is the process of estimating and correcting any carrier phase and frequency differences between the transmitted and received signals. Typically, carrier synchronization is achieved using a phase lock loop (PLL) system; however, this method is unreliable when experiencing frequency offsets larger than 30 kHz. This thesis evaluates the FPGA implementation of a combined FFT and PLL-based carrier phase synchronization system. The algorithm includes non-data-aided, FFT-based, frequency estimator used to initialize a data-aided, PLL-based phase estimator. The frequency estimator algorithm employs a resource-efficient strategy of averaging several small FFTs instead of using one large FFT, which results in a rough estimate of the frequency offset. Since it is initialized with a rough frequency estimate, this hybrid design allows the PLL to start in a state close to frequency lock and focus mainly on phase synchronization. The results show that the algorithm demonstrates comparable performance, based on performance metrics such as bit-error rate (BER) and estimator error variance, to alternative frequency estimation strategies and simulation models. Moreover, the FFT-initialized PLL approach improves the frequency acquisition range of the PLL while achieving similar BER performance as the PLL-only system

Investigation of Non-coherent Discrete Target Range Estimation Techniques for High-precision Location

Ranging is an essential and crucial task for radar systems. How to solve the range-detection problem effectively and precisely is massively important. Meanwhile, unambiguity and high resolution are the points of interest as well. Coherent and non-coherent techniques can be applied to achieve range estimation, and both of them have advantages and disadvantages. Coherent estimates offer higher precision but are more vulnerable to noise and clutter and phase wrap errors, particularly in a complex or harsh environment, while the non-coherent approaches are simpler but provide lower precision. With the purpose of mitigating inaccuracy and perturbation in range estimation, miscellaneous techniques are employed to achieve optimally precise detection. Numerous elegant processing solutions stemming from non-coherent estimate are now introduced into the coherent realm, and vice versa. This thesis describes two non-coherent ranging estimate techniques with novel algorithms to mitigate the instinct deficit of non-coherent ranging approaches. One technique is based on peak detection and realised by Kth-order Polynomial Interpolation, while another is based on Z-transform and realised by Most-likelihood Chirp Z-transform. A two-stage approach for the fine ranging estimate is applied to the Discrete Fourier transform domain of both algorithms. An N-point Discrete Fourier transform is implemented to attain a coarse estimation; an accurate process around the point of interest determined in the first stage is conducted. For KPI technique, it interpolates around the peak of Discrete Fourier transform profiles of the chirp signal to achieve accurate interpolation and optimum precision. For Most-likelihood Chirp Z-transform technique, the Chirp Z-transform accurately implements the periodogram where only a narrow band spectrum is processed. Furthermore, the concept of most-likelihood estimator is introduced to combine with Chirp Z-transform to acquire better ranging performance. Cramer-Rao lower bound is presented to evaluate the performance of these two techniques from the perspective of statistical signal processing. Mathematical derivation, simulation modelling, theoretical analysis and experimental validation are conducted to assess technique performance. Further research will be pushed forward to algorithm optimisation and system development of a location system using non-coherent techniques and make a comparison to a coherent approach

Non Co-Operative Detection of LPI/LPD Signals Via Cyclic Spectral Analysis

This research proposes and evaluates a novel technique for detecting LPI/LPD communication signals using a digital receiver primarily designed to detect radar signals, such as a Radar Warning Receiver (RWR) or an Electronic Support Measures (ESM) receiver. The proposed Cyclic Spectrum Analysis (CSA) receiver is a robust detector that takes advantage of the spectral correlation properties of second-order cyclostationary signals. A computationally efficient algorithm is used to estimate the Spectral Correlation Function (SCF). Using state-of-the-art FFT processing, it is expected that the proposed CSA receiver architecture could estimate the entire cyclic spectrum m approximately 0.6 ms. The estimate is then reduced to an energy related test statistic that is valid for all cycle frequencies within the receiver bandwidth. By producing an estimate of the cyclic spectrum, the CSA receiver also benefits post-detection tasks such as signal classification and exploitation. As modeled, the ideal CSA receiver detection performance is within 1.0 dB of the radiometer in benign signal environments and consistently outperforms the radiometer in adverse signal environments. The effect on detection performance when the CSA receiver is implemented with channelized and quadrature digital receiver architectures is also examined

Robust synchronization for PSK (DVB-S2) and OFDM systems

The advent of high data rate (broadband) applications and user mobility into modern wireless communications presents new challenges for synchronization in digital receivers. These include low operating signal-to-noise ratios, wideband channel effects, Doppler effects and local oscillator instabilities. In this thesis, we investigate robust synchronization for DVB-S2 (Digital Video Broadcasting via Satellite) and OFDM (Orthogonal Frequency Division Multiplexing) systems, as these technologies are well-suited for the provision of broadband services in the satellite and terrestrial channels respectively.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Practical Aspects of the Frequency Domain Approach for Aircraft System Identification

Practical aspects of the frequency-domain approach for aircraft system identification are explained and demonstrated. Topics related to experiment design, flight data analysis, and dynamic modeling are included. For demonstration purposes, simulated time series data and simulated flight data from an F-16 nonlinear simulation with realistic noise are used. This approach enables detailed evaluations of the techniques and results, because the true characteristics of the data and aircraft dynamics are known for the simulated data. Analytical techniques and practical considerations are examined for the finite Fourier transform, nonparametric frequency response estimation, parametric modeling in the frequency domain, experiment design for frequency-domain modeling, data analysis and modeling in the frequency domain, and real-time calculations. Flight data from a subscale jet transport aircraft are used to demonstrate some of the techniques and technical issues

A Cognitive Radio Compressive Sensing Framework

With the proliferation of wireless devices and services, allied with further significant predicted growth, there is an ever increasing demand for higher transmission rates. This is especially challenging given the limited availability of radio spectrum, and is further exacerbated by a rigid licensing regulatory regime. Spectrum however, is largely underutilized and this has prompted regulators to promote the concept of opportunistic spectrum access. This allows unlicensed secondary users to use bands which are licensed to primary users, but are currently unoccupied, so leading to more efficient spectrum utilization. A potentially attractive solution to this spectrum underutilisation problem is cognitive radio (CR) technology, which enables the identification and usage of vacant bands by continuously sensing the radio environment, though CR enforces stringent timing requirements and high sampling rates. Compressive sensing (CS) has emerged as a novel sampling paradigm, which provides the theoretical basis to resolve some of these issues, especially for signals exhibiting sparsity in some domain. For CR-related signals however, existing CS architectures such as the random demodulator and compressive multiplexer have limitations in regard to the signal types used, spectrum estimation methods applied, spectral band classification and a dependence on Fourier domain based sparsity. This thesis presents a new generic CS framework which addresses these issues by specifically embracing three original scientific contributions: i) seamless embedding of the concept of precolouring into existing CS architectures to enhance signal sparsity for CR-related digital modulation schemes; ii) integration of the multitaper spectral estimator to improve sparsity in CR narrowband modulation schemes; and iii) exploiting sparsity in an alternative, non-Fourier (Walsh-Hadamard) domain to expand the applicable CR-related modulation schemes. Critical analysis reveals the new CS framework provides a consistently superior and robust solution for the recovery of an extensive set of currently employed CR-type signals encountered in wireless communication standards. Significantly, the generic and portable nature of the framework affords the opportunity for further extensions into other CS architectures and sparsity domains

Radio Science Experiment Data Analysis in the framework of the ESA Missions “Venus Express" and “Rosetta"

Occultation measurements exploit an observational geometry in which the spacecraft to Earth communication link is interrupted by the planet itself. Coherent, high-rate (100 ksamples/s) sampling of the down-converted RF incoming signal enables the OL receiving system to safeguard the high dynamics (up to 2 kHz/s) of the weak signals (attenuation > 50dB) emerging from the deep layers of the Venus atmosphere. The purpose of the developed software package, the Open-Loop data processing software (OL SW), is to extract the information embedded in noise by means of an iterative strategy. Essential skill of the OL SW is the progressive reduction of the signal bandwidth while at the same time maintaining high time resolution of the data. This implies high spacial resolution of the sounded media (i.e., the Venus atmosphere) and the capability of resolving effects of multipath propagation