Sincronização de quadro e frequência para OFDM no padrão IEEE 802.15.4g : algoritmos e implementação em hardware

Orientadores: Renato da Rocha Lopes, Eduardo Rodrigues de LimaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: O objetivo deste trabalho é propor métodos de sincronização de quadro e de frequência de portadora para a camada física MR-OFDM do padrão IEEE 802.15.4g, começando pela pesquisa de algoritmos, passando pelas etapas de modelagem e simulação em alto nível, e finalmente implementando e avaliando os métodos propostos em hardware. A sincronização de quadro é o processo responsável por detectar o início do dado transmitido, ou seja, a primeira amostra válida do sinal de interesse. No caso de sistemas OFDM, onde o sinal transmitido é composto por um ou mais símbolos OFDM (cada símbolo sendo composto por uma quantidade fixa de amostras), o objetivo é detectar a borda ou janelamento de tais símbolos OFDM, ou seja, onde começa e termina cada um deles. A sincronização de frequência, por sua vez, consiste em estimar e compensar o erro de frequência de portadora, causado principalmente pelo descasamento dos osciladores do transmissor e do receptor. Com base em estudos preliminares, selecionamos o algoritmo de Minn para a detecção de quadro. Para a correção de erro de frequência, dividimos o processo em duas etapas, como é geralmente proposto na literatura: primeiro, o erro de frequência fracionário é estimado no domínio do tempo durante a detecção de quadro e compensado via rotação de sinal; após a conversão do domínio do tempo para o domínio da frequência, o erro de frequência inteiro é estimado e compensado utilizando um novo e simples algoritmo que será proposto e detalhado neste trabalho. Os algoritmos propostos foram implementados em hardware e uma plataforma de verificação baseada em FPGA foi criada para avaliar o seu desempenho. Os módulos implementados são parte de um projeto que está sendo desenvolvido no Instituto de Pesquisa Eldorado (Campinas) que tem como objetivo implementar em ASIC um transceptor compatível com o padrão IEEE 802.15.4gAbstract: The objective of this work is proposing methods of frame and frequency synchronization for the MR-OFDM PHY of IEEE 802.15.4g standard, starting with the research of state-of-the-art algorithms, passing through modeling, high-level simulations, and finally implementing and evaluating the proposed methods in hardware. Frame synchronization is the process responsible for detecting the beginning of transmitted data and, in the case of OFDM systems, the border of each OFDM symbol, while frequency synchronization consists of estimating and compensating the Carrier Frequency Offset (CFO) caused mainly by a mismatch between the transmitter and receiver oscillators. Based on the initial studies, we selected Minn¿s algorithm for frame detection. For the CFO correction, we split the process into two steps, as commonly proposed in the literature: first, the Fractional CFO is estimated in the time domain during the frame detection and compensated via signal rotation; after the conversion from time to frequency domain, the Integer CFO is estimated and compensated with a novel and simple algorithm that will be detailed in this work. The proposed algorithms were implemented in hardware and inserted in an FPGA-based verification platform for performance measurement. The implemented modules are part of a project that is under development at Eldorado Research Institute (Campinas) and aims to implement in ASIC a transceiver compliant to the IEEE 802.15.4g standardMestradoTelecomunicações e TelemáticaMestra em Engenharia Elétric

Interpretations of Bicoherence in Space & Lab Plasma Dynamics

The application of bicoherence analysis to plasma research, particularly in non-linear, coupled-wave regimes, has thus far been significantly belied by poor resolution in time, and/or outright destruction of frequency information. Though the typical power spectrum cloaks the phase-coherency between frequencies, Fourier transforms of higher-order convolutions provide an n-dimensional spectrum which is adept at elucidating n-wave phase coherence. As such, this investigation focuses on the utility of the normalized bispectrum for detection of wave-wave coupling in general, with emphasis on distinct implications within the scope of non-linear plasma physics. Interpretations of bicoherent features are given for time series from shots at the DIII-D tokamak facility; the solar wind, as measured by the Cluster-II satellite installation; a van der Pol oscillator; and various audio signals, both recorded and contrived. Evaluations of the bicoherence exhibited by simple harmonic relationships are contrasted with those displaying truly non-linear signatures, and the temporal dynamics of their respective bispectra are assessed. Also considered are the curatives and caveats of cogently condensing these 4-dimensional data

Slice-Less Optical Arbitrary Waveform Measurement (OAWM) in a Bandwidth of More than 600 GHz Using Soliton Microcombs

We propose and demonstrate a novel scheme for optical arbitrary waveform measurement (OAWM) that exploits chip-scale Kerr soliton combs as highly scalable multiwavelength local oscillators (LO) for ultra-broadband full-field waveform acquisition. In contrast to earlier concepts, our approach does not require any optical slicing filters and thus lends itself to efficient implementation on state-of-the-art high-index-contrast integration platforms such as silicon photonics. The scheme allows to measure truly arbitrary waveforms with high accuracy, based on a dedicated system model which is calibrated by means of a femtosecond laser with known pulse shape. We demonstrated the viability of the approach in a proof-of-concept experiment by capturing an optical waveform that contains multiple 16 QAM and 64 QAM wavelength-division multiplexed (WDM) data signals with symbol rates of up to 80 GBd, reaching overall line rates of up to 1.92 Tbit/s within an optical acquisition bandwidth of 610 GHz. To the best of our knowledge, this is the highest bandwidth that has so far been demonstrated in an OAWM experiment

Hardware Realization of a Transform Domain Communication System

The purpose of this research was to implement a Transform Domain Communication System (TDCS) in hardware and compare experimental bit error performance with results published in literature. The intent is to demonstrate the effectiveness or ineffectiveness of a TDCS in communicating binary data across a real channel. In this case, an acoustic channel that is laden with narrowband interference was considered. A TDCS user pair was constructed to validate the proposed design using Matlab™ to control a PC sound card. The proposed TDCS design used the Bartlett method of spectrum estimation, the spectral notching algorithm found in TDCS literature, quadrature phase shift keying, and minimum mean square error transverse equalization to mitigate the effects of noise and intersymbol interference. Water-filling was evaluated as an alternative to spectral notching for performing waveform design and is shown to perform equivalently. Validated software was migrated to code suitable for use onboard a Digital Signal Processor Starter Kit (DSK). Two DSK boards were used, one for transmission and reception, and bit error performance results were obtained. Bit error analysis reveals that the TDCS hardware performs approximately the same as literature suggests

Reduced Order Estimation of Time Varying Wireless Channels in Real Life Scattering Environment

This thesis deals with theoretical study and numerical simulation of 2x1 MISO system with Alamouti coding and imperfect channel estimation at the receiver. We adopt two channel models to represent scattering environment. One is Sum of Sinusoids model, which is simple, but does not properly reflect the geometry of scattering environment. The second model uses a set of Modulated Discrete Prolate Spheroidal Sequences to represent the channel in a scenario with scattering from one or more clusters with predefined geometry. The effect of clusters location on estimation quality is examined. Furthermore, we derive reduced complexity Wiener filters for slow flat fading channel estimation in pilot aided receiver. Our approach is based on the approximation of the channel covariance function to zero and second order Taylor series to reduce computational effort of the filter design. Theoretical MMSE is developed, verified through simulation and compared to one of a full Wiener filter

Matched Filtering from Limited Frequency Samples

In this paper, we study a simple correlation-based strategy for estimating the unknown delay and amplitude of a signal based on a small number of noisy, randomly chosen frequency-domain samples. We model the output of this "compressive matched filter" as a random process whose mean equals the scaled, shifted autocorrelation function of the template signal. Using tools from the theory of empirical processes, we prove that the expected maximum deviation of this process from its mean decreases sharply as the number of measurements increases, and we also derive a probabilistic tail bound on the maximum deviation. Putting all of this together, we bound the minimum number of measurements required to guarantee that the empirical maximum of this random process occurs sufficiently close to the true peak of its mean function. We conclude that for broad classes of signals, this compressive matched filter will successfully estimate the unknown delay (with high probability, and within a prescribed tolerance) using a number of random frequency-domain samples that scales inversely with the signal-to-noise ratio and only logarithmically in the in the observation bandwidth and the possible range of delays.Comment: Submitted to the IEEE Transactions on Information Theory on January 13, 201

Efficient channel equalization algorithms for multicarrier communication systems

Blind adaptive algorithm that updates time-domain equalizer (TEQ) coefficients by Adjacent Lag Auto-correlation Minimization (ALAM) is proposed to shorten the channel for multicarrier modulation (MCM) systems. ALAM is an addition to the family of several existing correlation based algorithms that can achieve similar or better performance to existing algorithms with lower complexity. This is achieved by designing a cost function without the sum-square and utilizing symmetrical-TEQ property to reduce the complexity of adaptation of TEQ to half of the existing one. Furthermore, to avoid the limitations of lower unstable bit rate and high complexity, an adaptive TEQ using equal-taps constraints (ETC) is introduced to maximize the bit rate with the lowest complexity. An IP core is developed for the low-complexity ALAM (LALAM) algorithm to be implemented on an FPGA. This implementation is extended to include the implementation of the moving average (MA) estimate for the ALAM algorithm referred as ALAM-MA. Unit-tap constraint (UTC) is used instead of unit-norm constraint (UNC) while updating the adaptive algorithm to avoid all zero solution for the TEQ taps. The IP core is implemented on Xilinx Vertix II Pro XC2VP7-FF672-5 for ADSL receivers and the gate level simulation guaranteed successful operation at a maximum frequency of 27 MHz and 38 MHz for ALAM-MA and LALAM algorithm, respectively. FEQ equalizer is used, after channel shortening using TEQ, to recover distorted QAM signals due to channel effects. A new analytical learning based framework is proposed to jointly solve equalization and symbol detection problems in orthogonal frequency division multiplexing (OFDM) systems with QAM signals. The framework utilizes extreme learning machine (ELM) to achieve fast training, high performance, and low error rates. The proposed framework performs in real-domain by transforming a complex signal into a single 2–tuple real-valued vector. Such transformation offers equalization in real domain with minimum computational load and high accuracy. Simulation results show that the proposed framework outperforms other learning based equalizers in terms of symbol error rates and training speeds