Orthogonal Frequency Division Multiplexing (OFDM) plays an important role in the implementation of high data rate communication. In this thesis, the problems of data detection and channel and carrier frequency offset estimation in OFDM systems are studied. <p>Multi-symbol non-coherent data detection is studied which performs data detection by processing multiple symbols without the knowledge of the channel impulse response (CIR). <p>For coherent data detection, the CIR needs to be estimated. Our objective in this thesis is to work on blind channel estimators which can extract the CIR using just one block of received OFDM data. A blind channel estimator for (Single Input Multi Output) SIMO OFDM systems is derived. The conditions under which the estimator is identifiable is studied and solutions to resolve the phase ambiguity of the proposed estimator are given.<p>A channel estimator for superimposed OFDM systems is proposed and its CRB is derived. The idea of simultaneous transmission of pilot and data symbols on each subcarrier, the so called superimposed technique, introduces the efficient use of bandwidth in OFDM context. Pilot symbols can be added to data symbols to enable CIR estimation without sacrificing the data rate. Despite the many advantages of OFDM, it suffers from sensitivity to carrier frequency offset (CFO). CFO destroys the orthogonality between the subcarriers. Thus, it is necessary for the receiver to estimate and compensate for the frequency offset. Several high accuracy estimators are derived. These include CFO estimators, as well as a joint iterative channel/CFO estimator/data detector for superimposed OFDM. The objective is to achieve CFO estimation with using just one OFDM block of received data and without the knowledge of CIR.

A successive interference cancellation (SIC) structure is proposed for multiuser interference cancellation (MUI) due to carrier frequency offsets (CFOs) in the uplink of orthogonal frequency division multiple access (OFDMA) systems. The proposed architecture adopts a circular convolution to suppress the impacts caused by CFOs. This paper demonstrates that, with 2 iterations, the SIC has better performance than that of the parallel interference cancellation (PIC), but system complexity is only 1/2K, where K is the number of users in the uplink of OFDMA system. This study also shows that system complexity can be significantly reduced if proper approximation is made.

Synchronization is a challenging but very important task in communications. In digital communication systems, a hierarchy of synchronization problems has to be considered: carrier synchronization, symbol timing synchronization and frame synchronization. For bandwidth efficiency and burst transmission reasons, the former two synchronization steps tend to favor non-data aided (NDA or blind) techniques, while in general, the last one is usually solved by inserting repetitively known bits or words into the data sequence, and is referred to as a data-aided (DA) approach. Over the last two decades, extensive research work has been carried out to design nondata-aided timing recovery and carrier synchronization algorithms. Despite their importance and spread use, most of the existing blind synchronization algorithms are derived in an ad-hoc manner without exploiting optimally the entire available statistical information. In most cases their performance is evaluated by computer simulations, rigorous and complete performance analysis has not been performed yet. It turns out that a theoretical oriented approach is indispensable for studying the limit or bound of algorithms and comparing different methods. The main goal of this dissertation is to develop several novel signal processing frameworks that enable to analyze and improve the performance of the existing timing recovery and carrier synchronization algorithms. As byproducts of this analysis, unified methods for designing new computationally and statistically efficient (i.e., minimum variance estimators) blind feedforward synchronizers are developed. Our work consists of three tightly coupled research directions. First, a general and unified framework is proposed to develop optimal nonlinear least-squares (NLS) carrier recovery scheme for burst transmissions. A family of blind constellation-dependent optimal "matched" NLS carrier estimators is proposed for synchronization of burst transmissions fully modulated by PSK and QAM-constellations in additive white Gaussian noise channels. Second, a cyclostationary statistics based framework is proposed for designing computationally and statistically efficient robust blind symbol timing recovery for time-selective flat-fading channels. Lastly, dealing with the problem of frame synchronization, a simple and efficient data-aided approach is proposed for jointly estimating the frame boundary, the frequency-selective channel and the carrier frequency offset.

This master thesis analyzes the effect of Carrier Frequency Offsets (CFO) on LTEuplink transmission, which is the main cause of ICI (Inter Carrier Interference) andMAI (Multiuser Access Interference). A model of the LTE uplink is required toconduct the study and is implemented in MATLAB, in compliance with 3GPPspecifications. The model can generate uplink signal as generated by the UE, (UserEquipment) and it supports multiple channel bandwidths described by the 3GPP.The channel estimation is done with the help of block type pilots. The model is usedto simulate the experimental conditions. The presence of CFO results in poor systemperformance. Therefore, many algorithms have been proposed for the CFOcancellation such as Successive Interference Cancellation (SIC), Parallel InterferenceCancellation (PIC) and Inverse Interference Matrix Cancellation. As the topic is verybroad, I investigate the performance of Inverse Interference Matrix Cancellationalgorithm. Compared with the other CFO cancellation algorithms this algorithm candirectly estimate the interference components from the inverse pilot matrix, thusthere is no need for CFO estimation. Simulation results show that the algorithm isvery effective in the presence of CFO. The channel estimation technique used is theLeast Square (LS) method and frequency selective channel is used for simulation.Performance graphs are plotted in terms of BER (Bit Error Rate) against differentvalues of SNR (Signal to Noise Ratio).

Abstract In this thesis, iterative detection and estimation algorithms for digital communications systems in the presence of parametric uncertainty are explored and further developed. In particular, variational methods, which have been extensively applied in other research fields such as artificial intelligence and machine learning, are introduced and systematically used in deriving approximations to the optimal receivers in various channel conditions. The key idea behind the variational methods is to transform the problem of interest into an optimization problem via an introduction of extra degrees of freedom known as variational parameters. This is done so that, for fixed values of the free parameters, the transformed problem has a simple solution, solving approximately the original problem. The thesis contributes to the state of the art of advanced receiver design in a number of ways. These include the development of new theoretical and conceptual viewpoints of iterative turbo-processing receivers as well as a new set of practical joint estimation and detection algorithms. Central to the theoretical studies is to show that many of the known low-complexity turbo receivers, such as linear minimum mean square error (MMSE) soft-input soft-output (SISO) equalizers and demodulators that are based on the Bayesian expectation-maximization (BEM) algorithm, can be formulated as solutions to the variational optimization problem. This new approach not only provides new insights into the current designs and structural properties of the relevant receivers, but also suggests some improvements on them. In addition, SISO detection in multipath fading channels is considered with the aim of obtaining a new class of low-complexity adaptive SISOs. As a result, a novel, unified method is proposed and applied in order to derive recursive versions of the classical Baum-Welch algorithm and its Bayesian counterpart, referred to as the BEM algorithm. These formulations are shown to yield computationally attractive soft decision-directed (SDD) channel estimators for both deterministic and Rayleigh fading intersymbol interference (ISI) channels. Next, by modeling the multipath fading channel as a complex bandpass autoregressive (AR) process, it is shown that the statistical parameters of radio channels, such as frequency offset, Doppler spread, and power-delay profile, can be conveniently extracted from the estimated AR parameters which, in turn, may be conveniently derived via an EM algorithm. Such a joint estimator for all relevant radio channel parameters has a number of virtues, particularly its capability to perform equally well in a variety of channel conditions. Lastly, adaptive iterative detection in the presence of phase uncertainty is investigated. As a result, novel iterative joint Bayesian estimation and symbol a posteriori probability (APP) computation algorithms, based on the variational Bayesian method, are proposed for both constant-phase channel models and dynamic phase models, and their performance is evaluated via computer simulations.

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Approved for public release; distribution in unlimited. / OFDM is a modulation technique that achieves high data rates, increased bandwidth efficiency and robustness in multipath environments. However, OFDM has some disadvantages, such as sensitivity to channel fading, large peak to average ratio and sensitivity to frequency offset. The latter causes intercarrier interference (ICI) and a reduction in the amplitude of the desired subcarrier which results in loss of orthogonality. In this thesis, the effects of frequency offset are studied in terms of loss of orthogonality. A number of techniques for frequency offset estimation are presented and tested in computer simulations. / Lieutenant Junior Grade, Turkish Navy

This thesis proposes a blind receiver for the Nyquist pulse shaped quadratureamplitude modulation (QAM) signals. The focus is on single carrier signals. The blind receiver includes the estimation of the symbol rate, the roll-off factor of the filter, the optimal sample phase, the frequency offset, the phase offset and as well as the correction of frequency and phase offsets. The blind receiver is proposed for the cognitive radio applications. Cognitive radios are intelligent devices which can adapt themselves according to its user and its environment, i.e. they are aware of the user and the environment. Another importance of cognitive radios is they can detect the incoming signal and demodulate it and also respond to the transmitting node with the same parameters. In order to demodulate the signal and to respond the transmitter node, there are some parameters which are needed to be known. The estimation starts with the bandwidth and carrier frequency, continued by the estimation of the symbol rate, which is a crucial factor. After the estimation and restrictions of these parameters, the roll-off factor of the filter is estimated for match filtering to remove the inter symbol interference (ISI) effect. Then the optimal sample phase is detected and the signal is downsampled. The following procedures include the modulation identification and estimation and correction of both frequency and phase offsets. The estimation algorithms performance is compared to the performances of the other algorithms available in the literature. These simulation results are presented and discussed in this thesis.

The recent advance in Field Programmable Gate Array (FPGA) technology has been largely embraced by the communication industry, which views this technology as an effective and economical alternative to the design of Application Specific Integrated Circuits (ASICs). The primary reasons for switching to FPGAs are lower development and non-recurring engineering costs, the flexibility to design to a preliminary standard and adapt the design as the standard evolves, as well as the option of performing software updates in the field.<p> A sector with strong interest in FPGAs is the coaxial cable TV/Internet distribution industry. The creation of soft preliminary standards by the standards organization governing the industry has been the main catalyst for the massive adoption of FPGAs by small to medium size companies, which see this technology as an opportunity to compete in this open market.<p> Both the circuit speed and the economy of FPGA technology depend upon using algorithms that map efficiently into its fabric. Often it is prudent to sacrifice performance to improve either clock speed or economy when developing with FPGAs. The purpose of this research is to both revise and devise synchronization algorithms / structures for cable digital receivers that are to be implemented in FPGA. <p> The main communication scheme used by the coaxial cable distribution industry is digital Quadrature Amplitude Modulation (QAM). The problem of synchronizing to the QAM signal in the receiver is not a new topic and several synchronization-related circuits, which were devised with ASICs implementation in mind, can be found in the open literature. Of interest in this thesis is the non-data-aided digital timing synchronizer that was proposed by D'Andrea to recover timing with no knowledge of the transmitted data. Accurate timing estimation was achieved by reshaping the received signal with a prefilter prior to estimating the timing. <p> A problem with D'Andrea's synchronizer is that the prefilter for reshaping the signal is a relatively long Finite Impulse Response (FIR) filter, whose implementation requires a large number of multipliers. This may not have been an issue with ASICs in as much as the number of hardwired multipliers on a chip is not limited as it is in an FPGA chip. One contribution in this research is to propose an alternative to D'Andrea's synchronizer by replacing the long FIR filter with two single-pole Infinite Impulse Response (IIR) filters that are directly placed inside the timing recovery loop. This novel architecture, which drastically reduces the number of multipliers, is well suited for FPGA implementation.<p> Non-data-aided feedforward synchronizers, which use the same prefilter as D'Andrea's synchronizer, have been receiving significant attention in recent years. Detailed performance analysis for these synchronizers can be found in the open literature. These synchronizers have the advantage of using a feedfordward structure rather than a feedback structure, as it is the case in D'Andrea's synchronizer, to estimate the timing. While D'Andrea's synchronizer has an advantage in performance over a non-data-aided feedforward synchronizer, this has not been reported in the literature. In this thesis a second contribution consists of thoroughly analyzing the steady state timing jitter in D'Andrea synchronizer by deriving a closed-form expression for the noise power spectrum and a simple equation to estimate the timing jitter variance. <p> A third contribution is a novel low-complexity and fast acquisition coherent detector for the detection of Quadrature Phase Shift Keying (QPSK) (i.e., 4-QAM) symbols. This detector performs carrier phase synchronization much faster than a conventional coherent detector. The acquisition time is comparable to that of a differential detector. The fast acquisition comes at the expense of phase jitter, and the end result is a 1 dB performance loss over theoretical coherent detection. This detector can be used in place of the differential detector with no economic penalty. Doing so yields a performance advantage of about 2 dB over differential detection.