This thesis presents a novel method to solve the problem of estimating the carrier frequency set in an Orthogonal Frequency Division Multiplexing (OFDM) system. The approach is based on the minimization of the probability of symbol error. Hence, this approach is called the Minimum Symbol Error Rate (MSER) approach. An existing approach based on Maximum Likelihood (ML) is chosen to benchmark the performance of the MSER-based algorithm. The MSER approach is computationally intensive. The thesis evaluates the approximations that can be made to the MSER-based objective function to make the computation tractable. A modified gradient function based on the MSER objective is developed which provides better performance characteristics than the ML-based estimator. The estimates produced by the MSER approach exhibit lower Mean Squared Error compared to the ML benchmark. The performance of MSER-based estimator is simulated with Quaternary Phase Shift Keying (QPSK) symbols, but the algorithm presented is applicable to all complex symbol constellations.

In OFDM systems carrier frequency offset is observed due to Doppler shift and transmitter-receiver frequency mismatches. This offset induces ICI (Intercarrier Interference). In this thesis, repeated data methods and pilot-aided carrier frequency offset(CFO) estimation methods and windowing techniques are used to mitigate the frequency offset problem and a performance comparison is made between these ICI cancellation techniques. Repeated data methods use only half of the bandwidth for information transmission to eliminate the ICI at the receiver. We have implemented repeated data methods including Self cancellation scheme and Symmetric Symbol Repetition (SSR) schemes to overcome ICI problem. We have also implemented Adjacent Conjugate Symbol Repetiton (ACSR) and Symmetric Conjugate Symbol Repetiton (SCSR) methods to mitigate both phase rotations and ICI. CFO estimation and correction methods generally use pilot sequences. We implemented the &ldquo / Conventional Pilots&rdquo / and &ldquo / Clustered Pilots&rdquo / pilot-aided CFO estimation techniques for ICI cancellation. Furthermore, we also implemented a new scheme by using the odd symmetry between pilot symbols. Nyquist windowing techniques apply windowing at the receiver side. We have implemented second order polynomial class of Nyquist windows and Nyquist window with Franks pulse used to mitigate ICI. These ICI cancellation methods are compared in AWGN and multipath Rayleigh fading channel models in terms of BER and carrier to interference ratio. It is shown that repeated data methods shows better performances than pilot-aided CFO estimation methods with a cost of increased bandwidth usage especially in high SNR&rsquo / s.

Cooperative relaying systems aim to improve weak communication links by exploiting the spatial diversity obtained by the statistically independent channels between relays and the destination. In this thesis a cooperative relaying scheme called the Opportunistic Multiple Relaying (OMR) is proposed with its special receiver structure. Unlike most relaying schemes in the literature, multiple relay nodes are allowed to transmit in nonorthogonal channels in OMR without requiring any control overhead for relay coordination. OMR is compared to a benchmark scheme called the Selection Relaying (SR) in which the relay node is preselected by the source before transmission according to the average channel quality information. It is observed that OMR performs significantly better than SR in terms of error performance.

Dans les systèmes de transmission multiporteuses et impliquant plusieurs utilisateurs, deux phénomènes viennent perturber la réception et la détection de symboles : le canal de propagation et le décalage des fréquences porteuses (DFP). Cette thèse traite de techniques d’égalisation et de synchronisation en fréquence reposant sur des techniques de type Kalman telles que le filtrage de Kalman étendu (EKF) du 1er ou du 2nd ordre, le filtrage de Kalman étendu itératif ou le filtrage de Kalman par sigma point (SPKF). Pour relaxer les hypothèses de Gaussianité sur les bruits de mesure et de modèle dans la représentation dans l’espace d’état, des approches de type H[infini] sont aussi étudiées.Ces méthodes sont ensuite exploitées dans des systèmes de type OFDMA ou OFDM-IDMA et sont combinées avec d’autres approches (MMSE-SD, tests statistiques, etc.) pour mettre en œuvre des récepteurs pouvant être notamment robustes à des interférences large bande, comme c’est le cas dans des applications de radio intelligence. / Multicarrier modulation is the common feature of high-data rate mobile wirelesssystems. In that case, two phenomena disturb the symbol detection. Firstly,due to the relative transmitter-receiver motion and a difference between the localoscillator (LO) frequency at the transmitter and the receiver, a carrier frequencyoffset (CFO) affects the received signal. This leads to an intercarrier interference(ICI). Secondly, several versions of the transmitted signal are received due to thewireless propagation channel. These unwanted phenomena must be taken intoaccount when designing a receiver. As estimating the multipath channel and theCFO is essential, this PhD deals with several CFO and channel estimation methodsbased on optimal filtering.Firstly, as the estimation issue is nonlinear, we suggest using the extended Kalmanfilter (EKF). It is based on a local linearization of the equations around the laststate estimate. However, this approach requires a linearization based on calculationsof Jacobians and Hessians matrices and may not be a sufficient descriptionof the nonlinearity. For these reasons, we can consider the sigma-point Kalmanfilter (SPKF), namely the unscented Kalman Filter (UKF) and the central differenceKalman filter (CDKF). The UKF is based on the unscented transformationwhereas the CDKF is based on the second order Sterling polynomial interpolationformula. Nevertheless, the above methods require an exact and accurate apriori system model as well as perfect knowledge of the additive measurementnoisestatistics. Therefore, we propose to use the H∞ filtering, which is known tobe more robust to uncertainties than Kalman filtering. As the state-space representationof the system is non-linear, we first evaluate the “extended H∞ filter”,which is based on a linearization of the state-space equations like the EKF. As analternative, the “unscented H∞ filter”, which has been recently proposed in theliterature, is implemented by embedding the unscented transformation into the“extended H∞ filter” and carrying out the filtering by using the statistical linearerror propagation approach.The above techniques have been implemented in different multicarrier contexts:Firstly, we address the estimation of the multiple CFOs and channels by meansof a control data in an uplink orthogonal frequency division multiple access(OFDMA) system. To reduce the amount of control data, the optimal filteringtechniques are combined in an iterative way with the so-called minimum meansquare error successive detector (MMSE-SD) to obtain an estimator that doesnot require pilot subcarriers.

Parameter estimation and signal detection are the two key components of a wireless communication system. They directly impact the bit-error-ratio (BER) performance of the system. Several criteria have been successfully applied for parameter estimation and signal detection. They include maximum likelihood (ML), maximum a-posteriori probability (MAP), least square (LS) and minimum mean square error (MMSE) etc. In the linear detection framework, linear MMSE (LMMSE) and LS are the most popular ones. Nevertheless, these criteria do not necessarily minimize the BER, which is one of the key aspect of any communication receiver design. Thus, minimization of BER is tantamount to an important design criterion for a wireless receiver, the minimum bit/symbol error ratio (MBER/MSER). We term this design criterion as the minimum-error-probability (MEP). In this thesis, parameter estimation and signal detection have been extensively studied based on the MEP framework for various unexplored scenar-ios of a wireless communication system. Thus, this thesis has two broad categories of explorations, first parameter estimation and then signal detection. Traditionally, the MEP criterion has been well studied in the context of the discrete signal detection in the last one decade, albeit we explore this framework for the continuous parameter es-timation. We first use this framework for channel estimation in a frequency flat fading single-input single-output (SISO) system and then extend this framework to the carrier frequency offset (CFO) estimation of multi-user MIMO OFDM system. We observe a reasonably good SNR improvement to the tune of 1 to 2.5 dB at a fixed BER (tentatively at 10−3). In this context, it is extended to the scenario of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) or MIMO-OFDM with pa-rameter estimation error statistics obtained from LMMSE only and checked its effect at the equalizer design using MEP and LMMSE criteria. In the second exploration of the MEP criterion, it is explored for signal detection in the context of MIMO-relay and MIMO systems. Various low complexity solutions are proposed to alleviate the effect of high computational complexity for the MIMO-relay. We also consider various configurations of relay like cognitive, parallel and multi-hop relaying. We also propose a data trans-mission scheme with a rate of 1/Ns (Ns is the number of antennas at the transmitter) with the help of the MEP criterion to design various components. In all these cases, we obtain considerable BER improvement compared to the existing solutions.