<p> In this thesis, we present three algorithms for blind estimation of the finite impulse response (FIR) channels in the presence of unknown noise. The algorithms are developed considering different available system resources: 1) If only one receiving antenna is available, based on the single-input-single-output (SISO) system model, with the output being up-sampled, we develop the maximum a posteriori (MAP) algorithm for Gaussian distributed noise. With large enough samples being collected, during which the channel keeps invariant, an efficient implementation of the MAP algorithm is also obtained; 2) If two receiving antennae can be affordable, based on the singleinput-multiple-output (SIMO) system model and up-sampling both the outputs, we develop a subspace based algorithm utilizing Canonical Correlation Decomposition (CCD) to obtain the subspaces, and a maximum likelihood (ML) based algorithm which starts from the Gaussian distributed projection error from the noise subspace onto the COD-estimated signal subspace. The developed channel estimators achieve superior performance measured by the normalized root mean square error (NRMSE), compared with some existing second-order-statistics (SOS) based methods while keeping the computation complexity comparable. When more than two receiving antennae are available, by treating them as one group and applying the MAP algorithm or separating them into two groups and applying the CCD based algorithms, the channels can still be blindly estimated with or without up-sampling the outputs. </p> / Thesis / Master of Applied Science (MASc)

ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / Spatial multiplexing (SM) systems have received significant attention because the architecture offers high spectral efficiency. However, relatively little research exists on optimization of SM systems in the presence of jamming. In a spatially uncoded SM system, such as V-BLAST, the channel state information is assumed to be unavailable a priori at both transmitter and receiver. Here, Kalman filtering is used to estimate the Rayleigh fading channel at the receiver. The spatial correlation of the jammer plus noise is also estimated, and spatial whitening to reject the jammers is employed in both the Kalman channel estimator and detector. To avoid the exponential complexity of maximum-likelihood (ML) detection, the QRD-M algorithm is employed. In contrast to sphere decoding, QRD-M has fixed decoding complexity of order O(M), and is thus attractive for hardware implementation. The performance of the joint Kalman filter channel estimator, spatial whitener and QRD-M detector is verfied by simulations.

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / An acoustic modem employing direct-sequence spread-spectrum (DSSS) signaling is considered with LDPC coding. The underwater acoustic channel is tracked using a Kalman filter which requires accurate data decisions. To improve KF performance and reduce the overall error rate, joint iterative LDPC decoding and channel estimation is proposed based on a factor graph and sum-product algorithm approximation. In this scheme, the decoder posterior log likelihood ratios (LLRs) provide data decisions for the KF. Decoder extrinsic LLRs are similarly incorporated into the detector LLRs to yield improved priors for decoding. Error rate simulations of the overall modem are provided for a shallow-water channel model with Ricean/Rayleigh fading.

[pt] Este trabalho tem como finalidade explorar uma técnica de redução do erro de estimativas da resposta de freqüência discreta do canal geradas por símbolos piloto em sistemas de transmissão OFDM (Orthogonal Frequency Division Multiplexing). Nesta técnica, uma transformação linear projeta o vetor que contem as estimativas obtidas inicialmente no subespaço em que a verdadeira resposta de freqüência do canal tem que estar, resultando em uma redução da variância do erro das estimativas. A aplicação conjunta desta técnica com filtragem adaptativa para a estimação da resposta de freqüência do canal também está no contexto desta dissertação. Os resultados dos experimentos são analisados em termos da taxa de erro de bit média obtida e da convergência dos algoritmos adaptaivos empregados nas etapas de estimação de canal no receptor. / [en] This work a technique for error reduction in estimates of the discrete channel frequency response obtained with aid of pilot symbols in OFDM (Orthogonal Frequency Division Multiplexing) transmission systems. In this technique projects the vector that contains the initial discrete channel frequency response estimate is projected into the subspace where the true channel frequency response has to lye, yielding a new channel estimate with a reduced error variance. The joint application of this technique with adaptive filtering for channel estimation is also developed herein. The performance of the proposed methods is analyzed in terms of the mean bit error rate achieved and of the convergence of the adaptive channel estimation algorithms used in the receiver.

"Fading is one of the most fundamental impairments to wireless communications. The standard approach to combating fading is by adding redundancy - or diversity - to help increase coverage and transmission speed. Motivated by the results in multiple-input multiple-output technologies, which are usually used at base stations or access points, cooperation commutation has been proposed to improve the performance of wireless networks which consist of low-cost single antenna devices. While the majority of the research in cooperative communication focuses on flat fading for its simplicity and easy analysis, in practice the underlying channels in broadband wireless communication systems such as cellular systems (UMTS/LTE) are more likely to exhibit frequency selective fading. In this dissertation, we consider a frequency selective fading channel model and explore distributed diversity techniques in broadband wireless relay networks, with consideration to practical issues such as channel estimation and complexity-performance tradeoffs. We first study a system model with one source, one destination and multiple decode-and-forward (DF) relays which share a single channel orthogonal to the source. We derive the diversity-multiplexing tradeoff (DMT) for several relaying strategies: best relay selection, random relay selection, and the case when all decoding relays participate. The best relay selection method selects the relay in the decoding set with the largest sum-squared relay-to-destination channel coefficients. This scheme can achieve the optimal DMT of the system at the expense of higher complexity, compared to the other two relaying strategies which do not always exploit the spatial diversity offered by the relays. Different from flat fading, we find special cases when the three relaying strategies have the same DMT. We further present a transceiver design and prove it can achieve the optimal DMT asymptotically. Monte Carlo simulations are presented to corroborate the theoretical analysis. We provide a detailed performance comparison of the three relaying strategies in channels encountered in practice. The work has been extended to systems with multiple amplify-and-forward relays. We propose two relay selection schemes with maximum likelihood sequential estimator and linear zero- forcing equalization at the destination respectively and both schemes can asymptotically achieve the optimal DMT. We next extend the results in the two-hop network, as previously studied, to multi-hop networks. In particular, we consider the routing problem in clustered multi-hop DF relay networks since clustered multi-hop wireless networks have attracted significant attention for their robustness to fading, hierarchical structure, and ability to exploit the broadcast nature of the wireless channel. We propose an opportunistic routing (or relay selection) algorithm for such networks. In contrast to the majority of existing approaches to routing in clustered networks, our algorithm only requires channel state information in the final hop, which is shown to be essential for reaping the diversity offered by the channel. In addition to exploiting the available diversity, our simple cross-layer algorithm has the flexibility to satisfy an additional routing objective such as maximization of network lifetime. We demonstrate through analysis and simulation that our proposed routing algorithm attains full diversity under certain conditions on the cluster sizes, and its diversity is equal to the diversity of more complicated approaches that require full channel state information. The final part of this dissertation considers channel estimation in relay networks. Channel state information is vital for exploiting diversity in cooperative networks. The existing literature on cooperative channel estimation assumes that block lengths are long and that channel estimation takes place within a fading block. However, if the forwarding delay needs to be reduced, short block lengths are preferred, and adaptive estimation through multiple blocks is required. In particular, we consider estimating the relay-to-destination channel in DF relay systems for which the presence of forwarded information is probabilistic since it is unknown whether the relay participates in the forwarding phase. A detector is used so that the update of the least mean square channel estimate is made only when the detector decides the presence of training data. We use the generalized likelihood ratio test and focus on the detector threshold for deciding whether the training sequence is present. We also propose a heuristic objective function which leads to a proper threshold to improve the convergence speed and reduce the estimation error. Extensive numerical results show the superior performance of using this threshold as opposed to fixed thresholds."

This thesis investigates reliable data communication techniques for wireless channels. The problem of data detection at the receiver is considered and several novel detectors and parameter estimators are presented.¶ It is shown that by using a noise-limiting prefilter, with a spectral support at least equal to the signal part of the received signal, and sampling its output at the Nyquist rate, a set of sufficient statistics for maximum likelihood sequence detection (MLSD) is obtained.¶ Observing that the time-variations of the multipaths in a wireless channel are bandlimited, channel taps are closely approximated as polynomials in time. Using this representation, detection techniques for frequency-flat and frequency-selective channels are obtained. The proposed polynomial predictor based sequence detector (PPSD) for frequency-flat channels is similar in structure to the MLSD that employs channel prediction. However, the PPSD uses {\em a priori} known polynomial based predictor taps. It is observed that the PPSD, without any explicit knowledge of the channel autocovariance, performs close to the Innovations based MLSD.¶ New techniques for frequency-selective channel estimation are presented. They are based on a rectangular windowed least squares algorithm, and they employ a polynomial model of the channel taps. A recursive form of the least squares algorithm with orthonormal polynomial basis vectors is developed. Given the appropriate window size and polynomial model order, the proposed method outperforms the conventional least mean squares (LMS) and the exponentially weighted recursive least squares (EW-RLS) algorithms. Novel algorithms are proposed to obtain near optimal window size and polynomial model order.¶ The improved channel estimation techniques developed for frequency-selective channels are incorporated into sliding window and fixed block channel estimators. The sliding window estimator uses received samples over a time window to calculate the channel taps. Every symbol period, the window is moved along another symbol period and a new estimate is calculated. A fixed block estimator uses all received samples to estimate the channel taps throughout a data packet, all at once. In fast fading and at a high signal-to-noise ratio (SNR), both techniques outperform the MLSD receivers which employ the LMS algorithm for channel estimation.¶ An adaptive multiuser detector, optimal in the weighted least squares (WLS) sense, is derived for direct sequence code division multiple access (DS-CDMA) systems. In a multicellular configuration, this detector jointly detects the users within the cell of interest, while suppressing the intercell interferers in a WLS sense. In the absence of intercell interferers, the detector reduces to the well-known multiuser MLSD structure that employs a bank of matched filters. The relationship between the proposed detector and a centralized decision feedback detector is derived. The effects of narrowband interference are investigated and compared with the multiuser MLSD.¶ Since in a fast time-varying channel, the LMS or the EW-RLS algorithms cannot track the channel variations effectively, the receiver structures proposed for single user communications are extended to multiuser DS-CDMA systems. The fractionally-chip-spaced channel taps of the convolution of the chip waveform with the multipath channel are estimated. Linear equalizer, decision feedback equalizer and MLSDs are studied, and under fast fading, as the SNR increases, they are found to outperform the LMS based adaptive minimum mean squared error (MMSE) linear receivers.

<p>This thesis work carries out a study of IEEE 802.16 standards and mainly concentrates on the 802.16a OFDM PHY layer. A Simulink model based on 802.16a OFDM PHY baseband is built for simulation and performance evaluation. All mandatory blocks in the 802.16a OFDM-PHY specification are included: Randomization, FEC,adaptive modulation, and IFFT/FFT. A multipath Rayleigh fading channel is implemented and frequency domain channel estimation is selected for this model. Perfect synchronization is assumed.</p>

In wireless communication systems, transmitted signals are corrupted by fading as well as noise. The receiver can benefit from the estimates of fading channels to detect the transmitted symbols. However, in practical wireless systems channel information cannot be estimated perfectly at the receiver. Therefore, it is crucial to examine the effect of channel estimation error on the structure and performance of the receivers. In the first part of the thesis, we study single-user systems with single-antenna reception over fading channels in the presence of Gaussian-distributed channel estimation error. By using the statistical information of the channel estimation error, we will derive the structure of maximum-likelihood receivers for a number of different modulation formats and then analyze their performance over fading channels. In the second part of the thesis, we consider the uplink of multi-user wireless systems with multi-antenna reception. For conventional diversity combining techniques such as maximal ratio combining and optimum combining we analyze the performance degradation due to imperfect channel estimates in the presence of multiple interfering users for several fading channels. By investigating the probability density function of the output signal-to-interference ratio, we will derive analytical expressions for several performance measures such as the average signal-to-interference ratio, outage probability and average bit-error probability. These expressions quantify performance degradation due to channel estimation error.

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.

In wireless communication systems, transmitted signals are corrupted by fading as well as noise. The receiver can benefit from the estimates of fading channels to detect the transmitted symbols. However, in practical wireless systems channel information cannot be estimated perfectly at the receiver. Therefore, it is crucial to examine the effect of channel estimation error on the structure and performance of the receivers. In the first part of the thesis, we study single-user systems with single-antenna reception over fading channels in the presence of Gaussian-distributed channel estimation error. By using the statistical information of the channel estimation error, we will derive the structure of maximum-likelihood receivers for a number of different modulation formats and then analyze their performance over fading channels. In the second part of the thesis, we consider the uplink of multi-user wireless systems with multi-antenna reception. For conventional diversity combining techniques such as maximal ratio combining and optimum combining we analyze the performance degradation due to imperfect channel estimates in the presence of multiple interfering users for several fading channels. By investigating the probability density function of the output signal-to-interference ratio, we will derive analytical expressions for several performance measures such as the average signal-to-interference ratio, outage probability and average bit-error probability. These expressions quantify performance degradation due to channel estimation error.