¡@¡@In recent year, orthogonal frequency division multiplexing ¡]OFDM¡^ technology has been widely used in high-speed communication systems. One primary reason for the popularity of OFDM is its ability to provide good performance in multi-path channels than the other systems through the use of Guard interval(GI). By using the Guard interval, it can convert these inter-symbol interference (ISI) channels into ISI-free channels. But Guard interval without any information will caused inter-channel interference. In order to solve this problem, a guard interval using cyclic prefix (CP) is inserted to avoid inter-symbol interference from the adjacent symbols and inter-channel interference from other sub-channels. However, using long cyclic prefix will decrease the transmission rate, reduce the spectral efficiency, and increase the signal-to-noise power ratio¡]SNR¡^loss. If we choose a shorter one, the channel length may be longer than the cyclic prefix. The interference caused by insufficient cyclic prefix can seriously degrade the performance of OFDM systems. In order to solve this problem, a time domain equalizer¡]TEQ¡^is usually used in the receiver to shorten the channel length of OFDM transmission system, and therefore minimize the ISI and ICI. However, because of its high complexity, the optimum design of TEQ is hard to realize. ¡@¡@So we use an iterative channel estimation technique between time domain and frequency domain to mitigate the ISI and ICI which is caused by insufficient cyclic prefix. The iterative technique can remove ISI and hold the circular convolution property. By utilizing the iterative technique we can improve the channel estimation performance as the OFDM symbol used sufficient cyclic prefix. ¡@¡@In the computer simulations, we consider the worst case that the OFDM symbol is transmitted without guard interval. The results show that our proposed method can effectively suppress residual ISI. The comparison between our proposed method including both proposed channel estimation¡]PCE¡^and proposed data demodulation¡]PDD¡^, decision feedback channel estimation¡]DFCE¡^, avoid ISI preamble channel estimation¡]AISIP¡^, and residual ISI cancellation¡]RISIC¡^algorithm are made in this thesis. Finally, the performance improvement of the proposed algorithm under several channel conditions is considered and compared with other algorithms.

Traditionally in CDMA system, selective rake receiver is the popular method of detection. When used in DS-UWB system, the complex in door environment will increase the channel paths. As the channel paths increase, the more fingers which are part of Rake receiver will increase. It will be difficult for hardware implement when consider the operation of channel estimation and Rake receiver. And it is unfavorable for hardware design. In this thesis, we will use partial Rake receiver to replace selective Rake receiver. Channel estimation is implemented by template the receiver signals within 2 bit time window length. The performance is acceptable and the hardware complexity is reduced. When implement the channel estimation, we combine some blocks of acquisition and channel estimation for reducing hardware complexity.

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Single-carrier linear modulation techniques combined with frequency-domain equalization provide a viable alternative to multicarrier techniques for combating multipath fading in channels with large delay spread. Such modulations tolerate frequency offset and have well controlled peak to average power ratio. They have comparable complexity to orthogonal frequency division multiplexing (OFDM) systems, and are more robust to synchronization errors. If error correction coding is used, then information can be iteratively passed between the equalizer and the decoder to improve performance. This is referred to as turbo equalization. To date, several turbo equalization schemes have been proposed, but little work has been done to address the problem of channel estimation for the turbo equalization process. The work in this thesis considers frequency-domain turbo equalization with imperfect channel state information (CSI) at the receiver for different wireless channels. A receiver structure incorporating joint frequency-domain turbo equalization and time- domain channel estimation is developed. The novelty of this scheme lies in the combination of time-domain channel estimation and frequency-domain turbo equalization, and in its extension to high level modulation formats. The performance of the system is investigated by a combination of analysis and computer simulation. It is found that the system performs well over a range of dispersive channels.

This thesis looks at the problem of channel estimation and equalization in a multiple-input multiple-output (MIMO) dispersive fading environments. Two classes of MIMO receiver structure are proposed with integrated channel estimation and tracking. One is a symbol-by-symbol based receiver using a MIMO minimum mean square error (MMSE) decision feedback equalizer (DFE), and the other is a sequence-based receiver using a partitioned Viterbi algorithm (PVA) which approaches the performance of maximum likelihood sequence estimation (MLSE). A MIMO channel estimator capable of tracking the time and frequency selective channel impulse responses, known as the vector generalized recursive least squares (VGRLS) algorithm, is developed. It has comparable performance and a similar level of complexity as the optimum Kalman filter. However, it does not require any knowledge of the channel statistics to operate and as such it can be employed in a Rician fading channel readily. A reduced complexity form of the estimator, known as the vector generalized least mean squares (VGLMS) algorithm, is also developed. This is achieved by replacing the online recursive computation of the VGRLS algorithm's 'intermediate' Riccatti matrix with an offline pre-computed matrix. This reduces the complexity of the algorithm by an order of a magnitude, but at the expense of degraded performance. The estimators are integrated with the above-mentioned equalizers in a decision directed mode to form a receiver structure that can operate in continuously time-varying fading channels. Due to decision delays, the outputs from the equalizer are delayed and this then produces 'delayed' channel estimates. A simple polynomial-based channel prediction module is employed to provide up-to-date channel estimates required by the equalizers. However, simulation results show that the channel prediction module may be omitted for a very slowly fading channel where the channel responses do not vary much. In the case of the PVA- receiver, the zero-delay tentative decisions are used as feedback to the channel estimators with negligible loss.

Master of Engineering by Research / As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels.

Abstract Multiuser demodulation algorithms for centralized receivers of asynchronous direct-sequence (DS) spread-spectrum code-division multiple-access (CDMA) systems in frequency-selective fading channels are studied. Both DS-CDMA systems with short (one symbol interval) and long (several symbol intervals) spreading sequences are considered. Linear multiuser receivers process ideally the complete received data block. The approximation of ideal infinite memory-length (IIR) linear multiuser detectors by finite memory-length (FIR) detectors is studied. It is shown that the FIR detectors can be made near-far resistant under a given ratio between maximum and minimum received power of users by selecting an appropriate memory-length. Numerical examples demonstrate the fact that moderate memory-lengths of the FIR detectors are sufficient to achieve the performance of the ideal IIR detectors even under severe near-far conditions. Multiuser demodulation in relatively fast fading channels is analyzed. The optimal maximum likelihood sequence detection receiver and suboptimal receivers are considered. The parallel interference cancellation (PIC) receiver is demonstrated to achieve better performance in known channels than the decorrelating receiver, but it is observed to be more sensitive to channel coefficient estimation errors than the decorrelator. At high channel loads the PIC receiver suffers from bit error rate (BER) saturation, whereas the decorrelating receiver does not. Choice of channel estimation filters is shown to be crucial if low BER is required. Data-aided channel estimation is shown to be more robust than decision-directed channel estimation, which may suffer from BER saturation caused by hang-ups at high signal-to-noise ratios. Multiuser receivers for dynamic CDMA systems are studied. Algorithms for ideal linear detector computation are derived and their complexity is analyzed. The complexity of the linear detector computation is a cubic function of KL, where K and L are the number of users and multipath components, respectively. Iterative steepest descent, conjugate gradient, and preconditioned conjugate gradient algorithms are proposed to reduce the complexity. The computational requirements for one iteration are a quadratic function of KL. The iterative detectors are also shown to be applicable for parallel implementation. Simulation results demonstrate that a moderate number of iterations yields the performance of the corresponding ideal linear detectors. A quantitative analysis shows that the PIC receivers are significantly simpler to implement than the linear receivers and only moderately more complex than the conventional matched filter bank receiver.

<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.