The main objective of this dissertation is to present the structural design, performance evaluation, and complexity reduction of iterative joint channel estimation and data detection receivers. One of the main technical challenges in advanced wireless communications stems from the characteristics of a wireless channel, e.g., time selectivity of a channel, mobility of users, and multipath propagation. Channel estimation is essential for achieving reliable information transmission for practical wireless communication applications. Numerous channel estimation structures have been developed for different underlying channels using pilot-symbol assisted modulation (PSAM) approaches. However, since pilot symbols carry no data information, the time and the power spent on pilot symbols degrades the efficiency and the throughput of the system. Therefore, it is necessary to minimize the pilot insertion ratio without degrading the error performance. This motivates our research on iterative joint channel estimation and data detection receivers with full- and reduced- or low-complexity. In this thesis, we first propose an iterative channel estimator (ICE), based on a maximum a posteriori (MAP) algorithm, for single-carrier systems with PSAM structures. In contrast to existing MAP channel estimators, the proposed channel estimator has a lower computational complexity, which increases linearly with the modulation alphabet size. The computational complexity is reduced by exploiting a survivor in an efficient manner, while achieving comparable error performance to a full complexity receiver. For orthogonal frequency division multiplexing (OFDM) systems, we also propose novel signal constellations to facilitate channel estimation without pilot symbol transmission, and analyze the bit error rate for the proposed constellations. We also develop a suitable joint channel estimation and data detector with full- and low-complexity for the proposed constellations. This low-complexity ICE achieves an error performance comparable to the ICE with full-complexity. Finally, for vertical Bell Laboratories layered space-time OFDM systems, we propose an ICE based on a PSAM structure for time-varying multipath fading channels. By exploiting the statistical properties of a wireless channel, we also develop a method to suppress intercarrier interference due to the channel time selectivity, and propose a low-complexity ICE that exploits a priori information in an efficient manner.

Recently, there has been a growing interest in improving the performance of the wireless relay networks through the use of Physical Layer Network Coding (PLNC) techniques. The physical layer network coding technique allows two terminals to transmit simultaneously to a relay node and decode the modulo-2 sum of the transmitted bits at the relay. This technique considerably improves performance over Digital Network Coding technique. In this thesis, we will present an algorithm for joint decoding of the modulo-2 sum of bits transmitted from two unsynchronized transmitters at the relay. We shall also address the problems that arise when boundaries of the signals do not align with each other and when the channel parameters are slowly varying and are unknown to the receiver at the relay node. Our approach will first jointly estimate the timing o sets and fading gains of both signals using a known pilot sequence sent by both transmitters in the beginning of the packet and then perform Maximum Likelihood detection of data using a state-based Viterbi decoding scheme that takes into account the timing o sets between the interfering signals. We shall present an algorithm for simultaneously tracking the amplitude and phase of slowly varying wireless channel that will work in conjunction our Maximum Likelihood detection algorithm. Finally, we shall provide extension of our receiver to support antenna diversity. Our results show that the proposed detection algorithm works reasonably well, even with the assumption of timing misalignment. We also demonstrate that the performance of the algorithm is not degraded by amplitude and/or phase mismatch between the users. We further show that the performance of the channel tracking algorithm is close to the ideal case i.e. when the channel estimates are perfectly known. Finally, we demonstrate the performance boost provided by the receiver antenna diversity.

Timing recovery is the processing of synchronizing the sampler with the received analog signal. Sampling at the wrong times can have a devastating impact on performance. Conventional timing recovery techniques are based on a decision-directed phase-locked loop (PLL). They are adequate only when the operating signal-to-noise ratio (SNR) is sufficiently high, but recent advances in error-control coding have made it possible to communicate reliably at very low SNR, where conventional techniques fail. This thesis develops new techniques for timing recovery that are capable of working at low SNR. We propose a new timing recovery scheme based on per-survivor processing (PSP), which jointly performs timing recovery and equalization, by embedding a separate PLL into each survivor of a Viterbi algorithm. The proposed scheme is shown to perform better than conventional scheme, especially when the SNR is low and the timing error is large. An important advantage of this technique is its amenability to real-time implementation. We also propose a new iterative timing recovery scheme that exploits the presence of the error-control code; in doing so, it can perform even better than the PSP scheme described above, but at the expense of increased complexity and the requirement of batch processing. This scheme is realized by embedding the timing recovery process into a trellis-based soft-output equalizer using PSP. Then, this module iteratively exchanges soft information with the error-control decoder, as in conventional turbo equalization. The resulting system jointly performs the functions of timing recovery, equalization, and decoding. The proposed iterative timing recovery scheme is shown to perform better than previously reported iterative timing recovery schemes, especially when the timing error is severe. Finally, performance analysis of iterative timing recovery schemes is difficult because of their high complexity. We propose to use the extrinsic information transfer (EXIT) chart as a tool to predict and compare their performances, considering that the bit-error rate computation takes a significant amount of simulation time. Experimental results indicate that the system performance predicted by the EXIT chart coincides with that obtained by simulating data transmission over a complete iterative receiver, especially when the coded block length is large.

This thesis investigates the use of Maximum Likelihood Sequence Estimation (MLSE) in the presence of unknown channel parameters. MLSE is a fundamental problem that is closely related to many modern research areas like Space-Time Coding, Overloaded Array Processing and Multi-User Detection. Per-Survivor Processing (PSP) is a technique for approximating MLSE for unknown channels by embedding channel estimation into the structure of the Viterbi Algorithm (VA). In the case of successful acquisition, the convergence rate of PSP is comparable to that of the pilot-aided RLS algorithm. However, the performance of PSP degrades when certain sequences are transmitted. In this thesis, the blind acquisition characteristics of PSP are discussed. The problematic sequences for any joint ML data and channel estimator are discussed from an analytic perspective. Based on the theory of indistinguishable sequences, modifications to conventional PSP are suggested that improve its acquisition performance significantly. The effect of tree search and list-based algorithms on PSP is also discussed. Proposed improvement techniques are compared for different channels. For higher order channels, complexity issues dominate the choice of algorithms, so PSP with state reduction techniques is considered. Typical misacquisition conditions, transients, and initialization issues are reported. / Master of Science