4-D Tomographic Inference: Application to SPECT and MR-driven PET

Emission tomographic imaging is framed in the Bayesian and information theoretic framework. The first part of the thesis is inspired by the new possibilities offered by PET-MR systems, formulating models and algorithms for 4-D tomography and for the integration of information from multiple imaging modalities. The second part of the thesis extends the models described in the first part, focusing on the imaging hardware. Three key aspects for the design of new imaging systems are investigated: criteria and efficient algorithms for the optimisation and real-time adaptation of the parameters of the imaging hardware; learning the characteristics of the imaging hardware; exploiting the rich information provided by depthof- interaction (DOI) and energy resolving devices. The document concludes with the description of the NiftyRec software toolkit, developed to enable 4-D multi-modal tomographic inference

Interference Mitigation in Wireless Communications

The primary objective of this thesis is to design advanced interference resilient schemes for asynchronous slow frequency hopping wireless personal area networks (FH-WPAN) and time division multiple access (TDMA) cellular systems in interference dominant environments. We also propose an interference-resilient power allocation method for multiple-input-multiple-output (MIMO) systems. For asynchronous FH-WPANs in the presence of frequent packet collisions, we propose a single antenna interference canceling dual decision feedback (IC-DDF) receiver based on joint maximum likelihood (ML) detection and recursive least squares (RLS) channel estimation. For the system level performance evaluation, we propose a novel geometric method that combines bit error rate (BER) and the spatial distribution of the traffic load of CCI for the computation of packet error rate (PER). We also derived the probabilities of packet collision in multiple asynchronous FH-WPANs with uniform and nonuniform traffic patterns. For the design of TDMA receivers resilient to CCI in frequency selective channels, we propose a soft output joint detection interference rejection combining delayed decision feedback sequence estimation (JD IRC-DDFSE) scheme. In the proposed scheme, IRC suppresses the CCI, while DDFSE equalizes ISI with reduced complexity. Also, the soft outputs are generated from IRC-DDFSE decision metric to improve the performance of iterative or non-iterative type soft-input outer code decoders. For the design of interference resilient power allocation scheme in MIMO systems, we investigate an adaptive power allocation method using subset antenna transmission (SAT) techniques. Motivated by the observation of capacity imbalance among the multiple parallel sub-channels, the SAT method achieves high spectral efficiency by allocating power on a selected transmit antenna subset. For 4 x 4 V-BLAST MIMO systems, the proposed scheme with SAT showed analogous results. Adaptive modulation schemes combined with the proposed method increase the capacity gains. From a feasibility viewpoint, the proposed method is a practical solution to CCI-limited MIMO systems since it does not require the channel state information (CSI) of CCI.Ph.D.Committee Chair: Professor Gordon L. StBe

Combined turbo coding and interference rejection for DS-CDMA.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2004.This dissertation presents interference cancellation techniques for both the Forward Error Correction (FEC) coded and the uncoded Direct Sequence Code Division Multiple Access (DS-CDMA) systems. Analytical models are also developed for the adaptive and the non-adaptive Parallel Interference Cancellation (PlC) receivers. Results that are obtained from the computer simulations of the PlC receiver types confirm the accuracy of the analytical models that are developed. Results show that the Least Mean Square (LMS) algorithm based adaptive PlC receivers have bit error rate performances that are better than those of the non-adaptive PlC receivers. In the second part of this dissertation, a novel iterative multiuser detector for the Turbo coded DS-CDMA system is developed. The performance of the proposed receiver in the multirate CDMA system is also investigated. The developed receiver is found to have an error rate performance that is very close to the single user limit after a few numbers of iterations. The receiver is also resilient against the near-far effect. A methodology is also presented on the use of the Gaussian approximation method in the convergence analysis of iterative interference cancellation receivers for turbo coded DS-CDMA systems

Achievable rates of iterative MIMO receivers over interference channels

In this thesis, we study the achievable rates of some interference communication schemes when iterative interference-cancellation (IC) is applied. We assume multiple-input multiple-output (MIMO) communication employing iterative receivers with linear front-ends which involves two modules concatenated serially and cooperating iteratively; a linear combiner based on minimum-mean-square-error (MMSE) detection or maximal-ratio-combining (MRC) and a SISO decoder. We investigate the achievable rates of this receiver when the transmitted signal is Gaussian-distributed with hypothetical erasure-type feedback from the decoder to the combiner and a more practical case with large-size QAM constellations with log-likelihood-ratios (LLRs) being exchanged between the receiver's modules. The achievable rate is approximated by the area below the EXIT curve of the linear FE receiver. Some properties have been observed and mathematically been proved about the iterative MIMO receivers with linear front-end

Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

Distributed detection, localization, and estimation in time-critical wireless sensor networks

In this thesis the problem of distributed detection, localization, and estimation (DDLE) of a stationary target in a fusion center (FC) based wireless sensor network (WSN) is considered. The communication process is subject to time-critical operation, restricted power and bandwidth (BW) resources operating over a shared communication channel Buffering from Rayleigh fading and phase noise. A novel algorithm is proposed to solve the DDLE problem consisting of two dependent stages: distributed detection and distributed estimation. The WSN performs distributed detection first and based on the global detection decision the distributed estimation stage is performed. The communication between the SNs and the FC occurs over a shared channel via a slotted Aloha MAC protocol to conserve BW. In distributed detection, hard decision fusion is adopted, using the counting rule (CR), and sensor censoring in order to save power and BW. The effect of Rayleigh fading on distributed detection is also considered and accounted for by using distributed diversity combining techniques where the diversity combining is among the sensor nodes (SNs) in lieu of having the processing done at the FC. Two distributed techniques are proposed: the distributed maximum ratio combining (dMRC) and the distributed Equal Gain Combining (dEGC). Both techniques show superior detection performance when compared to conventional diversity combining procedures that take place at the FC. In distributed estimation, the segmented distributed localization and estimation (SDLE) framework is proposed. The SDLE enables efficient power and BW processing. The SOLE hinges on the idea of introducing intermediate parameters that are estimated locally by the SNs and transmitted to the FC instead of the actual measurements. This concept decouples the main problem into a simpler set of local estimation problems solved at the SNs and a global estimation problem solved at the FC. Two algorithms are proposed for solving the local problem: a nonlinear least squares (NLS) algorithm using the variable projection (VP) method and a simpler gird search (GS) method. Also, Four algorithms are proposed to solve the global problem: NLS, GS, hyperspherical intersection method (HSI), and robust hyperspherical intersection (RHSI) method. Thus, the SDLE can be solved through local and global algorithm combinations. Five combinations are tied: NLS2 (NLS-NLS), NLS-HSI, NLS-RHSI, GS2, and GS-N LS. It turns out that the last algorithm combination delivers the best localization and estimation performance. In fact , the target can be localized with less than one meter error. The SNs send their local estimates to the FC over a shared channel using the slotted-Aloha MAC protocol, which suits WSNs since it requires only one channel. However, Aloha is known for its relatively high medium access or contention delay given the medium access probability is poorly chosen. This fact significantly hinders the time-critical operation of the system. Hence, multi-packet reception (MPR) is used with slotted Aloha protocol, in which several channels are used for contention. The contention delay is analyzed for slotted Aloha with and without MPR. More specifically, the mean and variance have been analytically computed and the contention delay distribution is approximated. Having theoretical expressions for the contention delay statistics enables optimizing both the medium access probability and the number of MPR channels in order to strike a trade-off between delay performance and complexity

Shuttle Ku-band and S-band communications implementation study

Various aspects of the shuttle orbiter S-band network communication system, the S-band payload communication system, and the Ku-band communication system are considered. A method is proposed for obtaining more accurate S-band antenna patterns of the actual shuttle orbiter vehicle during flight because the preliminary antenna patterns using mock-ups are not realistic that they do not include the effects of additional appendages such as wings and tail structures. The Ku-band communication system is discussed especially the TDRS antenna pointing accuracy with respect to the orbiter and the modifications required and resulting performance characteristics of the convolutionally encoded high data rate return link to maintain bit synchronizer lock on the ground. The TDRS user constraints on data bit clock jitter and data asymmetry on unbalanced QPSK with noisy phase references are included. The S-band payload communication system study is outlined including the advantages and experimental results of a peak regulator design built and evaluated by Axiomatrix for the bent-pipe link versus the existing RMS-type regulator. The nominal sweep rate for the deep-space transponder of 250 Hz/s, and effects of phase noise on the performance of a communication system are analyzed

The application of auditory signal processing principles to the detection, tracking and association of tonal components in sonar.

A steady signal exerts two complementary effects on a noisy acoustic environment: one is to add energy, the other is to create order. The ear has evolved mechanisms to detect both effects and encodes the fine temporal detail of a stimulus in sequences of auditory nerve discharges. Taking inspiration from these ideas, this thesis investigates the use of regular timing for sonar signal detection. Algorithms that operate on the temporal structure of a received signal are developed for the detection of merchant vessels. These ideas are explored by reappraising three areas traditionally associated with power-based detection. First of all, a time-frequency display based on timing instead of power is developed. Rather than inquiring of the display, "How much energy has been measured at this frequency? ", one would ask, "How structured is the signal at this frequency? Is this consistent with a target? " The auditory-motivated zero crossings with peak amplitudes (ZCPA) algorithm forms the starting-point for this study. Next, matters related to quantitative system performance analysis are addressed, such as how often a system will fail to detect a signal in particular conditions, or how much energy is required to guarantee a certain probability of detection. A suite of optimal temporal receivers is designed and is subsequently evaluated using the same kinds of synthetic signal used to assess power-based systems: Gaussian processes and sinusoids. The final area of work considers how discrete components on a sonar signal display, such as tonals and transients, can be identified and organised according to auditory scene analysis principles. Two algorithms are presented and evaluated using synthetic signals: one is designed to track a tonal through transient events, and the other attempts to identify groups of comodulated tonals against a noise background. A demonstration of each algorithm is provided for recorded sonar signals