It has been shown in the literature that the oil and gas industry deals with a substantial number of biases that impact project evaluation and portfolio performance. Previous studies concluded that properly estimating uncertainties will significantly impact the success of risk takers and their profits. Although a considerable number of publications investigated the impact of cognitive biases, few of these publications tackled the problem from a quantitative point of view. The objective of this work is to demonstrate the value of quantifying uncertainty and evaluate its impact on the optimization of oil and gas portfolios, taking into consideration the risk of each project. A model has been developed to perform portfolio optimization using Markowitz theory. In this study, portfolio optimization has been performed in the presence of different levels of overconfidence and directional bias to determine the impact of these biases on portfolio performance. The results show that disappointment in performance occurs not only because the realized portfolio net present value (NPV) is lower than estimated, but also because the realized portfolio risk is higher than estimated. This disappointment is due to both incorrect estimation of value and risk (estimation error) and incorrect project selection (decision error). The results of the cases analyzed show that, in a high-risk-tolerance environment, moderate overconfidence and moderate optimism result in an expected decision error of about 19% and an expected disappointment of about 50% of the estimated portfolio. In a low-risk-tolerance environment, the same amounts of moderate overconfidence and optimism result in an expected decision error up to 103% and an expected disappointment up to 78% of the estimated portfolio. Reliably quantifying uncertainty has the value of reducing the expected disappointment and the expected decision error. This can be achieved by eliminating overconfidence in the process of project evaluation and portfolio optimization. Consequently, overall industry performance can be improved because accurate estimates enable identification of superior portfolios, with optimum reward and risk levels, and increase the probability of meeting expectations.

Empowered by linear precoding and decoding, a spatially multiplexed multiple-input multiple-output (MIMO) system becomes a convenient framework to offer high data rate, diversity and interference management. While most of the current precoding/decoding designs have assumed perfect channel state information (CSI) at the receiver, and sometimes even at the transmitter, in this thesis we design the precoder and decoder with imperfect CSI at both the transmit and the receive sides, and investigate the joint impact of channel estimation errors and channel correlation on system structure and performance. The mean-square error (MSE) related performance metrics are used as the design criteria. We begin with the minimum total MSE precoding/decoding design for a single-user MIMO system assuming imperfect CSI at both ends. Here the CSI includes the channel estimate and channel correlation information. The structures of the optimum precoder and decoder are determined. Compared to the perfect CSI case, linear filters are added to the transceiver structure to improve system robustness against imperfect CSI. The effects of channel estimation error and channel correlation are quantified by simulations. With imperfect CSI at both ends, the exact capacity expression for a single-user MIMO channel is difficult to obtain. Instead, a tight capacity lower-bound is used for system design. The optimum structure of the transmit covariance matrix for the lower-bound has not been found in the existing literature. By transforming the transmitter design into a joint precoding/decoding design problem, we derive the expression of the optimum transmit covariance matrix. The close relationship between the maximum mutual information design and the minimum total MSE design is also discovered assuming imperfect CSI. For robust multiuser MIMO communications, minimum average sum MSE transceiver (precoder-decoder pairs) design problems are formulated for both the uplink and the downlink, assuming imperfect channel estimation and channel correlation at the base station (BS). We propose improved iterative algorithms based on the associated Karush-Kuhn-Tucker (KKT) conditions. Under the assumption of imperfect CSI, an uplink--downlink duality in average sum MSE is proved. As an alternative for the uplink optimization, a sequential semidefinite programming (SDP) method is proposed. Simulation results are provided to corroborate the analysis. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-07-25 10:53:45.175

Rateless codes, also known as fountain codes, are a class of erasure error-control codes that are particularly well suited for broadcast/multicast systems. Raptor codes, as a particularly successful implementation of digital fountain codes, have been used as the application layer forward error correction (FEC) codes in the third generation partnership program (3GPP) Multimedia Broadcast and Multicast Services (MBMS) standard. However, the application of rateless codes to wireless multimedia broadcast/multicast communications has yet to overcome two major challenges: first, wireless multimedia communications usually has stringent delay requirements. In addition, multimedia multicast has to overcome heterogeneity. To meet these challenges, we propose a rateless code design that takes the layered nature of source traffic as well as the varying quality of transmission channels into account. A convex optimization framework for the application of unequal error protection (UEP) rateless codes to synchronous and asynchronous multimedia multicast to heterogeneous users is proposed. A second thread of the thesis addresses the noisy, bursty and time- varying nature of wireless communication channels that challenge the assumption of erasure channels often used for the wired internet. In order to meet this challenge, the optimal combination of application-layer rateless code and physical layer FEC code rates in time-varying fading channels is investigated. The performance of rateless codes in hybrid error-erasure channels with memory is then studied, and a cross-layer decoding method is proposed to improve decoding performance and complexity. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2011-06-12 16:26:36.136

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