In present day wireless applications, especially for time-varying channels, we require flexible coding schemes that utilize a minimum of bandwidth and can support different code rates. In addition, we require coding schemes that are simple in terms of complexity but give good performance. Recently a special class of turbo-like codes called repeat accumulate (RA) codes were proposed. These codes are extremely simple in terms of complexity compared to turbo or LDPC codes and have been shown to have decoding thresholds close to the capacity of the AWGN channel. In this thesis, we propose rate-compatible punctured systematic RA codes for the additive white Gaussian noise (AWGN) channel. We first pro-pose a three phase puncturing scheme that provides rate compatibility and show that very high rate code rates can be obtained from a single mother code. We then provide a methodology to design rate-compatible RA codes based on our three phase puncturing scheme. The design involves optimizing the punctured profile of the code such that the resulting high rate codes give good performance. The design is done with the help of existrinsic in-formation transfer (EXIT) charts which are plots used to analyze the constituent decoders. Code rates up to 10/11 are obtained from a single rate 1/3 regular RA code. Performance results show that our design methodology combined with our proposed puncturing scheme can provide significant coding gains at high code rates even with practical blocklengths. Hence rate-compatible punctured RA codes are suitable for many wireless applications.

Bibliography: leaves 197-205. / xiv, 205 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / This thesis is concerned with methods for protecting speech coding parameters transmitted over noisy channels. A linear prediction (LP) coder is employed to remove the short term correlations of speech. Protection of two sets of parameters are investigated. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1995?

Thesis (Ph.D.)--University of Melbourne, Dept. of Electrical and Electronic Engineering, 2008. / Typescript. Includes bibliographical references (leaves 149-158).

Thesis (M. App. Sc.)--Carleton University, 2001. / Includes bibliographical references (p. 126-131). Also available in electronic format on the Internet.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Robertson, R. Clark. "September 2009." Description based on title screen as viewed on 6 November 2009. Author(s) subject terms: Link-16/JTIDS, (31, 15) Reed-Solomon (RS) coding, 32-ary Orthogonal signaling, Additive White Gaussian Noise (AWGN), Pulse-Noise Interference (PNI), Perfect Side Information (PSI). Includes bibliographical references (p. 49-51). Also available in print.

Thesis (M.S. in Electronic Warfare Systems Engineering)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Robertson, Ralph C. "September 2009." Description based on title screen as viewed on 5 November 2009. Author(s) subject terms: Link-16/JTIDS, Reed-Solomon (RS) coding, Cyclic Code-Shift Keying (CCSK), Minimum-Shift Keying (MSK), convolutional codes, concatenated codes, perfect side information (PSI), Pulsed-Noise Interference (PNI), Additive White Gaussian Noise (AWGN), coherent detection, noncoherent detection. Includes bibliographical references (p. 79). Also available in print.

Thesis (M.S.)--Oregon State University, 2011. / Printout. Includes bibliographical references (leaves 115-116). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

A large literature has documented a pattern of stochastic, or random, choice in individual decision making. In games, in which payoffs depend on beliefs over opponents’ behavior, another potentially important source of stochasticity is in the beliefs themselves. Hence, there may be both “noisy actions” and “noisy beliefs”. This dissertation explores the equilibrium implications of both types of noise in normal form games. Theory is developed to understand the effects of noisy beliefs, and the model is compared to the canonical model of noisy actions. Predictions—and assumptions—are tested using existing and novel experimental data. Chapter 1 introduces noisy belief equilibrium (NBE) for normal form games, a model that injects “noisy beliefs” into an otherwise standard equilibrium framework. Axioms restrict the belief distributions to be unbiased with respect to and responsive to changes in the opponents’ behavior. We compare NBE to an axiomatic form of quantal response equilibrium (QRE) in which players have correct beliefs over their opponents’ behavior, but take “noisy actions”. We show that NBE generates similar predictions as QRE such as the “own-payoff effect”, and yet is more consistent with the empirically documented effects of changes in payoff magnitude. Unlike QRE, NBE is a refinement of rationalizability and invariant to affine transformations of payoffs. Chapter 2, joint with Jeremy Ward, studies an equilibrium model in which there is both “noisy actions” and “noisy beliefs”. The model primitives are an action-map, which determines a distribution of actions given beliefs, and a belief-map, which determines a distribution of beliefs given opponents’ behavior. These are restricted to satisfy the axioms of QRE and NBE, respectively, which are simply stochastic generalizations of “best response” and “correct beliefs”. In our laboratory experiment, we collect actions data and elicit beliefs for each game within a family of asymmetric 2-player games. These games have systematically varied payoffs, allowing us to “trace out” both the action- and belief-maps. We find that, while both sources of noise are important in explaining observed behaviors, there are systematic violations of the axioms. In particular, although all subjects observe and play the same games, subjects in different roles have qualitatively different belief biases. To explain this, we argue that the player role itself induces a higher degree of strategic sophistication in the player who faces more asymmetric payoffs. This is confirmed by structural estimates. Chapter 3 considers logit QRE (LQRE), the common parametric form of QRE; and we endogenize its precision parameter "lambda", which controls the degree of “noisy actions”. In the first stage of an endogenous quantal response equilibrium (EQRE), each player chooses her precision optimally subject to costs, taking as given other players’ (second-stage) behavior. In the second stage, the distribution of players’ actions is a heterogenous LQRE given the profile of first-stage precision choices. EQRE satisfies a modified version of the regularity axioms, nests LQRE as a limiting case for a sequence of cost functions, and admits analogues of classic results for LQRE such as those for equilibrium selection. We show how EQRE differs from LQRE using the family of generalized matching pennies games.

As a result of our heavy reliance on internet usage and running online transactions, authentication has become a routine part of our daily lives. So, what happens when we lose or cannot use our digital credentials? Can we securely recover our accounts? How do we ensure it is the genuine user that is attempting a recovery while at the same time not introducing too much friction for the user? In this dissertation, we present research results demonstrating that account recovery is a growing need for users as they increase their online activity and use different authentication factors. We highlight that the account recovery process is the weakest link in the authentication domain because it is vulnerable to account takeover attacks because of the less secure fallback authentication mechanisms usually used. To close this gap, we study user behavior-based machine learning (ML) modeling as a critical part of the account recovery process. The primary threat model for ML implementation in the context of authentication is poisoning and evasion attacks. Towards that end, we research randomized modeling techniques and present the most effective randomization strategy in the context of user behavioral biometrics modeling for account recovery authentication. We found that a randomization strategy that exclusively relied on the user’s data, such as stochastically varying the features used to generate an ensemble of models, outperformed a design that incorporated external data, such as adding gaussian noise to outputs. This dissertation asserts that account recovery process security posture can be vastly improved by incorporating user behavior modeling to add resiliency against account takeover attacks and nudging users towards voluntary adoption of more robust authentication factors.