Multicarrier modulation is a transmission technique that is quite convenient for high data rates in wireless communication. Information symbols are partitioned and parallelly sent over multiple narrowband subchannels. Pulse shaping filters are critically important in multicarrier modulation for determining the characteristics of signal in time and frequency domains. In this thesis, we propose a new pulse shaping approach for multicarrier schemes to increase spectral efficiency in multi-user scenarios. Conventionally, the time-frequency lattice and the prototype filter are designed considering the worst-case of time-varying multipath channel. However, this approach ignores to make use of multi-user diversity and leads to excessive spacings between successive symbols in time and frequency. Unlike the prevalent methods, we investigate user-based filter utilization considering the wireless channel of each user individually to prevent over-design and improve spectral efficiency. Also, this approach is implemented in a denser time-frequency lattice design. Symbols are allowed to be overlapped (depending on time-frequency dispersion of their individual channels) as long as the signal-to-interference ratios (SIRs) observed by all users are kept above a certain level. Employing user-specific filters to enhance SIR of the user exposed to the most interference provides more overlapping flexibility. Therefore, further improvement in spectral efficiency is achieved in our wireless communication system design.

A central feature of wireless networks is multiple users sharing a common medium. Cellular systems are among the most common examples of such networks. The main phenomenon resulting from this inter-user interaction is interference, and thus analyzing interference networks is critical to determine the capacity of wireless networks. The capacity region of an interference network is defined as the set of rates that the users can simultaneously achieve while ensuring arbitrarily small probability of decoding error. It is an inherently hard problem to find the capacity region of interference networks. Even the capacity region of a general 2-user interference channel is a prominent open problem in information theory. This work's goal is to derive achievable regions that are improved over known results, and when possible, capacity theorems, for K user interference networks. Another multiuser channel that is commonly found in wireless systems is a broadcast channel. Broadcast channels stand side by side with Interference channels as the two of the most important channels for which capacity results are still not completely known. In this work we develop inner and outer bounds on the capacity region of fading broadcast channels, using which we find a part of the capacity region under some conditions. In summary, this work first presents coding arguments for new achievable rate regions and, where possible, capacity results for K-user interference networks. Second, it provides inner and outer-bounds for a class of fading broadcast channels. / text

The fundamentally fluctuating nature of the strength of a wireless link poses a significant challenge when seeking to achieve reliable communication at high data rates. Common sense, supported by information theory, tells us that one can move closer towards achieving higher data rates if the transmitter is provided with a priori knowledge of the channel. Such channel knowledge is typically provided to the transmitter by a feedback channel that is present between the receiver and the transmitter. The quality of information provided to the transmitter is proportional to the bandwidth of this feedback channel. Thus, the design of feedback channels is a key aspect in enabling high data rates. In the past, these feedback channels have been designed locally, on a link-by-link basis. While such an approach can be globally optimal in some cases, in many other cases, this is not true. In this thesis, we identify various settings in wireless networks, some already a part of existing standards, others under discussion in future standards, where the design of feedback channels is a problem that requires global, network-wide optimization. In general, we propose the treatment of feedback bandwidth as a network-wide resource, as the next step en route to achieving Gigabit wireless. Not surprisingly, such a global optimization initiative naturally leads us to the important issue of computational efficiency. Computational efficiency is critical from the point-of-view of a network provider. A variety of optimization techniques are employed in this thesis to solve the large combinatorial problems that arise in the context of feedback allocation. These include dynamic programming, sub-modular function maximization, convex relaxations and compressed sensing. A naive algorithm to solve these large combinatorial problems would typically involve searching over a exponential number of possibilities to find the optimal feedback allocation. As a general theme, we identify and exploit special application-specific structure to solve these problems optimally with reduced complexity. Continuing this endeavour, we search for more intricate structure that enables us to propose approximate solutions with significantly-reduced complexity. The accompanying analysis of these algorithms studies the inherent trade-offs between accuracy, efficiency and the required structure of the problem. / text

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The efficient and reliable communication of data from multiple sources to a single receiver plays an important role in emerging applications such as wireless sensor networks. The correlation among observations picked-up by spatially distributed sensors in such a network can be exploited to enhance the efficiency and reliability of communication. In particular, information theory shows that optimal communication of information from correlated sources requires distributed joint source-channel (DJSC) coding. This dissertation develops new approaches to designing DJSC codes based on low density parity check (LDPC) codes. The existence of low complexity code optimization algorithms and decoding algorithms make these codes ideal for joint optimization and decoding of multiple codes operating on correlated sources. The well known EXIT analysis-based LDPC code optimization method for channel coding in single-user point-to-point systems is extended to the optimization of two-user LDPC codes for DJSC coding in multi-access channels (MACs) with correlated users. Considering an orthogonal MAC with two correlated binary sources, an asymptotically optimal DJSC code construction capable of achieving any rate-pair in the theoretically-achievable two-user rate-region is presented. A practical approach to realizing this scheme using irregular LDPC codes is then developed. Experimental results are presented which demonstrate that the proposed codes can approach theoretical bounds when the codeword length is increased. For short codeword length and high inter-source correlation, these DJSC codes are shown to significantly outperform separate source and channel codes. Next, the DJSC code design for the transmission of a pair of correlated binary sources over a Gaussian MAC (GMAC) is investigated. The separate source and channel coding is known to be sub-optimal in this case. For the optimization of a pair of irregular LDPC codes, the EXIT analysis for message passing in a joint factor-graph decoder is analyzed, and an approach to modeling the probability density functions of messages associated with graph nodes which represent the inter-source dependence is proposed. Simulation results show that, for sufficiently large codeword lengths and high inter-source correlation, the proposed DJSC codes for GMAC can achieve rates higher than the theoretical upper bound for separate source and channel coding.

In "Technology and Literacy: A Story about the Perils of Not Paying Attention," Cynthia Selfe charges the field of composition not to simply consider technology a tool, but to "pay attention" to the rhetorical and social implications of those tools. In one sense, paying critical attention to technological literacies echoes the decade-old call for Computers and Writing practitioners to use research as a means of assessing online activities, suggesting that teachers not remain satisfied with the unreflective excitement that has been the operative epistemology of the field from its beginning. In another sense, Selfe's recent call enlists teachers and students in reflective and evaluative class discussion and writing on the technological literacy tools they are learning to use.This dissertation responds to both of these implications as it studies a semester of first-year college composition students within a synchronous online classroom environment. The question that guides my study is, in its most basic form, what happens during synchronous online writing conferences? And to speak to that question, I design an ethnographic context-sensitive text analysis employing grounded theory for data coding, a methodological model adaptable for future research in synchronous online classroom activity. I focus on three issues that have continually arisen in the scholarship surrounding synchronous conferencing: aspects of online language, the implications of the environment within object-oriented MUDs (MOOs), and the use of social constructionism as a theoretical foundation for synchronous conferencing.With the findings from my study, I conclude the dissertation by offering pedagogical suggestions to teachers and students for critically assessing synchronous online discourse. My articulation of assessment mandates that students and teachers engage in it together, collaboratively reflecting on what happens online and learning about synchronous online discourse-a significant ingredient in contemporary literacy. / Department of English

The efficient and reliable communication of data from multiple sources to a single receiver plays an important role in emerging applications such as wireless sensor networks. The correlation among observations picked-up by spatially distributed sensors in such a network can be exploited to enhance the efficiency and reliability of communication. In particular, information theory shows that optimal communication of information from correlated sources requires distributed joint source-channel (DJSC) coding. This dissertation develops new approaches to designing DJSC codes based on low density parity check (LDPC) codes. The existence of low complexity code optimization algorithms and decoding algorithms make these codes ideal for joint optimization and decoding of multiple codes operating on correlated sources. The well known EXIT analysis-based LDPC code optimization method for channel coding in single-user point-to-point systems is extended to the optimization of two-user LDPC codes for DJSC coding in multi-access channels (MACs) with correlated users. Considering an orthogonal MAC with two correlated binary sources, an asymptotically optimal DJSC code construction capable of achieving any rate-pair in the theoretically-achievable two-user rate-region is presented. A practical approach to realizing this scheme using irregular LDPC codes is then developed. Experimental results are presented which demonstrate that the proposed codes can approach theoretical bounds when the codeword length is increased. For short codeword length and high inter-source correlation, these DJSC codes are shown to significantly outperform separate source and channel codes. Next, the DJSC code design for the transmission of a pair of correlated binary sources over a Gaussian MAC (GMAC) is investigated. The separate source and channel coding is known to be sub-optimal in this case. For the optimization of a pair of irregular LDPC codes, the EXIT analysis for message passing in a joint factor-graph decoder is analyzed, and an approach to modeling the probability density functions of messages associated with graph nodes which represent the inter-source dependence is proposed. Simulation results show that, for sufficiently large codeword lengths and high inter-source correlation, the proposed DJSC codes for GMAC can achieve rates higher than the theoretical upper bound for separate source and channel coding.

The idea of utilizing multiple antennas (MIMO) has emerged as one of the significant breakthroughs in modern wireless communications. MIMO techniques can improve the spectral efficiency of wireless systems and provide significant throughput gains. As such, MIMO will be increasingly deployed in future wireless systems. On the other hand, in order to meet the increasing demand for high data rate multimedia wireless services, future wireless systems are evolving towards universal frequency reuse, where neighboring cells may utilize the same radio spectrum. As such, the performance of future wireless systems will be mainly limited by inter-cell interference (ICI). It has been shown that the throughput gains promised by conventional MIMO techniques degrade severely in multi-cell systems. This definitely attributes to the existence of the ICI. A lot of related work has been performed on the ICI mitigation or cancellation strategies, in multi-cell MIMO systems. Most of them assume that the channel and even data information is available at the collaborating base stations (BSs). Different from the previous work, we are looking into certain low-complexity codebook-based multi-cell multi-user MIMO strategies. For most of our work, we derive the statistics of the selected user's signal-to-interference-and-noise-ratio (SINR), which enable us to calculate the achieved sum-rate accurately and e ciently. With the derived sum-rate expressions, we evaluate and compare the sum-rate performance for several proposed low-complexity ICI-mitigation systems with various system parameters for single-user per-cell scheduling case. Furthermore, in order to fully exploit spatial multiplexing gain, we are considering multi-user per-cell scheduling case. Based on the assumption that all CSI including intra-cell and inter-cell channels are available at each BS, we rstly look into the centralized optimization approach. Typically, since the sum-rate maximization problem is mostly non-convex, it is generally di cult to obtain the globally optimum solution. Through certain approximation and relaxations, we successfully investigate an iterative optimization algorithm which exploits the second-order cone programming (SOCP) approach. From the simulation results, we will observe that the iterative option can provide near-optimum sum capacity, although only locally optimized. Afterwards, inspired by the successful application of Per-User Unitary Rate Control (PU2RC) scheme, we manage to extend it into dual-cell environment, with limited coordination between two cells. / Graduate

Thesis (Ph.D.)--University of Melbourne, Dept. of Psychology, 2004. / Typescript (photocopy). Includes bibliographical references (leaves 363-386).

Thesis (M. Ed.)--University of Canterbury, 2007. / Thesis (Typsecript photocopy). Includes bibliographical references (leaves 100-106). Also available via the World Wide Web.