Thesis (M.Eng.)--Memorial University of Newfoundland, 2005. / Restricted until October 2006. Bibliography: leaves 118-121.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 175-177).

The objective of the dissertation research is to understand the complex interaction between the algorithm and hardware aspects of symbol detection that is enhanced by lattice reduction (LR) preprocessing for wireless MIMO communication systems. The motivation for this work stems from the need to improve the bit-error-rate performance of conventional, low-complexity detectors while simultaneously exhibiting considerably reduced complexity when compared to the optimal method, maximum likelihood detection. Specifically, we first develop an understanding of the complex Lenstra-Lenstra-Lovász (CLLL) LR algorithm from a hardware perspective. This understanding leads to both algorithm modifications that reduce the required complexity and hardware architectures that are specifically optimized for the CLLL algorithm. Finally, we integrate this knowledge with an understanding of LR-aided MIMO symbol detection in a highly-correlated wireless environment, resulting in a joint LR/symbol detection algorithm that maps seamlessly to hardware. Hence, this dissertation forms the foundation for the adoption of lattice reduction algorithms in practical, high-throughput wireless MIMO communications systems.

Enabling multi-hop wireless mesh networks with multi-input multi-output (MIMO) functionality boosts network throughput by transmitting over multiple orthogonal spatial channels (spatial multiplexing) and by performing interference cancellation, to allow links within interference range to be concurrently active. Furthermore, if the channel is in a deep fade, then multiple antenna elements at the transmitter and/or receiver can be used to transmit a single stream, thereby improving signal quality (diversity gain). However, there is a fundamental trade-off between boosting individual link performance and reducing interference, which must be modeled in the process of optimizing network throughput. This is called the diversity-multiplexing-interference suppression trade-off. Optimizing network throughput therefore, requires optimizing the trade-off between the amounts of diversity employed on each link, the number of streams multiplexed on each link and the number of interfering links allowed to be simultaneously active in the network. We present a set of efficient heuristics for one-shot link scheduling and stream allocation that approximately solve the problem of optimizing network throughput in a single time slot. We identify the fundamental problem of verifying the feasibility of a given stream allocation. The problems of general link scheduling and stream allocation are very closely related to the problem of verifying feasibility. We present a set of efficient heuristic feasibility tests which can be easily incorporated into practical scheduling schemes. We show for some special MIMO network scenarios that feasibility is of polynomial complexity. However, we conjecture that in general, this problem, which is a variation of Boolean Satisablility, is NP-Complete.

Signal detection plays a critical role in realizing reliable transmission through communication systems. In this dissertation, by applying information theoretic approach, efficient detection schemes and algorithms are designed for three particular communication systems. First, a computation efficient coding and detection algorithm is developed to decode two dimensional inter-symbol interference (ISI) channels. The detection algorithm significantly reduces the computation complexity and makes the proposed equalization algorithm applicable. A new metric, the post-detection mutual information (PMI), is established to quantify the ultimate information rate between the discrete inputs and the hard detected output. This is the first time that the information rate loss caused by the hard mapping of the detectors is considered. Since the hard mapping step in the detector is irreversible, we expect that the PMI is reduced compared to the MI without hard mapping. The conclusion is confirmed by both the simulation and the theoretic results. Random complex field code is designed to achieve the secrecy capacity of wiretap channel with noiseless main channel and binary erasure eavesdroppers' channel. More importantly, in addition to approaching the secrecy capacity, RCFC is the first code design which provides a platform to tradeoff secrecy performance with the erasure rate of the eavesdropper's channel and the secrecy rate.

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 145-154).

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 73).

Thesis (Ph. D.)--University of California, Riverside, 2009. / Includes abstract. Title from first page of PDF file (viewed March 11, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 149-156). Also issued in print.

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M. Tech. Electrical Engineering / It is widely believed that the implementation of multi-user multiple-input multiple- output (MU-MIMO) technology at the radio access portion of current and future wireless networks would positively impact on the performance of such networks. This however demands the design of efficient multi-user scheduling algorithms at the data link layer. One algorithm that is known to be throughput optimal is the opportunistic scheduler. This work takes a cross-layer approach in designing a scheduler that takes into account both the channel and queue states of users. We propose a scheduling algorithm referred to as the Maximum Throughput Scheduler (MTS). The MTS explicitly expresses network throughput as the utility function. Through simulations, we show that the MTS outperforms other schedulers in terms of network throughput.