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The focus of this dissertation is the study of advanced processing techniques for multiuser interference cancellation in direct sequence code division multiple access communications. Emphasis is placed on the development of efficient techniques that are practical to implement. The work begins with a study of several sub-optimal multiuser detection techniques under a variety of conditions. Multistage parallel interference cancellation is identified as a practical and robust approach for mitigating multiple access interference. In order to reduce the effect of biased decision statistics inherent to parallel cancellation, a low-complexity modification to parallel interference cancellation that significantly improves performance is derived. Based on this approach, two real-time DSP implementations are devised, one fully coherent and one non-coherent. Multi-symbol differential detection is then explored as an alternative for improving the performance of the non-coherent approach. Additionally, dual-antenna diversity techniques are also investigated as a means for improving performance in multipath environments. / Ph. D.

There is increasing interest in the exploitation of multiple-input and multiple-output (MIMO) channels to enhance the capacity of wireless systems. In this study, we develop and evaluate a channel model, evaluate the corresponding channel capacity, and design and analyze a simple orthogonal transmit waveform for MIMO channels in mobile radio environments. We also evaluate the system performance of various interference cancellation techniques when employing multiple-receive antenna in interference-limited systems. The first part of this dissertation presents two major contributions to MIMO systems. The analytical expression for space-time MIMO channel correlation is derived for a Rayleigh fading channel. The information-theoretic channel capacity based on this correlation is also evaluated for a wide variety of mobile radio channels. The second part of this dissertation presents two major contributions to the area of orthogonal waveform design. We analyze the bit-error-rate (BER) performance of a proposed space-time orthogonal waveform for MIMO mobile radio communications. The application of the proposed space-time orthogonal waveform to a conventional cellular system is also evaluated and briefly discussed. Finally, this dissertation investigates a number of interference cancellation techniques for multiple-receive antenna systems. Both adaptive beamforming and multiuser detection are evaluated for various signal waveforms over a variety of mobile radio channels. / Ph. D.

This research investigates the application of multiuser detection to Code Division Multiple Access for cellular communications. This investigation focuses on the use of multiuser receivers at the base station of mobile radio systems. The first two chapters are dedicated to multiuser detection in general. An extensive literature survey is performed on the research concerning multiuser receivers to date. Six major receiver structures are chosen for extensive simulation studies. The bit error rate performance of these receivers is investigated in several system environments. Additionally, practical issues are considered such as computational complexity and robustness to code tracking errors. From this work, one receiver structure is identified for further study, namely multistage interference cancellation. The theoretical performance of this receiver is analyzed using a standard Gaussian Approximation and an Improved Gaussian Approximation for AWGN and fading environments. Additionally, the resistance of the receiver to interference energy levels is explored. Parameter estimation is an important issue for interference cancellation. Simple methods of improving parameter estimation are examined, as is the effect of parameter estimation error on system performance. A baseband hardware implementation is detailed and several design challenges are presented. Results are given for the performance of the implemented receiver and shown to match well with theory and computer simulation. Finally, the implications of this research are discussed. / Ph. D.

Parallel interference cancellation for DS-CDMA has been shown to suffer from biased amplitude estimates if a matched-filter estimator is used. The bias magnitude is proportional to the number of interfering users. For heavy system loads, the bias has been shown to adversely effect the accuracy of the interference cancellation process, thereby impairing BER after cancellation. Empirical simulation work has demonstrated that weighting down interference estimates can improve BER performance. This thesis substantiates these BER improvements by modelling and analyzing a soft interference cancellation technique which mitigates the effects of the bias by minimizing BER after cancellation in a bit-synchronous parallel interference cancellation CDMA receiver. We analyze system decision metrics with down-scaled interference estimates and determine both the mean and variance of the biased decision statistics. From these two metric moments, system BER is evaluated, and the optimal interference scaling function which minimizes BER is derived. We demonstrate BER performance enhancements by simulating this soft interference cancellation technique in systems under perfect power control and in the near-far situation. We further discuss the applicability of the results to asynchronous systems. / Master of Science

Interference is a fundamental problem in wireless networks. An effective solution to this problem usually calls for a cross-layer approach. Although there exist a large volume of works on interference management techniques in the literature, most of them are limited to signal processing at the physical (PHY) layer or information-theoretic exploitation. Studies of advanced interference techniques from a cross-layer optimization perspective remain limited, especially involving multi-hop wireless networks. This dissertation aims at filling this gap by offering a comprehensive investigation of three interference techniques: interference cancellation (IC), interference alignment (IA), and interference neutralization (IN). This dissertation consists of three parts: the first part studies IC in distributed multi-hop multiple-input multiple-output (MIMO) networks; the second part studies IA in multi-hop networks, cellular networks, and underwater acoustic (UWA) networks; and the third part focuses on IN in multi-hop single-antenna networks. While each part makes a step towards advancing an interference technique, they collectively constitute a body of work on interference management in the networking research community. Results in this dissertation not only advance network-level understanding of the three interference management techniques, but also offer insights and guidance on how these techniques may be incorporated in upper-layer protocol design. In the first part, we study IC in multi-hop MIMO networks where resource allocation is achieved through neighboring node coordination and local information exchange. Based on a well-established degree-of-freedom (DoF) MIMO model, we develop a distributed DoF scheduling algorithm with the objective of maximizing network-level throughput while guaranteeing solution feasibility at the PHY layer. The proposed algorithm accomplishes a number of beneficial features, including polynomial-time complexity, amenability to local implementation, a guarantee of feasibility at the PHY layer, and competitive throughput performance. Our results offer a definitive ``yes'' answer to the question --- Can the node-ordering DoF model be deployed in a distributed multi-hop MIMO network? In particular, we show that the essence of the DoF model --- a global node ordering, can be implicitly achieved via local operations, albeit it is invisible to individual node. In the second part, we investigate IA in various complex wireless networks from a networking perspective. Specifically, we study IA in three different domains: spatial domain, spectral domain, and temporal domain. In the spatial domain, we study IA for multi-hop MIMO networks. We derive a set of simple constraints to characterize the IA capability at the PHY layer. We prove that as long as the set of simple constraints are satisfied, there exists a feasible IA scheme (i.e., precoding and decoding vectors) at the PHY layer so that the data streams on each link can be transported free of interference. Therefore, instead of dealing with the complex design of precoding and decoding vectors, our IA constraints only require simple algebraic addition/subtraction operations. Such simplicity allows us to study network-level IA problems without being distracted by the tedious details in signal design at the PHY layer. Based on these IA constraints, we develop an optimization framework for unicast and multicast communications. In the spectral domain, we study IA in OFDM-based cellular networks. Different from spatial IA, spectral IA is achieved by mapping data streams onto a set of frequency bands/subcarriers (rather than a set of antenna elements). For the uplink, we derive a set of simple IA constraints to characterize a feasible DoF region for a cellular network. We show how to construct precoding and decoding vectors at the PHY layer so that each data stream can be transported free of interference. Based on the set of IA constraints, we study a user throughput maximization problem and show the throughput improvement over two other schemes via numerical results. For the downlink, we find that we can exploit the uplink IA constraints to the downlink case simply by reversing the roles of user and base station. Further, the downlink user throughput maximization problem has the exactly same formulation as the uplink problem and thus can be solved in the exactly same way. In the temporal domain, we study IA for UWA networks. A fundamental issue in UWA networks is large propagation delays due to slow signal speed in water medium. But temporal IA has the potential to turn the adverse effect of large propagation delays into something beneficial. We propose a temporal IA scheme based on propagation delays, nicknamed PD-IA, for multi-hop UWA networks. We first derive a set of PD-IA constraints to guarantee PD-IA feasibility at the PHY layer. Then we develop a distributed PD-IA scheduling algorithm, called Shark-IA, to maximally overlap interference in a multi-hop UWA network. We show that PD-IA can turn the adverse propagation delays to throughput improvement in multi-hop UWA networks. In the third part, we study IN for multi-hop single-antenna networks with full cooperation among the nodes. The fundamental problem here is node selection for IN in a multi-hop network environment. We first establish an IN reference model to characterize the IN capability at the PHY layer. Based on this reference model, we develop a set of constraints that can be used to quickly determine whether a subset of links can be active simultaneously. By identifying each eligible neutralization node as a neut, we study IN in a multi-hop network with a set of sessions and derive the necessary constraints to characterize neut selection, IN, and scheduling. These constraints allow us to study IN problems from a networking perspective but without the need of getting into signal design issues at the PHY layer. By applying our IN model and constraints to study a throughput maximization problem, we show that the use of IN can generally increase network throughput. In particular, throughput gain is most significant when there is a sufficient number of neuts that can be used for IN. In summary, this dissertation offers a comprehensive investigation of three interference management techniques (IC, IA, and IN) from a networking perspective. Theoretical and algorithmic contributions of this dissertation encompass characterization of interference exploitation capabilities at the PHY layer, derivation of tractable interference models, development of feasibility proof for each interference model, formulation of throughput maximization problems, design of distributed IC and PD-IA scheduling algorithms, and development of near-optimal solutions with a performance guarantee. The results in this dissertation offer network-level understanding of the three interference management techniques and lay the groundwork for future research on interference management in wireless networks. / Ph. D.

Interest in Ultra-wideband (UWB) has surged since the FCC's approval of a First Report and Order in February 2002 which provides spectrum for the use of UWB in various application areas. Because of the extremely large bandwidth UWB is currently being touted as a solution for high data rate, short-range wireless networks. An integral part of designing systems for this application or any application is an understanding of the statistical nature of the wireless UWB channel. This thesis presents statistical characterizations for the large and small scale indoor channel. Specifically, for large scale modeling channel frequency dependence is investigated in order to justify the application of traditional narrowband path loss models to UWB signals. Average delay statistics and their distributions are also presented for small scale channel modeling. The thesis also investigates narrowband interference cancellation. To protect legacy narrowband systems the FCC requires any UWB transmission to maintain a very low power spectral density. However, a UWB system may therefore be hampered by the presence of a higher power narrowband signal. Narrowband interferers have a much greater power spectral density than UWB signals and can negatively affect signal acquisition, demodulation, and ultimately lead to poor bit error performance. It is therefore desirable to mitigate any in-band narrowband interference. If the interferer's frequency is known then it may simply be removed using a notched filter. It is however of more interest to develop an adaptive solution capable of canceling interference at any frequency across the band. Solutions which are applied in the analog front end are preferable to digital backend solutions since the latter require extremely high rate sampling. The thesis therefore discusses two analog front-end interference cancellation techniques. The first technique digitally estimates the narrowband interference (this is possible because the UWB signal is not being sampled) and produces an RF estimate to perform the narrowband cancellation in the analog domain. Two estimation techniques, an LMS algorithm and a transversal filter, are compared according to their error performances. The second solution performs real-time Fourier analysis using transform domain processing. The signal is converted to the frequency domain using chirp Fourier transforms and filtered according to the UWB spectrum. This technique is also characterized in terms of bit error rate performance. Further discussion is provided on chirp filter bandwidths, center frequencies, and the applicability of the technology to UWB. / Master of Science

In this thesis, I demonstrate a genetic-algorithm-based optimization method for designing matching and decoupling networks (MDNs) for asymmetric two-element antenna arrays. The proposed method considers practical aspects in MDN realization by accounting for short pieces of transmission lines between the lumped elements and only using capacitor/inductor values from a predefined database of commercially available lumped component values. In addition, the proposed algorithm is able to explore all subsets of a general MDN topology in its search for a solution, providing some flexibility for system optimization (e.g., reducing the number of lumped elements used in an MDN). Details about the proposed approach along with performance analysis of four design examples based on this method are presented. One of the designs was fabricated and measured to demonstrate the effectiveness of the proposed design method. Chapter 1 provides the motivation and context for this work with relevant literature review and objectives of this thesis. Chapter 2 reviews existing MDN design techniques and discusses practical design considerations for the proposed method. Chapter 3 briefly discusses the basics of genetic algorithm (GA) and its relevance to this work. Chapter 4 presents the method proposed in my thesis work and describes how the genetic algorithm is implemented for designing MDNs for asymmetric two-element antenna arrays. Chapter 5 reports the details of four different MDN design examples along with their simulation and measurement results. Chapter 6 concludes the thesis work and discusses potential future development to further advance this work.