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

The research described herein was undertaken to determine how masked thresholds changed when individuals wore an active noise reduction (ANR) hearing protection device (HPD), a passive HPD, or no HPD. An ANR earmuff, a passive earmuff, and a user-molded foam earplug were tested in two types of noises (pink and red) at two different noise levels (85 dBA and 100 dBA). The signal used was an industry-standard backup alarm. The experimental design was completely within-subjects. An ascending method of limits was used to obtain 15-20 correct positive responses, which were then averaged to obtain the masked thresholds for each treatment condition. A visual probability monitoring task was incorporated in the experimental design to provide a loading task for the participants. In addition to masked thresholds, comfort and mental workload were assessed. Finally, participants were asked to rank each of the three HPDs with respect to their perceived ability to facilitate hearing the signal in noise. Results indicated that in 85 dBA noise, masked thresholds were lower when hearing protection devices were worn, compared to the unoccluded condition. Additionally, the results indicated that the ANR device provided a significant advantage (lower masked thresholds) over the passive earmuff in the low-frequency biased red noise (across both noise levels) and the 100 dBA noise level (across both noise spectra). However, the ANR earmuff exhibited no significant advantage over the user-molded foam earplug in any of the conditions. Rather, the user-molded foam earplug produced significantly lower masked thresholds at 100 dBA. The results also indicated that there was no difference between the three devices in their perceived ability to facilitate detection of the signal. There was also not a significant difference in comfort ratings between the three HPDs, although there were several complaints about the comfort of the ANR earmuff during the experiment. / 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.

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.

Two experiments were conducted to investigate Adaptive Noise Cancelling and Cepstrum echo removal post-processing techniques on acoustic data from a linear microphone array in an anechoic chamber. A point source speaker driven with white noise was used as the primary signal. The first experiment included a background speaker to provide interference noise at three different Signal-to-Noise Ratios to simulate noise propagating down a wind tunnel circuit. The second experiment contained only the primary source and the wedges were removed from the floor to simulate reflections found in a wind tunnel environment. The techniques were applicable to both signal microphone and array analysis. The Adaptive Noise Cancellation proved successful in its task of removing the background noise from the microphone signals at SNRs as low as -20 dB. The recovered signals were then used for array processing. A simulation reflection case was analyzed with the Cepstral technique. Accurate removal of the reflection effects was achieved in recovering both magnitude and phase of the direct signal. Experimental data resulted in Cepstral features that caused errors in phase accuracy. A simple phase correction procedure was proposed for this data, but in general it appears that the Cepstral technique is and would be not well suited for all experimental data. / Master of Science

Over the past decade, wireless data communication has experienced a phenomenal growth, which is driven by the popularity of wireless devices and the growing number of bandwidth hungry applications. During the same period, various advanced communication technologies have emerged to improve network throughput. Some examples include multi-input multi-output (MIMO), full duplex, cognitive radio, mmWave, among others. An important research direction is to understand the impacts of these new technologies on network throughput performance. Such investigation is critical not only for theoretical understanding, but also can be used as a guideline to design algorithms and network protocols in the field. The goal of this dissertation is to understand the impact of some advanced technologies on network throughput performance. More specifically, we investigate the following three technologies: MIMO, full duplex, and mmWave communication. For each technology, we explore the performance envelope of wireless networks by studying a throughput maximization problem. / Ph. D. / As everyone knows, we are now living in a connected world, where network access is available anytime and anywhere. According to Cisco’s report [97], global Internet traffic is expected to reach 2.3 zettabytes per year by 2020, and wireless data traffic will account for 65% of the total Internet traffic. There are three primary contributors for the explosive growth of wireless data demand: the rising number of wireless devices, the increasing number of new applications, and the evergrowing amount of video traffic. Each year, all kinds of smart devices with increased intelligence are introduced in market. The number of wireless devices is predicted to reach 11.6 billion by 2020 [97]. The smart devices enable people to enjoy mobile applications for entertainment, such as social networking, video streaming, and gaming. Such bandwidth hungry applications have changed the wireless data consumption pattern. According to Ericssons report [98], video traffic dominates the mobile data consumption for all kinds of mobile devices. Moreover, the amount of video traffic is still growing more than 50 % annually. To meet the ever-growing traffic demand, innovative technologies have been developed to expand the capacity of wireless networks. Some examples include multi-input multi-output (MIMO), full duplex, cognitive radio, mmWave, ultra-wideband, among others. In this dissertation, we aim to investigate the impact of such advanced technologies on network throughput performance. Such theoretical study is critical since it can be used as a guidline to design real-world network protocols.

Research efforts have shown that capacity in a DS/CDMA cellular system can be increased through the use of digital signal processing techniques that exploit the nature of the multiple access interference (MAI). By jointly demodulating the users in the system, this interference can be characterized and reduced thus decreasing the overall probability of error in the system. Numerous multiuser structures exist, each with varying degrees of complexity and performance. However, the size and complexity of these structures is large relative to a conventional receiver. This effort demonstrates a practical approach to implementing parallel interference cancellation applied to DBPSK DS/CDMA on an FPGA-based configurable computing platform. The system presented acquires, tracks, cancels, and demodulates four users independently and performs various levels of interference cancellation. The performance gain of the receiver in a four-user environment under various levels of noise and cancellation are presented. / Master of Science

No description available.

This work deals with digital signal processing in the field of adaptive filtering. Fundamental basics of adaptive filtering are described and primary aim is to create executable laboratory examples, using adaptive filtering, in LabView programming language. These laboratory examples are intended to be used by students fo studying and during laboratory lessons. Objective is to connect the examples with external devices, such as microphone. A microphone is used as an user's speech input acquiring interface. In the thesis is depicted Wiener's filter and problem of adaptive filtering is discussed. Contemporary adaptive algorithms are described and their applications as well. Most mentioned is the LMS algorithm and it's forms. Laboratory examples use following concepts: Adaptive Echo Cancellation, Active Noise Control and System Identification. Each of these examples is solely executable (need for LabView or Run-time engine), consisting also of theory with diagrams. Examples therefore are usable even without manual.

In telecommunication, messages sent through a wireless medium often experience noise interfering with the signal in a way that corrupts the messages. As the demand for high throughput in the mobile network is increasing, algorithms that can detectand correct these corrupted messages quickly and accurately are of interest to the industry. Polar codes have been chosen by the Third Generation Partnership Project as the error correction code for 5G New Radio control channels. This thesis work aimed to investigate whether the polar code Successive Cancellation (SC) could be parallelized and if a graphics processing unit (GPU) can be utilized to optimize the execution time of the algorithm. The polar code Successive Cancellation was enhanced by implementing tree pruning and support for GPUs to leverage their parallelization. The difference in execution time between the concurrent and sequential versions of the SC algorithm with and without tree pruning was evaluated. The tree pruning SC algorithm almost always offered shorter execution times than the SC algorithm that did not employ treepruning. However, the support for GPUs did not reduce the execution time in these tests. Thus, the GPU is not certain to be able to improve this type of enhanced SC algorithm based on these results. / Meddelanden som överförs över ett mobilt nät utsätts ofta för brus som distorterar dem. I takt med att intresset ökat för hög genomströmning i mobilnätet har också intresset för algoritmer som snabbt och tillförlitligt kan upptäcka och korrigera distorderade meddelanden ökat. Polarkoder har valts av "Third Generation Partnership Project" som den klass av felkorrigeringskoder som ska användas för 5G:s radiokontrollkanaler. Detta examensarbete hade som syfte att undersöka om polarkoden "Successive Cancellation" (SC) skulle kunna parallelliseras och om en grafisk bearbetningsenhet (GPU) kan användas för att optimera exekveringstiden för algoritmen. SC utökades med stöd för trädbeskärning och parallellisering med hjälp av GPU:er. Skillnaden i exekveringstid mellan de parallella och sekventiella versionerna av SC-algoritmen med och utan trädbeskärning utvärderades. SC-algoritmen för trädbeskärning erbjöd nästan alltid kortare exekveringstider än SC-algoritmen som inte använde trädbeskärning. Stödet för GPU:er minskade dock inte exekveringstiden. Således kan man med dessa resultat inte med säkerhet säga att GPU-stöd skulle gynna SC-algoritmen.