The past two decades have seen a surge in the number of applications requiring precise positioning data. Modern cellular networks offer many services based on the user's location, such as emergency services (e.g., E911), and emerging wireless sensor networks are being used in applications spanning environmental monitoring, precision agriculture, warehouse and manufacturing logistics, and traffic monitoring, just to name a few. In these sensor networks in particular, obtaining precise positioning data of the sensors gives vital context to the measurements being reported. While the Global Positioning System (GPS) has traditionally been used to obtain this positioning data, the deployment locations of these cellular and sensor networks in GPS-constrained environments (e.g., cities, indoors, etc.), along with the need for reliable positioning, requires a localization scheme that does not rely solely on GPS. This has lead to localization being performed entirely by the network infrastructure itself, or by the network infrastructure aided, in part, by GPS. In the literature, benchmarking localization performance in these networks has traditionally been done in a deterministic manner. That is, for a fixed setup of anchors (nodes with known location) and a target (a node with unknown location) a commonly used benchmark for localization error, such as the Cramer-Rao lower bound (CRLB), can be calculated for a given localization strategy, e.g., time-of-arrival (TOA), angle-of-arrival (AOA), etc. While this CRLB calculation provides excellent insight into expected localization performance, its traditional treatment as a deterministic value for a specific setup is limited. Rather than trying to gain insight into a specific setup, network designers are more often interested in aggregate localization error statistics within the network as a whole. Questions such as: "What percentage of the time is localization error less than x meters in the network?" are commonplace. In order to answer these types of questions, network designers often turn to simulations; however, these come with many drawbacks, such as lengthy execution times and the inability to provide fundamental insights due to their inherent ``block box'' nature. Thus, this dissertation presents the first analytical solution with which to answer these questions. By leveraging tools from stochastic geometry, anchor positions and potential target positions can be modeled by Poisson point processes (PPPs). This allows for the CRLB of position error to be characterized over all setups of anchor positions and potential target positions realizable within the network. This leads to a distribution of the CRLB, which can completely characterize localization error experienced by a target within the network, and can consequently be used to answer questions regarding network-wide localization performance. The particular CRLB distribution derived in this dissertation is for fourth-generation (4G) and fifth-generation (5G) sub-6GHz networks employing a TOA localization strategy. Recognizing the tremendous potential that stochastic geometry has in gaining new insight into localization, this dissertation continues by further exploring the union of these two fields. First, the concept of localizability, which is the probability that a mobile is able to obtain an unambiguous position estimate, is explored in a 5G, millimeter wave (mm-wave) framework. In this framework, unambiguous single-anchor localization is possible with either a line-of-sight (LOS) path between the anchor and mobile or, if blocked, then via at least two NLOS paths. Thus, for a single anchor-mobile pair in a 5G, mm-wave network, this dissertation derives the mobile's localizability over all environmental realizations this anchor-mobile pair is likely to experience in the network. This is done by: (1) utilizing the Boolean model from stochastic geometry, which statistically characterizes the random positions, sizes, and orientations of reflectors (e.g., buildings) in the environment, (2) considering the availability of first-order (i.e., single-bounce) reflections as well as the LOS path, and (3) considering the possibility that reflectors can either facilitate or block reflections. In addition to the derivation of the mobile's localizability, this analysis also reveals that unambiguous localization, via reflected NLOS signals exclusively, is a relatively small contributor to the mobile's overall localizability. Lastly, using this first-order reflection framework developed under the Boolean model, this dissertation then statistically characterizes the NLOS bias present on range measurements. This NLOS bias is a common phenomenon that arises when trying to measure the distance between two nodes via the time delay of a transmitted signal. If the LOS path is blocked, then the extra distance that the signal must travel to the receiver, in excess of the LOS path, is termed the NLOS bias. Due to the random nature of the propagation environment, the NLOS bias is a random variable, and as such, its distribution is sought. As before, assuming NLOS propagation is due to first-order reflections, and that reflectors can either facilitate or block reflections, the distribution of the path length (i.e., absolute time delay) of the first-arriving multipath component (MPC) is derived. This result is then used to obtain the first NLOS bias distribution in the localization literature that is based on the absolute delay of the first-arriving MPC for outdoor time-of-flight (TOF) range measurements. This distribution is shown to match exceptionally well with commonly assumed gamma and exponential NLOS bias models in the literature, which were only attained previously through heuristic or indirect methods. Finally, the flexibility of this analytical framework is utilized by further deriving the angle-of-arrival (AOA) distribution of the first-arriving MPC at the mobile. This distribution gives novel insight into how environmental obstacles affect the AOA and also represents the first AOA distribution, of any kind, derived under the Boolean model. In summary, this dissertation uses the analytical tools offered by stochastic geometry to gain new insights into localization metrics by performing analyses over the entire ensemble of infrastructure or environmental realizations that a target is likely to experience in a network. / Doctor of Philosophy / The past two decades have seen a surge in the number of applications requiring precise positioning data. Modern cellular networks offer many services based on the user's location, such as emergency services (e.g., E911), and emerging wireless sensor networks are being used in applications spanning environmental monitoring, precision agriculture, warehouse and manufacturing logistics, and traffic monitoring, just to name a few. In these sensor networks in particular, obtaining precise positioning data of the sensors gives vital context to the measurements being reported. While the Global Positioning System (GPS) has traditionally been used to obtain this positioning data, the deployment locations of these cellular and sensor networks in GPS-constrained environments (e.g., cities, indoors, etc.), along with the need for reliable positioning, requires a localization scheme that does not rely solely on GPS. This has lead to localization being performed entirely by the network infrastructure itself, or by the network infrastructure aided, in part, by GPS. When speaking in terms of localization, the network infrastructure consists of what are called anchors, which are simply nodes (points) with a known location. These can be base stations, WiFi access points, or designated sensor nodes, depending on the network. In trying to determine the position of a target (i.e., a user, or a mobile), various measurements can be made between this target and the anchor nodes in close proximity. These measurements are typically distance (range) measurements or angle (bearing) measurements. Localization algorithms then process these measurements to obtain an estimate of the target position. The performance of a given localization algorithm (i.e., estimator) is typically evaluated by examining the distance, in meters, between the position estimates it produces vs. the actual (true) target position. This is called the positioning error of the estimator. There are various benchmarks that bound the best (lowest) error that these algorithms can hope to achieve; however, these benchmarks depend on the particular setup of anchors and the target. The benchmark of localization error considered in this dissertation is the Cramer-Rao lower bound (CRLB). To determine how this benchmark of localization error behaves over the entire network, all of the various setups of anchors and the target that would arise in the network must be considered. Thus, this dissertation uses a field of statistics called stochastic geometry} to model all of these random placements of anchors and the target, which represent all the setups that can be experienced in the network. Under this model, the probability distribution of this localization error benchmark across the entirety of the network is then derived. This distribution allows network designers to examine localization performance in the network as a whole, rather than just for a specific setup, and allows one to obtain answers to questions such as: "What percentage of the time is localization error less than x meters in the network?" Next, this dissertation examines a concept called localizability, which is the probability that a target can obtain a unique position estimate. Oftentimes localization algorithms can produce position estimates that congregate around different potential target positions, and thus, it is important to know when algorithms will produce estimates that congregate around a unique (single) potential target position; hence the importance of localizability. In fifth generation (5G), millimeter wave (mm-wave) networks, only one anchor is needed to produce a unique target position estimate if the line-of-sight (LOS) path between the anchor and the target is unimpeded. If the LOS path is impeded, then a unique target position can still be obtained if two or more non-line-of-sight (NLOS) paths are available. Thus, over all possible environmental realizations likely to be experienced in the network by this single anchor-mobile pair, this dissertation derives the mobile's localizability, or in this case, the probability the LOS path or at least two NLOS paths are available. This is done by utilizing another analytical tool from stochastic geometry known as the Boolean model, which statistically characterizes the random positions, sizes, and orientations of reflectors (e.g., buildings) in the environment. Under this model, considering the availability of first-order (i.e., single-bounce) reflections as well as the LOS path, and considering the possibility that reflectors can either facilitate or block reflections, the mobile's localizability is derived. This result reveals the roles that the LOS path and the NLOS paths play in obtaining a unique position estimate of the target. Using this first-order reflection framework developed under the Boolean model, this dissertation then statistically characterizes the NLOS bias present on range measurements. This NLOS bias is a common phenomenon that arises when trying to measure the distance between two nodes via the time-of-flight (TOF) of a transmitted signal. If the LOS path is blocked, then the extra distance that the signal must travel to the receiver, in excess of the LOS path, is termed the NLOS bias. As before, assuming NLOS propagation is due to first-order reflections and that reflectors can either facilitate or block reflections, the distribution of the path length (i.e., absolute time delay) of the first-arriving multipath component (MPC) (or first-arriving ``reflection path'') is derived. This result is then used to obtain the first NLOS bias distribution in the localization literature that is based on the absolute delay of the first-arriving MPC for outdoor TOF range measurements. This distribution is shown to match exceptionally well with commonly assumed NLOS bias distributions in the literature, which were only attained previously through heuristic or indirect methods. Finally, the flexibility of this analytical framework is utilized by further deriving angle-of-arrival (AOA) distribution of the first-arriving MPC at the mobile. This distribution yields the probability that, for a specific angle, the first-arriving reflection path arrives at the mobile at this angle. This distribution gives novel insight into how environmental obstacles affect the AOA and also represents the first AOA distribution, of any kind, derived under the Boolean model. In summary, this dissertation uses the analytical tools offered by stochastic geometry to gain new insights into localization metrics by performing analyses over all of the possible infrastructure or environmental realizations that a target is likely to experience in a network.

"2009" / Thesis (MSc (Hons))--Macquarie University, Faculty of Science, Dept. of Physics and Engineering, 2010. / Bibliography: p. 163-166. / Introduction -- Design theory and process technology -- 15GHz oscillator implementations -- 24GHz oscillator implementation -- Frequency prescaler implementation -- MMIC fabrication and measurement -- Conclusion. / Advances in Silicon Germanium (SiGe) Bipolar Complementary Metal Oxide Semiconductor (BiCMOS) technology has caused a recent revolution in low-cost Monolithic Microwave Integrated Circuit (MMIC) design. -- This thesis presents the design, fabrication and measurement of four MMICs for frequency synthesis, manufactured in a commercially available IBM 0.18μm SiGe BiCMOS technology with ft = 60GHz. The high speed and low-cost features of SiGe Heterojunction Bipolar Transistors (HBTs) were exploited to successfully develop two single-ended injection-lockable 15GHz Voltage Controlled Oscillators (VCOs) for application in an active Ka-Band antenna beam-forming network, and a 24GHz differential cross-coupled VCO and 1/6 synchronous static frequency prescaler for emerging Ultra Wideband (UWB) automotive Short Range Radar (SRR) applications. -- On-wafer measurement techniques were used to precisely characterise the performance of each circuit and compare against expected simulation results and state-of-the-art performance reported in the literature. -- The original contributions of this thesis include the application of negative resistance theory to single-ended and differential SiGe VCO design at 15-24GHz, consideration of manufacturing process variation on 24GHz VCO and prescaler performance, implementation of a fully static multi-stage synchronous divider topology at 24GHz and the use of differential on-wafer measurement techniques. -- Finally, this thesis has llustrated the excellent practicability of SiGe BiCMOS technology in the engineering of high performance, low-cost MMICs for frequency synthesis in millimeterwave (mm-wave) devices. / Mode of access: World Wide Web. / xxii, 166 p. : ill (some col.)

A 5 GHz continuous unlicensed bandwidth is available at millimeter-wave (mm-wave) frequencies around 60 GHz and offers the prospect for multi gigabit wireless applications. The inherent atmospheric attenuation at 60 GHz due to oxygen absorption makes the frequency range ideal for short distance communication networks. For these mm-wave wireless networks, the low noise amplifier (LNA) is a critical subsystem determining the receiver performance i.e., the noise figure (NF) and receiver sensitivity. It however proves challenging to realise high performance mm-wave LNAs in a silicon (Si) complementary metal-oxide semiconductor (CMOS) technology. The mm-wave passive devices, specifically on-chip inductors, experience high propagation loss due to the conductivity of the Si substrate at mm-wave frequencies, degrading the performance of the LNA and subsequently the performance of the receiver architecture. The research is aimed at realising a high performance mm-wave LNA in a Si BiCMOS technology. The focal points are firstly, the fundamental understanding of the various forms of losses passive inductors experience and the techniques to address these issues, and secondly, whether the performance of mm-wave passive inductors can be improved by means of geometry optimising. An associated hypothesis is formulated, where the research outcome results in a preferred passive inductor and formulates an optimised passive inductor for mm-wave applications. The performance of the mm-wave inductor is evaluated using the quality factor (Q-factor) as a figure of merit. An increased inductor Q-factor translates to improved LNA input and output matching performance and contributes to the lowering of the LNA NF. The passive inductors are designed and simulated in a 2.5D electromagnetic (EM) simulator. The electrical characteristics of the passive structures are exported to a SPICE netlist which is included in a circuit simulator to evaluate and investigate the LNA performance. Two LNAs are designed and prototyped using the 13μ-m SiGe BiCMOS process from IBM as part of the experimental process to validate the hypothesis. One LNA implements the preferred inductor structures as a benchmark, while the second LNA, identical to the first, replaces one inductor with the optimised inductor. Experimental verification allows complete characterization of the passive inductors and the performance of the LNAs to prove the hypothesis. According to the author's knowledge, the slow-wave coplanar waveguide (S-CPW) achieves a higher Q-factor than microstrip and coplanar waveguide (CPW) transmission lines at mm-wave frequencies implemented for the 130 nm SiGe BiCMOS technology node. In literature, specific S-CPW transmission line geometry parameters have previously been investigated, but this work optimises the signal-to-ground spacing of the S-CPW transmission lines without changing the characteristic impedance of the lines. Optimising the S-CPW transmission line for 60 GHz increases the Q-factor from 38 to 50 in simulation, a 32 % improvement, and from 8 to 10 in measurements. Furthermore, replacing only one inductor in the output matching network of the LNA with the higher Q-factor inductor, improves the input and output matching performance of the LNA, resulting in a 5 dB input and output reflection coefficient improvement. Although a 5 dB improvement in matching performance is obtained, the resultant noise and gain performance show no significant improvement. The single stage LNAs achieve a simulated gain and NF of 13 dB and 5.3 dB respectively, and dissipate 6 mW from the 1.5 V supply. The LNA focused to attain high gain and a low NF, trading off linearity and as a result obtained poor 1 dB compression of -21.7 dBm. The LNA results are not state of the art but are comparable to SiGe BiCMOS LNAs presented in literature, achieving similar gain, NF and power dissipation figures. / Dissertation (MEng)--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted