VTechWorks Repository :: Browsing by Author "Tranter, William H."

Browsing by Author "Tranter, William H."

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Adaptation For Multi-Antenna Systems
Phelps, Christopher Ian (Virginia Tech, 2009-08-03)
Previous attempts to adapt MIMO systems in the presence of varying channel conditions typically focus on characterizing the performance of a limited and predefined set of joint MoDem/CoDec and MIMO configurations over a representative set of channel realizations. Other work has attempted to adapt only the MIMO scheme to varying channel conditions without considering modulation format or the channel code used. Finally, attempts to configure the system through direct BER calculation based on channel conditions were also proposed. These methods suffer the problems of dependence on a limited set of simulated curves which may not account for all channel conditions that a real system might see, not configuring all parameters jointly or implicitly requiring channel state information to be fed back to the transmitter. None of these previous attempts have handled both cases where CSIT is available or not while jointly configuring the MoDem, CoDec and multi-antenna scheme. This work consists of two parts, focusing on energy efficiency in the presence of unoccupied frequency bands and on spectrally efficient operation under static frequency assignment. Utilizing minimum Euclidean distances of MoDem constellations and the minimum free Hamming distance metrics for channel codes, we develop distance metrics to describe the MIMO schemes which are considered. A minimum required distance is then determined as a function of desired BER and constellation. Based on the unified set of distance metrics, adaptive algorithms can evaluate the total distance of a signaling scheme, including MoDem, CoDec and MIMO scheme, and then calculate a decision metric based on the total distance and the required distance to meet the desired BER. The proposed system which aims to maximize energy efficiency is able to choose, based on spatial correlation, available channels, CSIT availability, and power amplifier configuration, the appropriate multi-antenna configuration, MoDem and Codec to meet a fixed throughput requirement while maximizing the energy efficiency or robustness of the link. The proposed work assumes that the open channels of a network can be accessed through individually tunable RF chains of the multi-antenna systems. This assumption permits the use of a multi-antenna, multi-channel scheme which sacrifices spatial diversity for frequency diversity. In addition to traditional, single-channel transmit diversity schemes, the adaptive system is also able choose, when more energy efficient, this novel, multi-channel configuration. When focusing on the maximization of spectral efficiency, a more conventional, single-channel model is assumed. In addition to the distance metrics for single-channel diversity schemes, distance metrics are then developed for spatial multiplexing schemes which take into account the interaction of spatial correlation, number of antennas and the rate of the channel code. The adaptive system uses the total distance of the joint configuration of MoDem, CoDec and MIMO scheme to calculate a decision metric which indicates whether the configuration will meet the desired BER. From a list of joint configurations which will meet the desired BER, the adaptive system then chooses the one which maximizes the spectral efficiency.
Adaptation in Reputation Management Systems for Ad hoc Networks
Refaei, Mohamed Tamer (Virginia Tech, 2007-02-02)
An ad hoc network adopts a decentralized unstructured networking model that depends on node cooperation for key network functionalities such as routing and medium access. The significance of node cooperation in ad hoc networks makes network survival particularly sensitive to insider node behavior. The presence of selfish or malicious nodes in an ad hoc network could greatly degrade the network performance and might even result in a total communication breakdown. Consequently, it is important for both security and performance reasons to discourage, expose, and react to such damaging misbehavior. Reputation management systems have been proposed to mitigate against such misbehavior in ad hoc networks. The functions of a reputation management system are to evaluate nodes' quality of behavior based on their cooperation (evaluation), distinguish between well-behaved and misbehaving nodes (detection), and appropriately react to misbehaving nodes (reaction). A significant number of reputation management systems have been proposed for ad hoc networks to date. However, there has been no attempt to consolidate all current research into a formal framework for reputation management systems. The lack of a formal framework is a potential weakness of the research field. For example, a formal comparison of proposed reputation management systems has remained difficult, mainly due to the lack of a formal framework upon which the comparison could be based. There is also a lack of formal metrics that could be used for quantitative evaluation and comparison of reputation management systems. Another major shortcoming in this research field is the assumption that the functions of reputation management (evaluation, detection, and reaction) are carried out homogeneously across time and space at different nodes. The dynamic nature of ad hoc networks causes node behavior to vary spatially and temporally due to changes in the local and network-wide conditions. Reputation management functions do not adapt to such changes, which may impact the system accuracy and promptness. We herein recognize an adaptive reputation management system as one where nodes carry out the reputation management functions heterogeneously across time and space according to the instantaneous perception of each of its surrounding network conditions. In this work, we address the above concerns. We develop a formal framework for reputation management systems upon which design, evaluation, and comparison of reputation management systems can be based. We define and discuss the different components of the framework and the interactions among them. We also define formal metrics for evaluation of reputation management systems. The metrics assess both, the effectiveness (security issues) of a reputation management system in detecting misbehavior and limiting its negative impact on the network, and its efficiency (performance issues) in terms of false positives and overhead exerted by the reputation management system on the network. We also develop ARMS, an autonomous reputation management system, based on the formal framework. The theoretical foundation of ARMS is based on the theory of Sequential Probability Ratio Test introduced by Wald. In ARMS, nodes independently and without cooperation manage their reputation management system functions. We then use ARMS to investigate adaptation in reputation management systems. We discuss some of the characteristics of an adaptive reputation management system such as sensitivity, adaptability, accuracy, and promptness. We consider how the choice of evaluation metric, typically employed by the evaluation function for assessment of node behavior, may impact the sensitivity and accuracy of node behavior evaluation. We evaluate the sensitivity and accuracy of node behavior evaluation using a number of metrics from the network and medium access layer. We then introduce a time-slotted approach to enhance the sensitivity of the evaluation function and show how the duration of an evaluation slot can adapt according to the network activity to enhance the system accuracy and promptness. We also show how the detection function can adapt to the network conditions by using the node's own behavior as a benchmark to set its detection parameters. To the best of our knowledge, this is the first work to explore the adaptation of the reputation management functions in ad hoc networks.
Adaptive Equalization for Indoor Channels
Morton, John M. (Virginia Tech, 1998-08-03)
This thesis describes the use of adaptive equalization techniques to compensate for the intersymbol interference (ISI) that results when digital data is transmitted over a multipath radio channel. The equalization structures covered in this work are the linear transversal equalizer (LTE), the fractionally spaced equalizer (FSE), the decision-feedback equalizer (DFE), and the maximum-likelihood sequence estimation (MLSE) equalizer. This work also covers adaptive algorithms for equalization including both the least mean squares (LMS) and the recursive least squares (RLS) algorithm. All these equalizer structures and algorithms will be modeled using various simulation modules. Equalization for both stationary and mobile radio channels is considered. Stationary channels are modeled with a simple exponentially decaying profile. The mobile radio channel is represented using a two-ray Rayleigh fading model for an outdoor environment. The SIRCIM channel modeling tool is used to create channel profiles for an indoor mobile radio channel. Adaptive arrays and their similarities to linear equalizers are also studied in this thesis. The properties and performance of simple adaptive array systems using the LMS and RLS algorithms are examined through simulation. This thesis concludes with an in-depth study of the use of adaptive equalization for high-speed data systems operating in an indoor environment. Both stationary and slowly varying radio channels are examined. Simulations of DFE and MLSE equalizers operating in such a system show that both equalizer structures provide better BER performance over a system with no equalization. These simulation results also show that the MLSE equalizer provides better performance than the DFE in almost all cases, but requires a great deal more computations.
An Algorithm and System for Measuring Impedance in D-Q Coordinates
Francis, Gerald (Virginia Tech, 2010-01-25)
This dissertation presents work conducted at the Center for Power Electronics Systems (CPES) at Virginia Polytechnic Institute and State University. Chapter 1 introduces the concept of impedance measurement, and discusses previous work on this topic. This chapter also addresses issues associated with impedance measurement. Chapter 2 introduces the analyzer architecture and the proposed algorithm. The algorithm involves locking on to the voltage vector at the point of common coupling between the analyzer and the system via a PLL to establish a D-Q frame. A series of sweeps are performed, injecting at least two independent angles in the D-Q plane, acquiring D- and Q-axis voltages and currents for each axis of injection at the point of interest. Chapter 3 discusses the analyzer hardware and the criteria for selection. The hardware built ranges from large-scale power level hardware to communication hardware implementing a universal serial bus. An eight-layer PCB was constructed implementing analog signal conditioning and conversion to and from digital signals with high resolution. The PCB interfaces with the existing Universal Controller hardware. Chapter 4 discusses the analyzer software. Software was written in C++, VHDL, and Matlab to implement the measurement process. This chapter also provides a description of the software architecture and individual components. Chapter 5 discusses the application of the analyzer to various examples. A dynamic model of the analyzer is constructed, considering all components of the measurement system. Congruence with predicted results is demonstrated for three-phase balanced linear impedance networks, which can be directly derived based on stationary impedance measurements. Other impedances measured include a voltage source inverter, Vienna rectifier, six-pulse rectifier and an autotransformer-rectifier unit.
Analysis and Development of Blind Adaptive Beamforming Algorithms
Biedka, Thomas E. (Virginia Tech, 2001-10-18)
This dissertation presents a new framework for the development and analysis of blind adaptive algorithms. An adaptive algorithm is said to be 'blind' if it does not require a known training sequence. The main focus is on application of these algorithms to adaptive antenna arrays in mobile radio communications. Adaptive antenna arrays can reduce the effects of cochannel interference, multipath fading, and background noise as compared to more conventional antenna systems. For these reasons, the use of adaptive antennas in wireless communication has received a great deal of attention in the literature. There are several reasons why the study of blind adaptive algorithms is important. First, it is common practice to switch to a blind mode once the training sequence has been processed in order to track a changing environment. Furthermore, the use of a blind algorithm can completely eliminate the need for a training sequence. This is desirable since the use of a training sequence reduces the number of bits available for transmitting information. The analysis framework introduced here is shown to include the well-known Constant Modulus Algorithm (CMA) and decision directed algorithm (DDA). New results on the behavior of the CMA and DDA are presented here, including analytic results on the convergence rate. Previous results have relied on Monte Carlo simulation. This framework is also used to propose a new class of blind adaptive algorithms that offer the potential for improved convergence rate.
Analysis and Implementation of a Novel Single Channel Direction Finding Algorithm on a Software Radio Platform
Keaveny, John Joseph (Virginia Tech, 2005-02-11)
A radio direction finding (DF) system is an antenna array and a receiver arranged in a combination to determine the azimuth angle of a distant emitter. Basically, all DF systems derive the emitter location from an initial determination of the angle-of-arrival (AOA). Radio direction finding techniques have classically been based on multiple-antenna systems employing multiple receivers. Classic techniques such as MUSIC [1][2] and ESPRIT use simultaneous phase information from each antenna to estimate the angle-of-arrival of the signal of interest. In many scenarios (e.g., hand-held systems), however, multiple receivers are impractical. Thus, single channel techniques are of interest, particularly in mobile scenarios. Although the amount of existing research for single channel DF is considerably less than for multi-channel direction finding, single channel direction finding techniques have been previously investigated. Since many of the single channel direction finding techniques are older analog techniques and have been analyzed in previous work, we will investigate a new single channel direction finding technique that takes specific advantage of digital capabilities. Specifically, we propose a phase-based method that uses a bank of Phase-Locked Loops (PLLs) in combination with an eight-element circular array. Our method is similar to the Pseudo-Doppler method in that it samples antennas in a circular array using a commutative switch. In the proposed approach the sampled data is fed to a bank of PLLs which track the phase on each element. The parallel PLLs are implemented in software and their outputs are fed to a signal processing block that estimates the AOA. This thesis presents the details of the new Phase-Locked Loop (PLL) algorithm and compares its performance to existing single channel DF techniques such as the Watson-Watt and the Pseudo-Doppler techniques. We also describe the implementation of the PLL algorithm on a DRS Signal Solutions, Incorporated (DRS-SS) WJ-8629A Software Definable Receiver with Sunrise™ Technology and present measured performance results.
Analytical Framework for the Performance Analysis of Multiple Antenna Systems
Bae, Kyung Kyoon (Virginia Tech, 2005-09-09)
There has been great interest in antenna array processing (diversity, beamforming, null steering, and spatial multiplexing) to enhance the received signal quality and the capacity of wireless communications systems. However, in order to properly exploit the characteristics of different array processing techniques, understanding trade-offs among different techniques and parametric investigation, which offers an insight as to what parameters determine system performance under different situations is necessary. In this study, we present analytical framework which can facilitate the performance analysis of systems with antenna array. Five original contributions to the performance analysis of antenna array processing are presented in this study. First, we present theoretical outage probability of a system equipped with an array which suppresses a few dominant interering signals in TDMA cellular networks when the fading statistics of interfering signals are independent but non-identically distributed. Most of the related previous works assumed either independent and identically distributed fading statistics among cochannel interferences (CCI) or Rayleigh fading when CCI signals are subject to i.n.d. fading statistics. Secondly, the performance of multi-branch predetection equal gain combiner for different modulation techniques in equally correlated Nakagami-m fading is presented through analytical analysis. Specifically, the characteristic function (CHF) and the moment generating function (MGF) of EGC output with correlated inputs are derived and used to evaluate the average symbol error probability (ASEP) and the outage probability performance, respectively. Thirdly, we derived analytical expression which can be used to analyze the performance of different types of diversity techniques in equally correlated Nakagami-m or Rice fading channels. Fourthly, asymptotic analysis on different types of diversity combiners in generalized fading channels is presented in a unifying way. Finally, we investigate and present the impact of transmit diversity at handsets on the reverse link DS/CDMA systems in terms of capacity and coverage over generalized fading channels through analytical approaches. Then, we validate the analytical results with simulation results and investigate practical issues which are hard to capture through analytical analysis using system level simulator we developed. Although we have mainly focused on applying the analytical framework we have derived in this work to the performance analysis of physical layer algorithms such as spatial diversity and adaptive null steering, the framework can be extended to assist the analysis and design of wireless communication systems such as, to name a few, distributed multiple input multiple output (MIMO) system in cooperative wireless networks, multipath routing protocol analysis in wireless fading channels, and antenna selection problems in MIMO system.
Antenna Array Systems: Propagation and Performance
Ertel, Richard Brian (Virginia Tech, 1999-07-28)
Due to the enormous performance gains associated with the use of antenna arrays in wireless networks, it is inevitable that these technologies will become an integral part of future systems. This report focuses on signal propagation modeling for antenna array systems and on its relationship to the performance of these systems. Accurate simulation and analytical models are prerequisite to the characterization of antenna array system performance. Finally, an understanding of the performance of these systems in various environments is needed for effective overall network design. This report begins with an overview of the fundamentals of antenna array systems. A survey of vector channel models is presented. Angle of arrival and time of arrival statistics for the circular and elliptical (Liberti's Model) models are derived. A generalized optimum output SINR analysis is derived for space-time processing structures in frequency selective fading channels. The hardware and software of the MPRG Antenna Array Testbed (MAAT) is described. A literature review of previous antenna array propagation measurements is given. Antenna array measurement results obtained with the MAAT are used to compare the properties of the received signal vector in the various environmental conditions. The influence of channel parameters on the ability of antenna arrays to separate the signals of two users on the reverse link is studied using simulation. Finally, forward link beamforming techniques are reviewed.
Applications of Sensor Fusion to Classification, Localization and Mapping
Abdelbar, Mahi Othman Helmi Mohamed Helmi Hussein (Virginia Tech, 2018-04-30)
Sensor Fusion is an essential framework in many Engineering fields. It is a relatively new paradigm for integrating data from multiple sources to synthesize new information that in general would not have been feasible from the individual parts. Within the wireless communications fields, many emerging technologies such as Wireless Sensor Networks (WSN), the Internet of Things (IoT), and spectrum sharing schemes, depend on large numbers of distributed nodes working collaboratively and sharing information. In addition, there is a huge proliferation of smartphones in the world with a growing set of cheap powerful embedded sensors. Smartphone sensors can collectively monitor a diverse range of human activities and the surrounding environment far beyond the scale of what was possible before. Wireless communications open up great opportunities for the application of sensor fusion techniques at multiple levels. In this dissertation, we identify two key problems in wireless communications that can greatly benefit from sensor fusion algorithms: Automatic Modulation Classification (AMC) and indoor localization and mapping based on smartphone sensors. Automatic Modulation Classification is a key technology in Cognitive Radio (CR) networks, spectrum sharing, and wireless military applications. Although extensively researched, performance of signal classification at a single node is largely bounded by channel conditions which can easily be unreliable. Applying sensor fusion techniques to the signal classification problem within a network of distributed nodes is presented as a means to overcome the detrimental channel effects faced by single nodes and provide more reliable classification performance. Indoor localization and mapping has gained increasing interest in recent years. Currently-deployed positioning techniques, such as the widely successful Global Positioning System (GPS), are optimized for outdoor operation. Providing indoor location estimates with high accuracy up to the room or suite level is an ongoing challenge. Recently, smartphone sensors, specially accelerometers and gyroscopes, provided attractive solutions to the indoor localization problem through Pedestrian Dead-Reckoning (PDR) frameworks, although still suffering from several challenges. Sensor fusion algorithms can be applied to provide new and efficient solutions to the indoor localization problem at two different levels: fusion of measurements from different sensors in a smartphone, and fusion of measurements from several smartphones within a collaborative framework.
An Approach to Using Cognition in Wireless Networks
Morales-Tirado, Lizdabel (Virginia Tech, 2009-12-18)
Third Generation (3G) wireless networks have been well studied and optimized with traditional radio resource management techniques, but still there is room for improvement. Cognitive radio technology can bring significantcant network improvements by providing awareness to the surrounding radio environment, exploiting previous network knowledge and optimizing the use of resources using machine learning and artificial intelligence techniques. Cognitive radio can also co-exist with legacy equipment thus acting as a bridge among heterogeneous communication systems. In this work, an approach for applying cognition in wireless networks is presented. Also, two machine learning techniques are used to create a hybrid cognitive engine. Furthermore, the concept of cognitive radio resource management along with some of the network applications are discussed. To evaluate the proposed approach cognition is applied to three typical wireless network problems: improving coverage, handover management and determining recurring policy events. A cognitive engine, that uses case-based reasoning and a decision tree algorithm is developed. The engine learns the coverage of a cell solely from observations, predicts when a handover is necessary and determines policy patterns, solely from environment observations.
Blind Acquisition of Short Burst with Per-Survivor Processing (PSP)
Mohammad, Maruf H. (Virginia Tech, 2002-11-26)
This thesis investigates the use of Maximum Likelihood Sequence Estimation (MLSE) in the presence of unknown channel parameters. MLSE is a fundamental problem that is closely related to many modern research areas like Space-Time Coding, Overloaded Array Processing and Multi-User Detection. Per-Survivor Processing (PSP) is a technique for approximating MLSE for unknown channels by embedding channel estimation into the structure of the Viterbi Algorithm (VA). In the case of successful acquisition, the convergence rate of PSP is comparable to that of the pilot-aided RLS algorithm. However, the performance of PSP degrades when certain sequences are transmitted. In this thesis, the blind acquisition characteristics of PSP are discussed. The problematic sequences for any joint ML data and channel estimator are discussed from an analytic perspective. Based on the theory of indistinguishable sequences, modifications to conventional PSP are suggested that improve its acquisition performance significantly. The effect of tree search and list-based algorithms on PSP is also discussed. Proposed improvement techniques are compared for different channels. For higher order channels, complexity issues dominate the choice of algorithms, so PSP with state reduction techniques is considered. Typical misacquisition conditions, transients, and initialization issues are reported.
BSML: A Binding Schema Markup Language for Data Interchange in Problem Solving Environments
Verstak, Alex; Ramakrishnan, Naren; Watson, Layne T.; He, Jian; Shaffer, Clifford A.; Bae, Kyung Kyoon; Jiang, Jing; Tranter, William H.; Rappaport, Theodore S. (Hindawi, 2003-01-01)
We describe a binding schema markup language (BSML) for describing data interchange between scientific codes. Such a facility is an important constituent of scientific problem solving environments (PSEs). BSML is designed to integrate with a PSE or application composition system that views model specification and execution as a problem of managing semistructured data. The data interchange problem is addressed by three techniques for processing semistructured data: validation, binding, and conversion. We present BSML and describe its application to a PSE for wireless communications system design.
Capacity-approaching data transmission in MIMO broadcast channels
Jiang, Jing (Virginia Tech, 2004-06-30)
This dissertation focuses on downlink multi-antenna transmission with packet scheduling in a wireless packet data network. The topic is viewed as a critical system design problem for future high-speed packet networks requiring extremely high spectral efficiency. Our aim is to illustrate the interaction between transmission schemes at the physical layer and scheduling algorithms at the medium access control (MAC) layer from a sum-capacity perspective. Various roles of multiple antennas are studied under channel-aware scheduling, including diversity, beamforming and spatial multiplexing. At a system performance level, our work shows that downlink throughput can be optimized by joint precoding across multiple transmit antennas and exploiting small-scale fading of distributed multiple input and multiple output (MIMO) channels. There are three major results in this dissertation. First, it is shown that over a MIMO Gaussian broadcast channel, and under channel-aware scheduling, open-loop transmit antenna diversity actually reduces the achievable sum rate. This reveals a negative interaction between open-loop antenna diversity and the closed-loop multiuser diversity through scheduling. Second, a suboptimal dirty paper coding (DPC) approach benefits greatly from multiuser diversity by an efficient packet scheduling algorithm. Performance analysis of a suboptimal greedy scheduling algorithm indicates that, compared with the receiver-centric V-BLAST method, it can achieve a much larger scheduling gain over a distributed MIMO channel. Further, pre-interference cancellation allows for transmissions free of error propagation. A practical solution, termed Tomlinson-Harashima precoding (THP), is studied under this suboptimal scheduling algorithm. Similar to V-BLAST, a reordering is applied to minimize the average error rate, which introduces only a negligible sum-rate loss in the scenarios investigated. Third, for an orthogonal frequency division multiplexing (OFDM) system using MIMO precoding, it is shown that a DPC-based approach is readily applicable and can be easily generalized to reduce the peak-to-average power ratio (PAR) up to 5 dB without affecting the receiver design. Simulations show that in an interference-limited multi-cell scenario, greater performance improvement can be achieved by interference avoidance through adaptive packet scheduling, rather than by interference diversity or averaging alone. These findings suggest that, coordinated with channel-aware scheduling, adaptive multiplexing in both spatial and frequency domains provides an attractive downlink solution from a total capacity point of view.
Cellular diagnostic systems using hidden Markov models
Mohammad, Maruf H. (Virginia Tech, 2006-10-19)
Radio frequency system optimization and troubleshooting remains one of the most challenging aspects of working in a cellular network. To stay competitive, cellular providers continually monitor the performance of their networks and use this information to determine where to improve or expand services. As a result, operators are saddled with the task of wading through overwhelmingly large amounts of data in order to trouble-shoot system problems. Part of the difficulty of this task is that for many complicated problems such as hand-off failure, clues about the cause of the failure are hidden deep within the statistics of underlying dynamic physical phenomena like fading, shadowing, and interference. In this research we propose that Hidden Markov Models (HMMs) be used as a method to infer signature statistics about the nature and sources of faults in a cellular system by fitting models to various time-series data measured throughout the network. By including HMMs in the network management tool, a provider can explore the statistical relationships between channel dynamics endemic to a cell and its resulting performance. This research effort also includes a new distance measure between a pair of HMMs that approximates the Kullback-Leibler divergence (KLD). Since there is no closed-form solution to calculate the KLD between the HMMs, the proposed analytical expression is very useful in classification and identification problems. A novel HMM based position location technique has been introduced that may be very useful for applications involving cognitive radios.
Characterization of Ultra Wideband Communication Channels
Muqaibel, Ali Hussein (Virginia Tech, 2003-03-05)
Ultra-wideband (UWB) communication has been the subject of extensive research in recent years due to its unique capabilities and potential applications, particularly in short-range multiple access wireless communications. However, many important aspects of UWB-based communication systems have not yet been thoroughly investigated. The propagation of UWB signals in indoor environments is the single most important issue with significant impacts on the future direction, scope, and generally the extent of the success of UWB technology. The objective of this dissertation is to obtain a more thorough and comprehensive understanding of the potentials of UWB technology by characterizing the UWB communication channels. Channel characterization refers to extracting the channel parameters from measured data. The extracted parameters are used to quantify the effect of the channel on communication UWB systems using this channel as signal transmission medium. Data are measured in different ways using a variety of time-domain and frequency-domain techniques. The experimental setups used in channel characterization effort also include pulse generators and antennas as integral parts of the channel, since the pulse shape and antenna characteristics have significant impact on channel parameters. At a fundamental level, the propagation of UWB signals, as any electromagnetic wave, is governed, among other things, by the properties of materials in the propagation medium. One of the objectives of this research is to examine propagation through walls made of typical building materials and thereby acquire ultra-wideband characterization of these materials. The loss and the dielectric constant of each material are measured over a frequency range of 1 to 15 GHz. Ten commonly used building materials are chosen for this investigation. These include, dry wall, wallboard, structure wood, glass sheet, bricks, concrete blocks, reinforced concrete (as pillar), cloth office partition, wooden door, and styrofoam slab. The work on ultra-wideband characterization of building materials resulted in an additional interesting contribution. A new formulation for evaluating the complex dielectric constant of low-loss materials, which involves solving real equations and thus requiring only one-dimensional root searching techniques, was found. The results derived from the exact complex equation and from the new formulation are in excellent agreement. Following the characterization of building materials, an indoor UWB measurement campaign is undertaken. Typical indoor scenarios, including line-of-sight (LOS), non-line-of-sight (NLOS), room-to-room, within-the-room, and hallways, are considered. Results for indoor propagation measurements are presented for local power delay profiles (local-PDP) and small-scale averaged power delay profiles (SSA-PDP). Site-specific trends and general observations are discussed. The results for pathloss exponent and time dispersion parameters are presented. The analyses results indicate the immunity of UWB signals to multipath fading. The results also clearly show that UWB signals, unlike narrowband signals, do not suffer from small scale fading, unless the receiver is too close to walls. Multipath components are further studies by employing a deconvolution technique. The application of deconvolution results in resolving multipath components with waveforms different from those of the sounding pulse. Resolving more components can improve the design of the rake receiver. The final part of this research elaborates on the nature of multiple access interference and illustrates the application of multi-user detection to improve the performance of impulse radio systems. Measured dispersion parameters and their effects on the multiple access parameters are discussed.
Characterization of Uplink Transmit Power and Talk Time in WCDMA Networks
Bhupathi Raju, Arjun (Virginia Tech, 2008-07-15)
As 3G handset manufacturers add more and more features such as multimedia applications, color displays, video cameras, web browsing, gaming, WLAN, and MP3 players, the current consumption of a handset is ever increasing. Of the many components, the RF power amplifiers receive the most attention as they draw significant battery current and continue to represent the largest power load on the battery. In order to improve the overall efficiency of a power amplifier, it is important to know the operating uplink transmit power levels of a mobile phone in the WCDMA network. The work in this thesis makes two major contributions. First is the characterization of uplink transmit power in WCDMA networks based on current network data (collected in AT&T's WCDMA network) and realistic usage scenarios. Second is an investigation of the relationship between the battery life and the probability distribution function of the transmit power. Another important finding is that the talk time estimates using field tests, lab testing and theoretical expressions all give results to within 5%. Based on these data, design goals for WCDMA power amplifiers (in order to improve the talk times significantly) are suggested. The output power levels where the PA efficiencies have to be improved in order to significantly increase the battery life of WCDMA handsets are presented.
Concatenation of Space-Time Block Codes with ConvolutionalCodes
Ali, Saajed (Virginia Tech, 2004-02-12)
Multiple antennas help in combating the destructive effects of fading as well as improve the spectral efficiency of a communication system. Receive diversity techniques like maximal ratio receive combining have been popular means of introducing multiple antennas into communication systems. Space-time block codes present a way of introducing transmit diversity into the communication system with similar complexity and performance as maximal ratio receive combining. In this thesis we study the performance of space-time block codes in Rayleigh fading channel. In particular, the quasi-static assumption on the fading channel is removed to study how the space-time block coded system behaves in fast fading. In this context, the complexity versus performance trade-off for a space-time block coded receiver is studied. As a means to improve the performance of space-time block coded systems concatenation by convolutional codes is introduced. The improvement in the diversity order by the introduction of convolutional codes into the space-time block coded system is discussed. A general analytic expression for the error performance of a space-time block coded system is derived. This expression is utilized to obtain general expressions for the error performance of convolutionally concatenated space-time block coded systems utilizing both hard and soft decision decoding. Simulation results are presented and are compared with the analytical results.
CPM Equalization to Compensate for ISI due to Band Limiting Channels
Moctezuma, Andres (Virginia Tech, 2006-08-04)
In modern wireless communication systems, such as satellite communications and wireless networks, the need for higher data rates without the need for additional transmit power has made Continuous Phase Modulation (CPM) one of the most attractive modulation schemes in band limited channels. However, as the data rates keep increasing, the spectral width of the CPM signal increases beyond the channel bandwidth and performance becomes constrained by the intersymbol interference (ISI) that results from band-limiting filters. We propose two approaches to the problem of equalization of band-limited CPM signals. First, our efforts are focused on shortening the channel impulse response so that we can use a low complexity MLSE equalizer. We implement the channel truncation structure by Falconer and Magee and adapt it to work with CPM signals. This structure uses a, a more derivable, pre-filter to shape the overall response of the channel, so that its impulse response is of shorter duration. Simulation results show that near-MLSE performance can be obtained while dramatically reducing MLSE equalizer complexity. In our second approach, we focus on eliminating the group-delay variations inside the channel passband using an FIR pre-filter. We assume the channel to be time-invariant and provide a method to design an FIR filter so that -when convolved with the band limiting filter - it results in more constant group-delay over the filter passband. Results show that eliminating the group-delay variations in the band limiting filter passband reduce the amount of ISI and improve bit error rate performance.
Cross-Layer Optimization: System Design and Simulation Methodologies
Mahajan, Rahul (Virginia Tech, 2006-11-21)
An important aspect of wireless networks is their dynamic behavior. The conventional protocol stack is inflexible as various protocol layers communicate in a strict manner. In such a case the layers are designed to operate under the worst conditions as opposed to adapting to changing conditions. This leads to inefficient use of spectrum and energy. Adaptation represents the ability of network protocols and applications to observe and respond to channel conditions. Traditional simulation methodologies independently model the physical and higher layers. When multiple layer simulations are required, an abstraction of one layer is inserted into the other to provide the multiple layer simulation. However, recent advances in wireless communication technologies, such as adaptive modulation and adaptive antenna algorithms, demand a cross layer perspective to this problem in order to provide a sufficient level of fidelity. However, a full simulation of both layers often results in excessively burdensome simulation run-times. The benefits and possible parametric characterization issues arising due to the cross-layer integration of lower physical and higher network layers are investigated in this thesis. The primary objective of investigating cross-layer simulation techniques is to increase the fidelity of cross-layer network simulations while minimizing the simulation runtime penalties. As a study of cross-layer system design a medium access control (MAC) scheme is studied for a MANET wherein the nodes are equipped with smart antennas. Traditional MAC protocols assume the use of omnidirectional antennas. Nodes with directional antennas are capable of transmitting in certain directions only and significantly reduce the chances of collision and increase the effective network capacity. MANETs using omni-directional antennas severely limit system performance as the entire space around a node up to its radio range is seen as a single logical channel. In this research a MAC protocol is studied that exploits space division multiple access at the physical layer. This is a strong example where physical and MAC design must be carried out simultaneously for adequate system performance. Power control is a very important in the design of cellular CDMA systems which suffer from the near-far problem. Finally, the interaction between successive interference cancellation (SIC) receivers at the physical layer and power control, which is a layer 2 radio resource management issue, is studied. Traffic for future wireless networks is expected to be a mix of real-time traffic such as voice, multimedia teleconferencing, and games and data traffic such as web browsing, messaging, etc. All these applications will require very diverse quality of service guarantees. A power control algorithm is studied, which drives the average received powers to those required, based on the QoS requirements of the individual users for a cellular CDMA system using SIC receivers.
Data and Computation Modeling for Scientific Problem Solving Environments
Verstak, Alexandre (Virginia Tech, 2002-08-15)
This thesis investigates several issues in data and computation modeling for scientific problem solving environments (PSEs). A PSE is viewed as a software system that provides (i) a library of simulation components, (ii) experiment management, (iii) reasoning about simulations and data, and (iv) problem solving abstractions. Three specific ideas, in functionalities (ii)-(iv), form the contributions of this thesis. These include the EMDAG system for experiment management, the BSML markup language for data interchange, and the use of data mining for conducting non-trivial parameter studies. This work emphasizes data modeling and management, two important aspects that have been largely neglected in modern PSE research. All studies are performed in the context of S4W, a sophisticated PSE for wireless system design.

Browsing by Author "Tranter, William H."

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