Browsing by Author "Hamid Krim, Committee Member"

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Antenna Selection and Space-Time Spreading Methods for Multiple-Antenna Systems
(2005-01-05) Sudarshan, Pallav; Jack Silverstein, Committee Member; Alexandra Duel-Hallen, Committee Member; Brian Hughes, Committee Chair; Hamid Krim, Committee Member
The use of multiple antennas at the transmitter and receiver can significantly improve the performance of a wireless communication system. In recent years, there has been a lot of interest in deriving efficient receiver architectures and designing signalling and coding schemes that maximize the performance gains of a multi-antenna system. In this dissertation, we focus on two such issues: space-time spreading methods at the transmitter, and antenna selection techniques at the receiver. For a synchronous code-division multiple-access (CDMA) system that employs multiple transmit antennas, we characterize the asymptotic spectral efficiency in terms of the number of users, processing gain, signal to noise ratio (SNR), array size, etc. Using this formula, we design the linear space-time spreading methods that maximize the spectral efficiency. The strategy for optimal spreading sequence allocation across antennas, and across users is also addressed. We show that the system capacity per chip is maximized when each user employs all the spreading sequences allocated to it on each transmit antenna. We then study reduced complexity receiver designs for multiple-antenna systems. A RF pre-processing architecture, that processes the received signal at carrier frequency, followed by selection, and down-conversion is considered. Recent results show that this architecture can outperform conventional antenna selection with the same number of RF chains. We derive the optimum RF pre-processing that is based only on the large-scale parameters of the channel. For a correlated channel, we show that RF pre-processing using channel statistics gives good results, and that instantaneous channel knowledge is not required for pre-processing. A beam pattern based geometric intuition is also developed to justify the performance gains. To accommodate the practical design constraints imposed by current variable phase-shifter technology, a sub-optimal phase approximation is also introduced. We show that this scheme is extremely robust to RF imperfections, such as phase and quantization errors. The impact of imperfect channel estimates on the performance of RF pre-processing is also studied, and the scheme is shown to be robust to channel estimate imperfections, as well. Finally, we focus on antenna selection for multi-access channels. For a multi-user system, we derive the statistics-based selection criteria that maximizes tight bounds on ergodic capacity. Two different receiver architectures are considered, and the performance gain compared to sub-optimal selection is quantified.
Asymptotic Analysis of Large Antenna Arrays for Communications and Radar Applications
(2006-03-28) Kamath, Ajith Mulki; Brian L.Hughes, Committee Chair; Hamid Krim, Committee Member; Jack W. Silverstein, Committee Member; Alexandra Duel-Hallen, Committee Member
In recent years there has been a growing interest in using antenna arrays at both ends of a wireless communication link. Such multiple input multiple output (MIMO) systems are beneficial both in terms of providing greatly improved data rates, as well as in terms of robustness in combating errors compared to systems which use only one antenna. These benefits are obtained without requiring extra transmit power or spectral bandwidth, but come at the cost of additional processing power. In radar, multiple antenna arrays have been in use for several decades. Even so, the idea of measuring the full received electro-magnetic (EM) wave for parameter estimation has been a recent one. In this dissertation, we address two issues through asymptotics: in MIMO systems, we develop insights into finite MIMO array performance by deriving precise results for asymptotically large MIMO arrays, and in radar we derive the gain from measuring the complete field over a spherical surface versus measuring only one polarization component using an equal number of sensors. First, we consider the distribution of the mutual information of a MIMO system with an uncorrelated Rayleigh fading channel. We show that, as the transmit and receive array sizes tend to infinity while maintaining their ratio constant, the mutual information distribution tends to Gaussian distribution at all signal to noise ratios (SNRs), and give a closed-form expression for its mean and variance. Through simulations, we observe that the mutual information distribution of a finite MIMO system with as few as 4 array elements at either end has a variance which depends only on the ratio of the two arrays and is also closely approximated by the asymptotic distribution variance. We show that the mean of the distribution can also be approximated much closer than previously shown, and hence combined with the asymptotic variance, this yields close approximations for outage capacities. We next consider the problem of determining the best possible tradeoff between diversity and multiplexing gains in an uncorrelated Rayleigh fading channel. Zheng and Tse have characterized this tradeoff in the large signal to noise ratio(SNR) limit. We apply our asymptotic results on mutual information to compute the finite SNR diversity-multiplexing tradeoffs at high outage probabilities in the range of practical interest. We show that the asymptotic results match the tradeoffs derived by Zheng and Tse only in the equal antenna MIMO array case. We then propose a linear dispersion coding scheme which modulates a block of data by picking a random unitary matrix, which was previously shown to produce full-rank full-diversity code-books with probability one. Through simulations using rectangular code-books, we show that these may also achieve the full Zheng-Tse diversity multiplexing tradeoff after using a maximum likelihood (ML) decoder. Having developed fundamental insights into MIMO arrays through the use of asymptotic analysis, we consider the impact of using vector antennas in large radar arrays. Specifically, we compare the performance of range and direction-of-arrival (DOA) estimation of a single source using an array of vector electro-magnetic (EM) sensors packed densely on the surface of a sphere, with a similarly shaped array with identically oriented dipole elements. We compute the Cramer-Rao lower bound on maximum-likelihood range and DOA estimation using either array. By taking the ratio of the confidence volumes as the gain, we compare the vector array estimate with the uni-polarized array as a function of target location.
Bayesian Based Structural Health Management and An Uncertainty Analysis Technique Utilizing Support Vector Machine
(2007-09-13) Cao, Yingfang; Fuh-Gwo Yuan, Committee Member; Mohammad N. Noori, Committee Chair; Hamid Krim, Committee Member; Gregory D. Buckner, Committee Member
Characterization of Propagation on Wires Over Lossy Earth
(2006-04-28) Buff, Peter Marcus; Michael B. Steer, Committee Chair; Douglas Barlage, Committee Member; Gianluca Lazzi, Committee Member; Hamid Krim, Committee Member
The propagation of electromagnetic energy on a wire located above lossy earth is experimentally characterized for the first time. New microwave de-embedding techniques are developed specifically for measurement environments with unknown lossy substrate properties. The novel Through–Match (TM) de-embedding technique developed here is used to de-embed the S-parameters of a line over earth and the results compared to the results produced from the well-known Through–Reflect–Match (TRM) technique. Although TRM is an established method for making microwave measurements, the technique is rederived here to facilitate the development of the new TM technique. Techniques and methodologies for the error analysis of de-embedding calibration methods are introduced. These techniques are valid for methods that use fixtures in the measurements with the assumption that the fixtures can be faithfully reproduced. The well-known Through–Reflect–Line (TRL) technique has errors known as λ/2 errors associated with the differential length of the line standard and through standard and are seemingly unpredictable in nature and extent. The origin of the errors is identified as small errors in the repeatability of the fixtures. To address the issue of outdoor measurements and the mesocopic nature of soil as an unstable and unpredictable medium, a soil surrogate was developed and modeled using a dielectric composite made from gelatin, High Fructose Corn Syrup (HFCS), water and NaCl. The composite is developed with relative permittivity ranging from 8 to 75 with selectable conductive and dielectric losses. The composite comprises gelatin, High Fructose Corn Syrup (HFCS), NaCl and water, and can be used to model soils, loams and sands in the 200 MHz to 20 GHz range. Frequency-dependent electrical characteristics resulting from the mesoscopic nature of soils is captured by the surrogate. The soil surrogate is suited to a laboratory environment providing a medium for repeatable measurements. The TM, TRM and TRL measurement methods are used and compared from 100 to 300 MHz for a single conductor lying on the air/composite interface.
Characterization of Various Antenna Structures Used For Device Illumination
(2004-06-02) Buff, Peter Marcus; Hamid Krim, Committee Member; Michael Steer, Committee Chair; Doug Barlage, Committee Member
A non-intrusive approach for personal surveillance is explored. A potential strategy for identification of electronic devices using electromagnetic illumination with the aim of identifying unique resonances and signatures is presented. The concept is that signatures can be compared to a known signature for a particular device. If discrepancies are detected, then the device may be flagged as a suspect item. Various antenna structures are analyzed to determine the ideal antenna characteristics needed for electromagnetic illumination. A double ridged horn antenna is designed, characterized and compared to a conical spiral right hand circular polarized antenna and a standard gain antenna. Various passive structures and electronic devices are illuminated with electromagnetic energy and responses analyzed.
Distributed and Collaborative Processing in Wireless Sensor Networks
(2007-08-21) Li, Wenjun; Huaiyu Dai, Committee Chair; Brian Hughes, Committee Member; Alexandra Duel-Hallen, Committee Member; Hamid Krim, Committee Member; Hien Tran, Committee Member
AN Efficient Transcutaneous Power LInk Desing To Be Used in Retinal Prosthesis
(2003-06-04) Kendir, Gurhan Alper; Gianluca Lazzi, Committee Member; Hamid Krim, Committee Member; Wentai Liu, Committee Chair
Design of the radio-frequency power links to be used in prosthetic body implanted systems is important. In this study, we present a novel design procedure for the coil design considering both the efficiency of the system and the radiated magnetic field. Closed loop class-E driver design for low-Q networks is also presented along with the coil design. Main specifications used in the design procedure are dimensions of the coils, distance between them, frequency of operation, load power, load voltage and the maximum available input DC voltage. Experimental results showed an overall power link efficiency of 65% delivering 250mW power to a 16V DC load from an optimal distance of 7mm.
A Framework for Object Characterization and Matching in Multi--and Hyperspectral Imaging Systems
(2003-08-14) Ramanath, Rajeev; Charles E. Smith, Committee Member; Wesley E. Snyder, Committee Chair; Griff L. Bilbro, Committee Member; Hamid Krim, Committee Member; Siamak Khorram, Committee Member
The idea of shape has been a field of scientific study since the time of Galileo. Most shapes that have been studied until now have been those that are 'conceivable' by the human mind. This has restricted the study of shape by the image processing community to the visible range of the spectrum (an otherwise very small range). Perception of shape in the realm of the spectrum outside of the visible range has not received much attention. However with the recent advancement in imaging systems (multi--and hyperspectral) that can capture images over a wide spectral range, it is only natural to expect this field to receive notice by the imaging community. In this work, the idea of 'shape' in the multi--and hyperspectral imaging scenarios is studied and its paradigms explored. Notions of the hyperspectral cube are borrowed from the remote sensing community as a means of representation of this high dimensional data. In this work, edges of two types are used, one that makes use of the vector valued data in the image and another that treats each spectral band individually. The edge-sets are used to extract spatio-spectral shape signatures of objects which are in turn used for extracting canonical views of objects and also to perform classification using three dimensionality reduction techniques, Principal Component Analysis, Independent Component Analysis and Non-negative Matrix Factorization. As an extension to edge-based decompositions, we also use view-based techniques for classification. The results obtained by using a combination of spatial and spectral information are compared with those resulting from conventional single-band techniques, showing considerable improvement. Issues regarding noisy data have been addressed using two approaches -- increasing the dimensionality of the eigensystem and estimating the new eigensystem under noisy conditions using approximations of results using perturbation theory. The former approach gives a measure of the number of basis vectors that need to be included additionally based upon the strength of the noise. It develops a system that adds dimensions (Noise Equivalent Dimensions) to the original eigensystem that compensates for the energy contributed by the noise. The latter approach determines the manner in which the eigenviews of an eigensystem change in the presence of noise by using first-order approximations from perturbation theory. Both approaches are compared using reconstruction error in the original and noisy data.
Fundamental Limits and Joint Design of Wireless Systems with Vector Antennas
(2005-08-31) Krishnamurthy, Sandeep Humchadakatte; Gianluca Lazzi, Committee Member; Hamid Krim, Committee Member; Moody Chu, Committee Member; Brian L. Hughes, Committee Chair
Multiple-antenna systems have generated tremendous research interest in the recent past mainly because of their promise of significant gains in capacity and performance as compared to single-antenna systems. Most work on multiple antennas has focused on the design of coding and modulation schemes, channel estimation algorithms and decoding architectures. Information is sent by the transmitter as electromagnetic (EM) waves which subsequently undergo multipath fading before they reach the receiver. The EM properties of the antennas and the nature of the scattering environment jointly impact the performance of communication algorithms. However, there are relatively few works in the literature that consider this interrelation in the design of transmitter-receiver architectures. In this dissertation we study three such problems: the dependence of capacity on the EM properties of antennas and the scattering environment, the limits on performance of parameter estimation algorithms at the receiver and finally, the fundamental limits on the capacity that volume-limited multiple-antenna systems can achieve. We first consider the joint design of multi-element antennas and capacity-optimal signalling for a multiple-input multiple-output (MIMO) wireless channel. We use EM theory and ray-tracing methods to derive a channel propagation model for antennas that can detect or excite more than one component of the electric field vector (known as vector antennas) in a discrete-multipath channel environment. This model provides insights into the inter-relation between the spatial multiplexing gain and the nature of the multipath environment for vector antennas. We then generalize this model to the case of antennas with more general electric-field patterns in a fading environment with clusters of scatterers. Capacity-optimal signalling and the impact of antenna electric field patterns on capacity are studied. We focus on joint antenna-signal design and derive optimality criterion for multi-element antenna systems for maximizing the ergodic capacity. We show that antennas that have orthogonal and equal norm electric-field patterns maximize the ergodic capacity. Vector antennas satisfy this criteria, but a uniform linear array does not. We next consider the problem of positioning and direction-of-arrival (DOA) estimation with ultrawideband (UWB) vector antennas. Due to the wideband nature of the antenna response and directional sensitivity of vector antennas, precise ranging and DOA estimation of a transmitting source can be jointly performed. We first derive a frequency-domain Cramer-Rao Bound formula in the asymptotic case of a large number of observation samples in stationary noise. We apply this formula to two UWB vector antennas and obtain closed-form lower-bound expressions for the ranging and DOA error covariances. A criterion based on the linearized confidence region is used to design signal pulses that give uniform resolving capability to the antennas for any DOA. Finally, we consider the fundamental capacity limits that a multi-element antenna system that is restricted to occupy a finite volume can achieve. For simplicity, we consider the problem of a spherical volume current source radiating into space with a receiver in the far-field capable of detecting the electric field on a concentric spherical surface. The system is first described as a linear operator, and the exact singular values of the system are derived in closed form. The singular values and hence the capacity is shown to depend on the transmitter volume only through its radius. We calculate the capacity of such a system, and provide capacity formulas that are accurate at high signal-to-noise ratio.
Gain Scheduling for Networked Control System
(2003-12-02) Tipsuwan, Yodyium; Griff L. Bilbro, Committee Member; Mo-Yuen Chow, Committee Chair; Hamid Krim, Committee Member; Douglas S. Reeves, Committee Member
Performances of closed-loop control systems operated over a data network are typically degraded by network-induced delays. Furthermore, the closed-loop control systems can become unstable. The purpose of this research has been to develop a control methodology to handle network-induced delay effects using optimal gain scheduling on existing controllers. The proposed gain scheduling technique adapts controller gains externally by modifying a controller output to enable the controller for uses over a data network. Since existing controllers can still be utilized, the proposed methodology can reduce control system reinstallation and replacement costs. First, the effectiveness of the proposed gain scheduling technique on networked DC motor speed control using a PI (Proportional-Integral) controller is investigated. Also, the concept of network traffic condition measurement to select optimal controller gains is presented. Then, a middleware framework to measure network traffic conditions on an IP network based on delays and delay variations and to modify controller gains is described. Suggestion of using neural network in the gain scheduling scheme is also given. Finally, the gain scheduling technique with the middleware framework is then extended to mobile robot path-tracking control.
Improving ANN Generalization via Self-Organized Flocking in conjunction with Multitasked Backpropagation
(2003-04-14) Potter, Matthew James; James Selgrade, Committee Member; Hamid Krim, Committee Member; Mark White, Committee Chair
The purpose of this research has been to develop methods of improving the generalization capabilities of artificial neural networks. Tools for examining the influence of individual training set patterns on the learning abilities of individual neurons are put forth and utilized in the implementation of new network learning algorithms. Algorithms are based largely on the supervised training algorithm: backpropagation, and all experiments use the standard backpropagation algorithm for comparison of results. The focus of the new learning algorithms revolve around the addition of two main components. The first addition is that of an unsupervised learning algorithm called flocking. Flocking attempts to provide network hyperplane divisions that are evenly influenced by examples on either side of the hyperplane. The second addition is that of a multi-tasking approach called convergence training. Convergence training uses the information provided by a clustering algorithm in order to create subtasks that represent the divisions between clusters. These subtasks are then trained in unison in order to promote hyperplane sharing within the problem space. Generalization was improved in most cases and the solutions produced by the new learning algorithms are demonstrated to be very robust against different random weight initializations. This research is not only a search for better generalizing ANN learning algorithms, but also a search for better understanding when dealing with the complexities involved in ANN generalization.
Investigation of Transmission, Propagation, and Detection of UWB Pulses Using Physical Modeling
(2007-08-22) Ma, Li; Brian L. Hughes, Committee Member; Alexandra Duel-Hallen, Committee Chair; Arne A Nilsson, Committee Member; Hans Hallen, Committee Co-Chair; Hamid Krim, Committee Member
Performance Analysis of Reliable Adaptive Transmission for Mobile Radio Slow Frequency Hopping Channels Aided by Long Range Prediction
(2004-11-05) Lei, Ming; Brian L. Hughes, Committee Member; Mo-Yun Chow, Committee Member; Hamid Krim, Committee Member; Hans Hallen, Committee Member; Alexandra Duel-Hallen, Committee Chair
Due to correlated fading in frequency hopping (FH) wireless communication systems, it is possible to predict the future channel state information (CSI) for one frequency based on the channel observations of other frequencies. As a result, the performance of slow FH systems can be improved by utilizing adaptive transmission techniques. We propose the optimal Minimum Mean Square Error (MMSE) Long Range Prediction algorithm for slow FH systems that employ coherent detection. A recursive autocorrelation update method and a simplified prediction algorithm are explored to reduce the complexity. Statistical model of the prediction accuracy is developed and used in the design of the reliable adaptive transmission systems. We investigate the performance of adaptive transmission for high-speed data transmission in SFH systems based on the proposed Long Range Prediction algorithms. For slow frequency hopping communications in the presence of partial-band interference, we propose to employ adaptive transmitter frequency diversity and adaptive modulation to mitigate the effects of partial-band interference and fading. Both standard Jakes model and realistic physical model are used to test the performance. Analysis and simulation results show that significant performance gains can be achieved relative to non-adaptive methods.
Shape Recovery from Brightness Images of 2-Dimensional Specular Reflectors
(2003-12-18) Pathak, Chetna; Wesley Snyder, Committee Chair; Hamid Krim, Committee Member; Griff Bilbro, Committee Member
This thesis proposes two methods to reconstruct the shape of 2-dimensional specular reflectors from multiple brightness images of the reflectors. Several images of a reflector are taken as the camera and a mounted light source move along the x-axis. From the specularities present in the images, reflectance information and camera locations are extracted. This information is used for reconstruction. The first method is an optimization algorithm that determines the surface shape by minimizing an objective function. The second method employs relaxation labeling. Reflector points are declared labels while the camera positions are considered objects. Object-label associations are investigated and the most consistent among these are retained to give the reflector shape.