Optimal pilot waveform assisted modulation for ultrawideband communications

Ultrawideband (UWB) transmissions induce pronounced frequency-selective fading effects in their multipath propagation. Multipath diversity gains can be collected to enhance performance, provided that the underlying channel can be estimated at the receiver. To this end, we develop a novel pilot waveform assisted modulation (PWAM) scheme that is tailored for UWB communications. We select our PWAM parameters by jointly optimizing channel estimation performance and information rate. The resulting transmitter design maximizes the average capacity, which is shown to be equivalent to minimizing the mean-square channel estimation error, and thereby achieves the Crame/spl acute/r-Rao lower bound. Application of PWAM to practical UWB systems is promising because it entails simple integrate-and-dump operations at the frame rate. Equally important, it offers a flexible UWB channel estimator, capable of striking desirable rate-performance tradeoffs depending on the channel coherence time.     

Object and texture classification using higher order statistics

The problem of the detection and classification of deterministic objects and random textures in a noisy scene is discussed. An energy detector is developed in the cumulant domain by exploiting the noise insensitivity of higher order statistics. An efficient implementation of this detector is described, using matched filtering. Its performance is analyzed using asymptotic distributions in a binary hypothesis-testing framework. The object and texture discriminant functions are minimum distance classifiers in the cumulant domain and can be efficiently implemented using a bank of matched filters. They are immune to additive Gaussian noise and insensitive to object shifts. Important extensions, which can handle object rotation and scaling, are also discussed. An alternative texture classifier is derived from a ML viewpoint and is statistically efficient at the expense of complexity. The application of these algorithms to the texture-modeling problem is indicated, and consistent parameter estimates are obtained     

Joint coding-precoding with low-complexity turbo-decoding

We combine error-control coding with linear precoding (LP) for flat-fading channels, as well as for wireless orthogonal frequency-division multiplexing transmissions through frequency-selective fading channels. The performance is analyzed and compared with the corresponding error-control-coded system without precoding. By wedding LP with conventional error-control coding, the diversity order becomes equal to the error-control code's minimum Hamming distance times the precoder size. We also derive a low-complexity turbo-decoding algorithm for joint coded-precoded transmissions. We analyze the decoding complexity and compare it with an error-control-coded system without LP. Extensive simulations with convolutional and turbo codes for HiperLan/2 channels support the analysis and demonstrate superior performance of the proposed system.     

Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks

UWB technology provides an excellent means for wireless positioning due to its high resolution capability in the time domain. Its ability to resolve multipath components makes it possible to obtain accurate location estimates without the need for complex estimation algorithms. In this article, theoretical limits for TOA estimation and TOA-based location estimation for UWB systems have been considered. Due to the complexity of the optimal schemes, suboptimal but practical alternatives have been emphasized. Performance limits for hybrid TOA/SS and TDOA/SS schemes have also been considered. Although the fundamental mechanisms for localization, including AOA-, TOA-, TDOA-, and SS-based methods, apply to all radio air interface, some positioning techniques are favored by UWB-based systems using ultrawide bandwidths.     

Higher-order statistics-based input/output system identification and application to noise cancellation

Higher-than-second-order statistics-based input/output identification algorithms are proposed for linear and nonlinear system identification. The higher-than-second-order cumulant-based linear identification algorithm is shown to be insensitive to contamination of the input data by a general class of noise including additive Gaussian noise of unknown covariance, unlike its second-order counterpart. The nonlinear identification is at least as optimal as any linear identification scheme. Recursive-least-squares-type algorithms are derived for linear/nonlinear adaptive identification. As applications, the problems of adaptive noise cancellation and time-delay estimation are discussed and simulated. Consistency of the adaptive estimator is shown. Simulations are performed and compared with the second-order design.Part of the results of this paper were presented at the workshop on HOSA, Vail, CO, June 1989, and at the International Conference on ASSP, Albuquerque, NM, April 1990. The work of G. B. Giannakis in this paper was supported by LabCom Contract 5-25254.     

Image modeling using inverse filtering criteria with application totextures

Statistical approaches to image modeling have largely relied upon random models that characterize the 2-D process in terms of its first- and second-order statistics, and therefore cannot completely capture phase properties of random fields that are non-Gaussian. This constrains the parameters of noncausal image models to be symmetric and, therefore, the underlying random field to be spatially reversible. Research indicates that this assumption may not be always valid for texture images. In this paper, higher- than second-order statistics are used to derive and implement two classes of inverse filtering criteria for parameter estimation of asymmetric noncausal autoregressive moving-average (ARMA) image models with known orders. Contrary to existing approaches, FIR inverse filters are employed and image models with zeros on the unit bicircle can be handled. One of the criteria defines the smallest set of cumulant lags necessary for identifiability of these models to date, Consistency of these estimators is established, and their performance is evaluated with Monte Carlo simulations as well as texture classification and synthesis experiments.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.     

Crossband Flexible UWB Multiple Access for High-Rate Multipiconet WPANs

Emerging indoor technologies including wireless multimedia and personal area networks (WPANs) entail high-rate systems capable of supporting multiple users (piconets) with variable rates. These requirements motivate the design of multiband (MB) ultra-wideband (UWB) radios for their simplicity in handling pronounced frequency selectivity, agility in coping with interference, scalability in providing multirate operation, and their potentially low cost. Relative to baseband UWB radios, MB-UWB systems have gained popularity in the IEEE standards for short-range wireless links. However, multiple-access (MA) schemes must be designed carefully to harness the diversity benefits provided by the MB-UWB propagation, in a spectrally efficient manner. To this end, we introduce a crossband flexible UWB MA scheme for multipiconet WPANs. The resultant design that we term FLEX-UWB offers resilience to multiuser interference, can conveniently accommodate various spreading alternatives, enables full multipath diversity, and can effect scalable spectral efficiency (from low to medium and high data rates). Simulations confirm the merits of FLEX-UWB radios in comparison with various alternatives     

Deterministic Time-Varying Packet Fair Queueing for Integrated Services Networks

In integrated services networks, the provision of Quality of Service (QoS) guarantees depends critically upon the scheduling algorithm employed at the network layer. In this work we review fundamental results on scheduling, and we focus on Packet Fair Queueing (PFQ) algorithms, which have been proposed for QoS wireline-wireless networking. The basic notion in PFQ is that the bandwidth allocated to a session is proportional to a positive weight _i . Because of the fixed weight assignment, the inherent in PFQ delay-bandwidth coupling imposes limitations on the range of QoS that can be supported. We develop PFQ with deterministic time-varying weight assignments, and we propose a low-overhead algorithm capable of supporting arbitrary piecewise linear service curves which achieve delay-bandwidth decoupling. Unlike existing service-curve based algorithms, our time-varying PFQ scheme does not exhibit the punishment phenomenon, and allows sessions to exploit the extra bandwidth in under-loaded networks.     

Cross-layer modeling of adaptive wireless links for QoS support in heterogeneous wired-wireless networks

Future wired-wireless multimedia networks require diverse quality-of-service (QoS) support. To this end, it is essential to rely on QoS metrics pertinent to wireless links. In this paper, we develop a cross-layer model for adaptive wireless links, which enables derivation of the desired QoS metrics analytically from the typical wireless parameters across the hardware-radio layer, the physical layer and the data link layer. We illustrate the advantages of our model: generality, simplicity, scalability and backward compatibility. Finally, we outline its applications to power control, TCP, UDP and bandwidth scheduling in wireless networks. The work by Q. Liu and G. B. Giannakis are prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The work by S. Zhou is supported by UConn Research Foundation internal grant 445157. Qingwen Liu (S’04) received the B.S. degree in electrical engineering and information science in 2001, from the University of Science and Technology of China (USTC). He received the M.S. degree in electrical engineering in 2003, from the University of Minnesota (UMN). He currently pursues his Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Minnesota (UMN). His research interests lie in the areas of communications, signal processing, and networking, with emphasis on cross-layer analysis and design, quality of service support for multimedia applications over wired-wireless networks, and resource allocation. Shengli Zhou (M’03) received the B.S. degree in 1995 and the M.Sc. degree in 1998, from the University of Science and Technology of China (USTC), both in electrical engineering and information science. He received his Ph.D. degree in electrical engineering from the University of Minnesota, 2002, and joined the Department of Electrical and Computer Engineering at the University of Connecticut, 2003. His research interests lie in the areas of communications and signal processing, including channel estimation and equalization, multi-user and multi-carrier communications, space time coding, adaptive modulation, and cross-layer designs. He serves as an associate editor for IEEE Transactions on Wireless Communications since Feb. 2005. G. B. Giannakis (Fellow’97) received his Diploma in Electrical Engineering from the National Technical University of Athens, Greece, 1981. From September 1982 to July 1986 he was with the University of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engineering, 1986. After lecturing for one year at USC, he joined the University of Virginia in 1987, where he became a professor of Electrical Engineering in 1997. Since 1999 he has been a professor with the Department of Electrical and Computer Engineering at the University of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications. His general interests span the areas of communications and signal processing, estimation and detection theory, time-series analysis, and system identification -- subjects on which he has published more than 200 journal papers, 350 conference papers and two edited books. Current research focuses on transmitter and receiver diversity techniques for single- and multi-user fading communication channels, complex-field and space-time coding, multicarrier, ultra-wide band wireless communication systems, cross-layer designs and sensor networks. G. B. Giannakis is the (co-) recipient of six paper awards from the IEEE Signal Processing (SP) and Communications Societies (1992, 1998, 2000, 2001, 2003, 2004). He also received the SP Society’s Technical Achievement Award in 2000. He served as Editor in Chief for the IEEE SP Letters, as Associate Editor for the IEEE Trans. on Signal Proc. and the IEEE SP Letters, as secretary of the SP Conference Board, as member of the SP Publications Board, as member and vice-chair of the Statistical Signal and Array Processing Technical Committee, as chair of the SP for Communications Technical Committee and as a member of the IEEE Fellows Election Committee. He has also served as a member of the IEEE-SP Society’s Board of Governors, the Editorial Board for the Proceedings of the IEEE and the steering committee of the IEEE Trans. on Wireless Communications.