Douglas B. Williams

QoS routing mechanisms and OSPF extensions

This paper presents and discusses path selection algorithms to support QoS routes in IP networks. The work is carried out in the context of extensions to the OSPF protocol, and the initial focus is on unicast flows, although some of the proposed extensions are also applicable to multicast flows. We first review the metrics required to support QoS, and then present and compare several path selection algorithms, which represent different trade-offs between accuracy and computational complexity. We also describe and discuss the associated link advertisement mechanisms, and investigate some options in balancing the requirements for accurate and timely information with the associated control overhead. The overall goal of this study is to identify a framework and possible approaches to allow deployment of QoS routing capabilities with the minimum possible impact to the existing routing infrastructure.

A space-frequency transmitter diversity technique for OFDM systems

A transmitter diversity technique for wireless communications over frequency selective fading channels is presented. The proposed technique utilizes orthogonal frequency division multiplexing (OFDM) to transform a frequency selective fading channel into multiple flat fading subchannels on which space-frequency processing is applied. Simulation results verify that in a slow fading environment the proposed space-frequency OFDM (SF-OFDM) transmitter diversity technique has the same performance as a previously reported space-time OFDM (ST-OFDM) transmitter diversity system but shows better performance in the more difficult fast fading environments. Other implementation advantages of SF-OFDM over the ST-OFDM transmitter diversity technique are also discussed.

A space-time coded transmitter diversity technique for frequency selective fading channels

A simple space-time coded orthogonal frequency division multiplexing (OFDM) transmitter diversity technique for wireless communications over frequency selective fading channels is presented. The proposed technique utilizes OFDM to transform frequency selective fading channels into multiple flat fading subchannels on which space-time coding is applied. A two-branch transmitter diversity system is implemented without bandwidth expansion and with a small increase in complexity beyond that of a conventional OFDM system. Simulations verify that the two-branch transmitter diversity system achieves a diversity gain equivalent to that of the optimal maximal ratio combining (MRC) receiver diversity system.

Transmission Subspace Tracking for MIMO Systems With Low-Rate Feedback

This paper describes a feedback algorithm for tracking the dominant subspaces of continuously time-varying channels in multiantenna communication systems. The nature of the problem is quantization of subspaces. It is well known that subspaces can be mathematically modeled as points in a Grassmann manifold. We model the variations between the dominant subspaces of channels at adjacent time instants to be along geodesics in the Grassmann manifold. Instead of quantizing the subspaces themselves, we propose to quantize the geodesic trajectory connecting two subspaces. More specifically, we quantize a key entity that characterizes a geodesic arc: the velocity matrix, which resembles angular speed in a one-dimensional complex space. Two techniques are proposed for quantizing the velocity matrix of the geodesic. In the first, a 1-bit feedback is utilized to indicate the preferred sign of a random velocity matrix of the geodesic. In the other, the velocity matrix is quantized using a Gaussian vector quantization codebook. Numerical results show that the performance of the proposed 1-bit feedback algorithm is better than a previously proposed Grassmannian subspace packing scheme at low-to-medium Doppler frequencies and better than a gradient sign feedback scheme at all Doppler frequencies. In our simulations, the Gaussian vector quantization algorithm is always better than the 1-bit feedback algorithm.

Array processing techniques for multiuser detection

Techniques often used in the area of adaptive array signal processing are applied to the multiuser detection problem. The results of this effort include a robust detector, suitable for use in the presence of modeling errors, and a reduced-rank detector with improved transient behavior relative to full-rank detectors. Algorithm performance is presented in the form of bit-error-rate (BER) curves and least mean square (LMS)-like learning curves.

Robust estimation of structured covariance matrices

In the context of the narrowband array processing problem, robust methods for accurately estimating the spatial correlation matrix using a priori information about the matrix structure are developed. By minimizing the worse case asymptotic variance, robust, structured, maximum-likelihood-type estimates of the spatial correlation matrix in the presence of noises with probability density functions in the in -contamination and Kolmogorov classes are obtained. These estimates are robust against variations in the noises amplitude distribution. The Kolmogorov class is demonstrated to be the natural class to use for array processing applications, and a technique is developed to determine exactly the size of this class. Performance of bearing estimation algorithms improves substantially when the robust estimates are used, especially when nonGaussian noise is present. A parametric structured estimate of the spatial correlation matrix that allows direct estimation of the arrival angles is also demonstrated. >

Detection and identification of human targets in radar data

Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

Counting the degrees of freedom when using AIC and MDL to detect signals

In the well known paper by Wax and Kailath (1985), the AIC and MDL criteria for determining the number of signals in a multichannel time-series are presented. An essential element of these criteria is the number of degrees of freedom in the model. We propose a different number for the degrees of freedom and show that the resulting MDL criterion performs noticeably better than the previous criterion. We also show that the same criteria are appropriate for either real or complex data. >

On the characterization of impulsive noise with /spl alpha/-stable distributions using Fourier techniques

A new technique is presented for the characterization of impulsive interference with /spl alpha/-stable processes. The proposed model is constructed by estimating the /spl alpha/-stable distribution parameters using the empirical characteristic function. Characteristic function based methods have been shown to yield the best performance but are plagued by the amount of computation required. The new parameter estimation algorithm is shown to achieve the same level of performance as other characteristic function based methods while greatly reducing the amount of computation required.

Pilot-symbol-assisted channel estimation for space-time coded OFDM systems

Space-time coded orthogonal frequency division multiplexing (OFDM) transmitter diversity techniques have been shown to provide an efficient means of achieving near optimal diversity gain in frequency-selective fading channels. For these systems, knowledge of the channel parameters is required at the receivers for diversity combining and decoding. In this paper, we propose a low complexity, bandwidth efficient, pilot-symbol-assisted (PSA) channel estimator for multiple transmitter OFDM systems. The pilot symbols are constructed to be nonoverlapping in frequency to allow simultaneous sounding of the multiple channels. The time-varying channel responses are tracked by interpolating a set of estimates obtained through periodically transmitted pilot symbols. Simulations are used to verify the effectiveness of the proposed estimator and to examine its limitations. It is also shown that the PSA channel estimator has a lower computational complexity and better performance than a previously proposed decision-directed minimum mean square error MMSE channel estimator for OFDM transmitter diversity systems.