The three broad areas of emphasis in the department are communications, signal processing, and photonics. The interest of the faculty and their current research falls generally into one of these areas.
Research in communications is in the areas of antenna design, wireless communications, computer and communication networks and network and data security. Research in antennas is focused on developing flat-panel antennas for US DBS satellite communication systems, and on small and efficient antenna designs for mobile communication applications. Another topic is development of software for design and analysis of antennas based on the finite element method (FEM) for use with large arrays.
In wireless communications, algorithms are being developed for high speed communications under the IEEE 802.11a standard. Efforts are focused on developing technologies that will support indoor and outdoor wireless connections exceeding 100Mbits/second. Another area of research is in power adaptation techniques for wireless multimedia. Focusing on the design of power efficient transmission policies for wireless multimedia, this research explores the tradeoff between transmission power, capacity and communication latency. Minimizing the transmission power is very critical for many reasons. First, lower transmit power translates directly into longer battery life. Second, lower transmit power implies lower interference to other devices operating in the same area and consequently higher capacities in terms of data rates or number of users supported. The new policies can result in substantial savings in transmission power (up to 60%) for small increases in packet delay.
Research in communication networks is aimed at developing model classification algorithms to automatically fit network traffic to stochastic models to enable service providers to automatically adapt their traffic control to changing network conditions. New real-time traffic measurement capabilities for routers are being developed by defining a "traffic profile" to capture the most important aspects of traffic flows in a compact mathematical form. These traffic metering capabilities will enable routers to provide traffic measurement data for a variety of applications such as traffic control, network planning, security, and accounting. Finally new models to analyze the cost/benefit trade-offs for mobile code are being developed by applying risk analysis used in other fields to quantify the security risks for mobile code. Another project is concerned with accurate modeling and prediction of network traffic for traffic management for optimal allocation of available resources. In this work, intelligent-system based models such as artificial neural networks and fuzzy logic investigated for their to characterize high-speed traffic at different time scales.
A new scheme for robust coding of video over noisy channels and transmission to reduce error propagation is being investigated by using a tree structure by classifying frames into three different categories. The structure introduces different levels of priority to the frames being coded. Different levels of error protection can be assigned to packets from different types of frames. It is expected that a combination of data partitioning with the proposed scheme will prove beneficial.
Research in signal processing covers a wide range of application areas. Blind source separation seeks to undo the acoustical mixing caused by room acoustics in multichannel recordings of acoustic events without knowledge of the sound sources, the room acoustics, or the physical arrangement of sources or sensors in the room. Applications include teleconferencing, audio recording, and surveillance. A related problem is that has applications in hearing aids is the removal of echo and reverberation caused by room acoustics that makes speech unintelligible.
In biomedical signal processing, human vision models are being developed which link visual acuity to eye motion. Blind system identification algorithms that are robust and provide a substantial improvement in the resolution and quality of medical ultrasound images are being investigated. Another area of interest is the use of subspace methods for speech enhancement and coding.
Other projects explore the use neural networks, fuzzy approaches and genetic algorithms to problems of interest. New approaches to short-term power system load forecasting in a deregulated and price-sensitive environment are being developed for a real-time pricing scenario where energy prices could change on an hourly basis. A two-stage load forecaster has been developed with the first stage consisting of a price-insensitive neural network forecaster known as ANNSTLF and a second stage fuzzy logic based module which transforms the price-insensitive forecast of ANNSTLF to a price sensitive load forecast. A second project focuses on developing fuzzy logic based pattern classifiers. A genetic algorithm (GA) based approach is being developed to optimize all the required fuzzy system parameters. The resulting fuzzy classifier will be tested for several different classification applications and its performance will be compared to other types of classifiers.
In many applications such as video browsing, indexing of relevant scenes in a video sequence is important for their efficient retrieval. Such indexing is most commonly done by identifying scene cuts that represent the boundary between video shots. Scene cut detection involves the identification of frames at which the content of the scene is significantly different from that of the previously retained frames. Traditional shot detection methods are sensitive to noise and often turn out to be inefficient in dealing with the so-called gradual scene changes. This research is aimed at developing robust techniques for identifying scene cuts and gradual scene changes.
Research in photonics is aimed at fabrication of an efficient monolithic laser source and fiber-like waveguide for use in wavelength division multiplexed (WDM) systems. The scheme for coupling light from a laser to a fiber allows for lower fabrication and production costs by obtaining high coupling efficiencies of light from lasers to glass waveguides. Another research project is concerned with determining grating strengths of surface emitting lasers by analyzing the reflection and transmission characteristics of a quantum-well structure with a finite length grating. Long wavelength (1310 and 1550 nm) grating-outcoupled surface-emitting lasers are also being investigated for telecommunications applications. Other programs are concerned with developing high power (1 to 10 Watts), highly coherent, single-frequency semiconductor lasers; coherent arrays of high power vertical cavity semiconductor lasers; and radio frequency gyroscopes designed to operate in the 50 to 100 GHz range of frequencies.
One of the greatest barriers to the insertion of optical interconnections in systems is cost. An interconnection medium that is immune to misalignments would radically lower the cost barrier for the insertion of optical interconnections in systems. Graded index material, developed extensively for reducing modal dispersion in fiber optics, has a potential application for alignment insensitive multi-chip optical interconnections as well. Experiments will be conducted to integrate and evaluate an optical interconnection architecture based on graded index slab material.