Research

IPS research in wireless communications includes:

• user scheduling and resource optimization from limited cross-layer feedback
• analyses of optimal noncoherent communication schemes and pilot-aided schemes
• communication over quickly varying channels with long delay spread (e.g., underwater acoustic channels)
• energy-efficient wireless communication in sensor networks
• exploitation of channel sparsity
• cooperative communication.

Research in wireless communication frequently relates to advances in sensor networks. Research on this connection includes:

• Energy-efficient wireless communication in sensor networks
• Energy management and resource allocation in sensor networks with replenishing energy sources

Faculty and researchers involved: Dr Phil Schniter, Dr C. Emre Koksal

Information-theoretic research conducted by IPS investigators includes

• Fundamental limitations of wireless channels in sensor networks with cross-layer feedback
• Information-theoretic secrecy in wireless networks
• Combining switching theory with information theory

Faculty and researchers involved: Dr C. Emre Koksal, Dr Hesham El Gamal.

IPS investigators explore inverse scattering, signal processing algorithms, and image analysis topics motivated by novel radar operating modalities. Current topics include:

• persistent video with synthetic aperture radar;
• image-aided tracking;
• high-frequency scattering models;
• through-wall imaging;
• signature identification;
• field measurements.

In addition, the lab is involved in hyperspectral data exploitation research. Hyperspectral images provide abundant spectral reflectivity and emissivity information about materials present within a scene. This information can be utilized for numerous tasks including material identification, vegetation and water monitoring, and natural resource monitoring. Current efforts are dedicated to hyperspectral change detection (identification of objects that have been inserted or removed from a scene over time). Atmospheric and illumination changes make this task difficult.

Graduate research assistants and internships are supported by Air Force Research Laboratory, the Air Force Office of Scientific Research, DARPA, Lincoln Laboratory, and industry partners.

Participating faculty: Dr Emre Ertin, Dr Randolph Moses, Dr Lee Potter.

Sensor networks, which support data acquisition across space and time, are an enabling technology that supports the development of new spatially-aware inference and control applications. Example sensing applications in this active and growing area include precision agriculture, non-invasive habitat monitoring, inventory control, and military applications such as intruder detection and tracking.

IPS investigators are involved in both theoretical and applied research for sensor networks. We have fielded sensor systems including acoustic, seismic, RF, magnetic, and infrared sensors. Current topics of theoretical focus include:

• Foreign object detection, classification, and tracking
• Sensor fusion and multimodal surveillance
• Propagation modeling in inhomogeneous atmospheres
• Performance bounds and scaling properties of sensor networks
• Sensor network self-localization and source localization
• Applications of game theory to sensor networks

Advances in sensor networks are frequently related to breakthroughs in networking theory and wireless communication:

• Energy-efficient wireless communication in sensor networks
• Energy management and resource allocation in sensor networks with replenishing energy sources

Faculty and researchers involved: Dr Eylem Ekici, Dr Emre Ertin, Dr Atilla Eryilmaz, Dr C. Emre Koksal, Dr Randolph Moses, Dr Ness Shroff.

Networking is a discipline that is concerned with communication between devices. Communication could be over a wired or wireless medium. Networks are the core of modern communication. Personal Area Networks, the Internet, Cellular Networks, Wireless Mesh Networks and Wireless Sensor Networks are some of the important classes of networks that significantly impact the modern world.

IPS research in networking can be classified into the following areas:

• Network Coding
• Fundamental problems in Scheduling, Routing and Congestion Control
• Network Security
• Data Aggregation and Energy Efficiency in Wireless Sensor Networks
• Mobile Networks

IPS research in networking theory includes

• Resource allocation in wireless networks with time-varying channels
• Analyzing important metrics such as throughput, energy and delay
• Studying fundamental characteristics of important scheduling policies (Greedy Maximal Scheduling (GMS), Maximum Weighted Matching (MWM), Maximum Matching)
• Utility maximization for wired and wireless networks
• Securing networks against potential attacks (e.g., DoS, Wormhole)
• Analyzing effects of mobility
• Developing provably efficient algorithms for achieving desired network performance

Faculty involved: Dr Eylem Ekici, Dr Atilla Eryilmaz, Dr C. Emre Koksal, Dr Phil Schniter, Dr Ness Shroff.

IPS researchers are studying data acquisition and processing aspects electron paramagnetic resonance (EPR) imaging and cardiac magnetic resonance imaging (MRI) in conjunction with researchers at the OSU College of Medicine’s Davis Heart & Lung Institute. In EPR, the goal is to reduce data acquisition time for 3D continuous wave imaging for in vivo measurement of oxygen. Our methods combine

• waveform and modulation design,
• 4D sampling strategies,
• digital receiver architectures, and
• inversion algorithms using physically-based parsimonious signal models.

Faculty and researchers involved: Dr Rizwan Ahmad, Dr Lee Potter.

Behavioral science studies such as exploring correlation between stress and addiction have relied mostly on self-reports and in-lab tests, neither of which provide accurate data in real time. Ohio State Biosensors group in collaboration with University of Memphis, University of Minnesota and University of South California has been developing prototype body wireless sensor nodes that aims to impact behavioral science research by making accurate behavioral data available in real time from the natural environment of subjects. Ohio State wireless biosensors include:

• ECG
• Galvanic Skin Response
• Respiration,
• Body and Ambient Temperature,
• 3-D acceleration
• Interstitial Fluid (ISF) based alcohol sensor.

Ohio State Wireless Biosensors enable behavioral science researchers to obtain accurate stress and addiction data from the field in real-time and targets behavioral science studies such as for studying relationship between alcohol and smoking, patterns of drinking, assessing the effectiveness of different substance abuse treatment programs.

Faculty involved: Dr Emre Ertin.

Ohio State software defined radar group has been developing vertically integrated software defined radar systems that can adapt to sensing requirements in real-time. Adaptation of both transmit waveform and receive signal processing enables the radar to operate in multiple modes including:

1. moving target indicator (MTI)
2. high range resolution (HRR) MTI
3. synthetic aperture radar
4. inverse synthetic aperture radar
5. through-wall imaging

Multiple phase centers facilitate polarimetric and interferometric operation as well as serve as a testbed to implement and test multi-input, multi-output (MIMO) and waveform adaptive radar concepts.

Ohio State prototype radar sensors combines high bandwidth digital back-end with a RF front-end having a variable center frequency over a wide frequency range (1-18 GHz covering L, S, X, and Ku bands). High speed digital waveform generator s are used to construct independent waveforms for each antenna. In the receive signal chain, the received energy is sampled at the baseband bandwidth coherently across the multiple channels and fed to a FPGA-based real-time signal processor for multi-channel coherent processing. Higher layer control algorithms select optimal RF sensing and processing settings to adapt to sensing objectives and changing environmental conditions.

Researchers involved: Dr Emre Ertin, Dr Randolph Moses.

With the growing number of wireless devices and increased spectrum occupancy, the unlicensed spectrum is getting scarce. Additionally, large portions of the licensed spectrum, even in urban areas, are underutilized. To address the potential spectrum exhaustion problem, new wireless communication paradigms have been proposed. The Cognitive Radio (CR) concept is a new wireless communication paradigm that improves the spectrum usage efficiency by exploiting the existence of spectrum holes. Devices using CRs referred to as Secondary Users (SUs), are aware of their spectrum environments and change their transmission and reception parameters to avoid interference with licensed spectrum users referred to as Primary Users (PUs). Networks consisting of nodes equipped with CRs are referred to as Cognitive Radio Networks (CRNs).

CRNs are networks that have cognitive and reconfigurable properties and the capability to detect unoccupied spectrum holes and change frequency for end-to-end communication. In most of the existing proposals, CRNs employ three steps of basic functionality. Observing and sensing is the first step of the cognitive process. The next step is to identify and analyze the spectrum. The last step is sharing the spectrum information and executing spectrum assignment. In addition to these awareness functionalities, to maintain seamless communication, several proposals envision spectrum mobility which is caused by three reasons such as PU detection, channel degradation, and SU mobility. IPS investigators explore solutions to these problems under the following topics:

• Resource management in multi-hop CRNs
• Spectrum handoff
• Adaptive cross-layer solutions
• Cooperation-based networking with cognitive radio terminals

Faculty and researchers involved: Dr Eylem Ekici.