Communications, Signal Processing and Networks

NASA / EPSCoR Funded Work on Bio-sensors and Telecom Subsystems

This project is developing technologies applicable to both human space-flight and robotic scout missions to outer planets and asteroids. At its center is a vision for wireless biosensors operating within future extra-vehicular activity (EVA) suits.

By designing sensor systems based on physiological studies taking place in K-State's kinesiology department, we are developing the ability to adapt sensor selections to varied missions. Developing a low-power wireless sensor network operating within an EVA suit represents a second major goal. This requires analysis of radio transmissions within a space-suit environment, taking into account radio-wave absorption levels in tissue and reflection from the aluminized Mylar protective material employed in the outer garment layers. A final technical thrust is to develop suitable software and hardware solutions.

To address the need for low-power radios in these applications, we are leveraging and maturing the K-State/JPL Mars Micro-Transceiver research conducted in previous years. This radio will be adapted for use in the sensor network development efforts and through a joint venture with Kansas industry matured to support infusion into a wide range of future robotic precursor scout missions. Outreach activities based on the space-suit theme are also being developed to inspire a new generation of students to pursue science, technology, engineering and mathematics (STEM) in their college education and future careers.

Communication Circuits Laboratory

The Communications Circuits Laboratory (CCL) conducts coordinated teaching and research in analog and radio frequency (RF)design. Within the teaching area, students design, build and test complete radios and radar systems at VHF through microwave frequencies. This gives our graduates practical, hands-on experience necessary for this field of engineering.

Our research efforts have been primarily focused on design of transceivers in integrated circuit form with special emphasis on the modeling and application of high-Q spiral inductors and performance of semiconductor processes. Students and faculty connected with the CCL have experience with standard bulk-CMOS, silicon-on-insulator (SOI) and silicon-on-sapphire (SOS) and GaAs integrated circuit processes. Designs are created with tools from both Agilent and Cadence, and are tested at the board and chip levels with industry caliber measurement equipment and probing stations.

Examples of research and development work is our Mars micro transceiver recently developed in collaboration with NASA's jet propulsion laboratory. This three-year project resulted in a complete RFIC chipset for future missions to the planet Mars. Please visit the webpage for more information.

Network Science and Engineering (NetSE) group

Our goals are to conduct theoretical research in emerging areas of network science as well as to design optimal networking solutions for current and future realistic problems. General areas of interest include network science, network robustness, network metrics, computer networking protocols, architectures, modeling and analysis, and interdependent networks.

The group has received funding mostly from the National Science Foundation, but also from the Kansas Bio Authority, U.S. Department of Agriculture (USDA), Department of Defense (DoD), National Academies Keck Futures Initiative, Kansas State University, and industry partners such as the Electric Power Affiliates Program (EPAP). Graduates from our group have published extensively and work now in academia and industry.

Network science

Projects in this area advance the boundaries of network theory by analyzing multi-layer and interconnected complex networks. These projects use rigorous mathematical tools from network science, spectral graph theory, nonlinear dynamics, stochastic processes, controls, game theory and optimization.

Network engineering

Projects in this research area focus on the design and evaluation of software-defined networking (SDN) solutions for communication and control of cyber-physical systems. Traffic engineering and security solutions are designed through mathematical modeling and optimization and evaluated in Mininet.

CPSWin - Cyber-Physical Systems and Wireless Innovations (CPSWin) Group

The CPSWIN group supports a wide range of fundamental as well as applied research in the areas of wireless communication and information processing. Core expertise of the group lies in mathematical/statistical modeling, estimation and detection/decision theory, optimization and control theory, and information theory.

The group has received funding from federal and state agencies such as National Science Foundation, NASA EPSCOR program, Kansas Department of Transportation (KDoT), Sandia National Labs (Department of Energy), U.S. Marines (M2 Technologies), State of Kansas, Kansas State University Targeted Excellence Program, as well as industry partners Garmin Inc., Trisquare Communications, etc. Researchers in the group have contributed to more than 60 peer-reviewed publications.

Key projects in the wireless communication area over the last five years include design of a practical cognitive radio, resource allocation and quality of service assurance in a competitive cognitive radio network, precoding for MIMO and MIMO-OFDM systems, coexistence issues between ultra-wideband and GPS systems, multiuser detection in MC-CDMA systems and biologically inspired spreading sequence design strategies.

The group’s contribution to the fields of spread spectrum communication and MIMO precoding has resulted in two patent applications. Projects in the area of information processing in sensor networks include resource allocation in collaborative target tracking, information fusion strategies for distributed event detection over bandwidth constrained networks, optimal control-based sensor deployment strategies, sensor fusion in biomedical applications, networked control of distributed systems, and automated pavement distress detection via image processing and sensor fusion methods.