Supported by NSF CNS #1731833

Next generation wireless networks will be characterized by larger volume, faster information transfer, and diversity. Wireless industry has been altering conventional license-based spectrum access policies through approaches utilizing unlicensed spectrum. This leads to dynamic spectrum access (DSA), where unlicensed use of a spectrum should avoid harm to licensed users, or should ensure a fair share of spectrum with other unlicensed users. DSA places an additional burden on business operations because revenue needs to be generated over dynamically changing resources, while providing expected quality of service to potential users. Yet, existing high-level approaches for spectrum sharing are not well poised to solve the core problem. Instead, finer-scale spectrum sharing in time, space, and spectrum dimensions is required. Furthermore, at such finer scales, it is essential to consider human behaviors and integrate economics into the tool-set of spectrum sharing. Finally, recent cyber-security concerns necessitate that such a system should incorporate security and privacy in its core. This project designs and develops advanced spectrum sharing techniques at the nexus of spectrum, pricing, and privacy, for next-generation DSA solutions. The project is conducted by an interdisciplinary team of experts in security, operations management, decision science, wireless communication, networking, and optimization. The fundamental results emerging from this research can enable transformative cognitive radio network management and operation solutions. The project supports multiple graduate students. Insights from the proposed collaborative research project between Ohio State and University of Nebraska Lincoln will educate both industry and academia across rural Nebraska and urban Ohio regions.

The project explores four main goals: (1) Secure spectrum resource metering solutions with a Cognitive Secure Cloud Radio Access Networks (CoSeC-RAN) architecture. Preserving the digital base-band data within the network leads to more accurate resource assignment and pricing decisions. (2) Advanced security and privacy-preserving solutions. The novel CoSeC-RAN architecture enables new directions to provide security to and by the network while preserving user privacy. (3) Dynamic pricing algorithms, where prices are updated in real-time based on available capacity and customer load. These pricing algorithms reflect non-stationary and stochastic nature of both available capacity and demand. Customer-specific bandwidth requirements and mechanisms for ensuring customer privacy are incorporated into algorithm design. (4) Spectrum sensing methods with incomplete information. CoSeC-RAN estimates primary signals at secondary user locations, with incomplete information from the network, to ensure minimum interference. Developed solutions are rigorously tested through large-scale simulations and experimentally in a city-wide testbed.

This study is a continuation of our previous research on Cog-TV.

Supported by NSF CNS #1619285

This project aims to increase the communication ranges and data rates of buried radios by leveraging expertise in the nexus of computer science and engineering and biological systems engineering. The goals of this project are to characterize the underground channel; develop environment-adaptive solutions to achieve high data rate, long-range communications; and illustrate applications to agriculture and transportation. The emerging use of wireless underground sensor networks (WUSNs) in many areas, including precision agriculture, transportation, environment and infrastructure monitoring, and border patrol, underscores the importance of wireless underground (UG) communications. Yet, existing limitations in terms of communication ranges and data rates prohibit widespread adoption. The novel approaches developed in the project broaden the scope of existing and novel applications, leading to economically viable solutions. The results and the insight from this project have the potential to enable a wide array of novel solutions from saving water resources for more food production to saving lives on the roadways.

Extending the communication ranges and increasing data rates in wireless UG communications faces unique challenges because of the interactions between soil and communication components: (1) Antenna properties depend on soil type and vary with changes in soil parameters such as temperature and moisture. (2) Channel characteristics, such as delay spread and coherence bandwidth, are time-variant functions of the soil parameters. (3) The soil-air interface results in fluctuations in both antenna performance and EM wave propagation, which should be considered in system design. To address these challenges, the project captures the impulse response of the wireless UG channel through extensive experiments throughout the state of Nebraska, which is one of the most diverse states in terms of soil textural properties, climatic gradients, and land use. Based on this analysis, advanced modulation schemes are developed. Moreover, based on UG antenna analysis, long-range communication techniques are developed. Two distinct applications from agriculture and transportation are considered to evaluate the developed solutions in a crop field and a crash test site.

Overall V2B Setup

Supported by NSF CNS #1816938

More than half of fatal vehicle crashes in the US today are "run-off-road" (RoR) crashes and roadside barriers are the last means of mitigating their severity. Yet, vehicles of tomorrow are slated to operate on roadside infrastructure designed decades ago. This project aims to bridge this gap by establishing wireless connectivity between vehicles and roadside barriers by developing a novel vehicle to barrier (V2B) communication and networking paradigm called connected barriers (CBs). CBs will (1) complement on-board sensor technologies and existing physical barriers, (2) avoid RoR crashes, (3) minimize the severity of a crash when it is inevitable, and (4) help develop mutual collaborations between the roadside safety and vehicular communication and networking communities, which will lead to robust technology solutions. Based on Department of Transportation's value of a statistical life estimate in 2014, the societal cost of a crash is $9.4 million per fatality, with approximately 10,000 fatal ROR crashes each year. With widespread implementation, this research project could reduce fatal and non-fatal crash rates by up to 70%, which could save as many as 8,000 lives per year in the U.S. alone and billions of dollars in economic losses. This project supports 2 graduate students and its results will be incorporated into several courses at UNL and OSU. Insights from the project results will help establish collaborative efforts to educate both industry and academia in Nebraska and Ohio.

To realize the CB vision, the project explores three main threads: (1) the foundations of V2B communication will be established through analysis of wireless channel characteristics in field measurements, actual car-crash tests, and channel model development. (2) to enable reliable control reactions, very high-fidelity barrier-assisted vehicle localization and vehicle-barrier synchronization solutions will be developed. (3) novel communication algorithms and protocols will be developed to disseminate periodic information about barrier and road conditions, and to facilitate real-time information exchange during upcoming RoR events, with an eye towards coexistence with existing communication standards. The developed solutions will be evaluated through encroachment and vehicle crash experiments in the Midwest Roadside Safety Facility, and system evaluations on low-volume suburban and rural road segments in collaboration with the Village of Eagle, Nebraska, and Nebraska's Cass County. Finally, a multi-time-scale simulation platform will be integrated by including empirical measurements of the wireless channel, vehicle and barrier dynamics, traffic dynamics, and communication and network dynamics to provide effective evaluation tools of the CB paradigm


constructionSupported by NSF CIS #1538029

The objective of this research is to examine whether, how, and to what extent workers' collective bodily and behavioral response patterns identify recognized/unrecognized hazards for the purpose of enhancing safety performance in construction environments. This research focuses on detecting hazards that causes fall accidents, a single most dangerous injury event within the construction industry, using workers - kinematic sensing data captured from wearable inertial measurement sensors. Methodologies developed in this research will enable the evaluation of collective patterns associated with human responses to estimate the likelihood of hazard locations across a construction site. Knowledge gained from this research will advance our ability to utilize response information for accident prevention, leading to reduced injuries and fatalities from construction-related accidents.

CFOSynt experiment platformSupported by NSF CNS #1423379

This project aims to fuse existing understanding of cross-layer networking with novel synchronization solutions, to overcome challenges in synchronization including adaptation on environment and energy availability, the disruption caused by Duty-cycle operations at the MAC layer, time dissemination due to multi-hop characteristics, and different granularity levels on timing accuracy requirements from applications. The results of the project are disseminated to attract female students and minorities as a part of the Building Recruiting and Inclusion for Diversity (BRAID) initiative.

Supported by NSF CAREER Grant CNS #0953900

Many applications for irrigation management and environment monitoring exploit buried sensors wired-connected to the soil surface for information retrieval. Wireless Underground Sensor Networks (WUSNs) is an emerging area of research that promises to provide communication capabilities to these sensors. However, the strong high attenuation caused by soil is the main challenge for the feasibility of WUSNs. In addition to the communication among the underground devices, a WUSN still requires aboveground devices for data retrieval, management, and relay functionalities. Therefore, the characterization of the channels among those nodes is essential for the realization of WUSNs. This project is based on experiments in agriculture field to establish communication channel models for WUSNs, which will support the development of WUSN multi-hop protocols and devices for the applications.

Supported by NSF Grant CNS #1247941

Cog-TV architecture

Today's wireless networks are facing an emerging spectrum crisis due to increased demand. FCC has recently allowed non-licensed devices to operate in the TV spectrum band, leading to cognitive radio networks (CRNs). It is argued that CRNs result in a technical and economical conflict with the TV broadcast companies, which own licenses to the TV spectrum. In this project, CRNs are considered as a business opportunity for broadcast companies. The answer to the following question is sought: "Is it economically and technically viable for broadcast companies to utilize TV white spaces for low-cost Internet provision and web-enabled TV services?" To facilitate the involvement of broadcast companies in the cognitive radio business, the concept of cognitive radio-enabled TV set (Cog-TV) is considered. Cog-TV provides low-cost access to the Internet and local area network capabilities. Cog-TVs are assigned optimal spectrum sensing schedules to provide service differentiation capabilities through a novel neighborhood watch concept. Dynamic pricing techniques are developed with the objective of distributing the peak-time demand load. Moreover, the cost of building the Cog-TV infrastructure in urban and rural areas is analyzed to determine its economic feasibility. Through this architecture, broadcast companies can leverage their channel ownership to create a competitive advantage.

The results from this research are expected to enable transformative and economically viable CRN development and management approaches. The Cog-TV concept has the potential to bring affordable Internet service to a large group of American households and impact consumer market by creating a niche market in new TV sets.

Supported by NSF grant DBI #1331895

This project investigates the feasibility of wireless underground sensor networks (WUSNs) for soil parameter monitoring and devises next-generation autonomous irrigation management tools to improve crop production efficiency. Agriculture is the largest user of freshwater resources, accounting for about 70-80% of current withdrawals. With the increasing demands and the emerging scarcity in freshwater resources, increasing the crop yield is essential. The wirelessly connected, permanently installed underground sensor networks can feed real-time information from the soil to the irrigation management system, improving crop yields in a cost-effective manner. This project develops a proof-of-concept irrigation management testbed and associated agricultural practices and tools for autonomous control of a center pivot irrigation system. The developed tools are integrated into a heterogeneous architecture that consists of underground sensing components, relay nodes, a cloud-based management system and mobile components. These results of this project will make significant contributions to the implementation of the variable rate irrigation concept. Moreover, irrigation-scheduling protocols developed using the WUSN will account for different soil textural classifications. While transforming irrigation practices, the research also devises sustainable underground system solutions through development of unique antenna designs; transmit power control techniques, and vibration energy harvesting systems. The resulting prototype is the first sustainable wireless underground sensor system and enables investigation of the relationships between locally-sensed data and crop yields. Accordingly, the project develops on-line management tools that will enhance crop production efficiency in the long-term.

Designing real-time scheduling and communication solutions for Emerging applications of wireless sensor networks (WSNs) is challenging since the characteristics of QoS metrics in WSNs are not well known yet. Due to the nature of wireless connectivity, it is infeasible to satisfy worst-case QoS requirements in WSNs. Instead, probabilistic QoS guarantees should be provided, which requires the definition of probabilistic QoS metrics. To provide an analytical tool for the development of real-time solutions, in this project, the statistical properties in WSNs are investigated. These properties include end-to-end delay, energy consumption, lifetime, and delay jitter. Our work shows that the framework accurately predicts the end-to-end delay distribution in WSNs. 

Whooping Cranes (Grus Americana) are an endangered species of bird that is native to North America. Less than 600 of these large birds remain. In order to effectively manage the population, detailed environmental and behavioral data is needed. To this end, monitoring devices will be attached to the birds. These devices utilize low-cost communication methods to deliver timely data on the bird's environment and behavior.