Projects 2012 – 2013

Projects 2013 – 2014

Cognitive Capacity Harvesting Networks

Prof. Yuguang Fang, University of Florida, USA
Prof. Savo Glisic, University of Oulu, Finland
Assoc. Prof. Pan Li, Mississippi State University, USA

Due to the emergence of ever increasing diversified applications provided by the smart devices such as smart phones, traditional telecommunications systems such as the wireless cellular systems no longer meet the ever exploding traffic demand, and cannot effectively deal with the shortage of available spectrum or congestion over wireless systems. On the other hand, tremendous temporal and spatial network resources, such as spectrum and computational capability, are severely under-utilized. Obviously, how to proactively harvest such residual resources and utilize them opportunistically to support diversified user traffic is an important yet challenging research direction. Although cognitive radio networks are to address this pressing issue, there is lack of viable network architecture in taking full advantage of the opportunistic spectrum access and there exist many practical design issues to be resolved. In this project, the PIs propose a flexible Cognitive Capacity Harvesting (CCH) network architecture to intelligently harvest network resources in both time and space and develop the corresponding technologies to support users’ services effectively. Moreover, the CCH network along with the newly developed networking technologies can enable non-cognitive devices to significantly gain benefits from cognitive radio networks and provides innovative approaches to the cognitive radio networks design. Furthermore, this project research opens a new school of thoughts in better utilizing the residual network resources and potentially changes the design approaches for next-generation telecommunications systems. Finally, this project involves the international partners and can enhance the international components in the educational program and prepare more competitive workforce.

Distributed Resource Allocation and Interference Management for Dense Heterogeneous Wireless Networks

Prof. Zhi Ding, University of California-Davis, USA
Prof. Jyri Hämäläinen, Aalto University, Finland
Assoc. Prof. Xin Liu, University of California-Davis, USA
Prof. Risto Wichman, Aalto University, Finland

This NSF collaboration project investigates the design and optimization of dynamic resource allocation and interference management strategies for spectrally efficient wireless heterogeneous networks that provide multi-level coverage and services. This research project is motivated by the recent advances in 4G wireless systems on the deployment and standardization of heterogeneous networks (HetNet). Such networks provide services to mobile subscribers of different priorities and dynamic quality needs. As more and more advanced physical layer schemes and medium access protocols are being integrated into wireless standards, future performance gain and progress in wireless networks have to rely more on intelligent resource allocation and interference management strategies that are dynamical and are adaptively responsive to location-and-time specific environment. In this project, the research team will address critical deployment issues that arise in HetNet by focusing on the development of distributed and effective mechanisms for resource allocation and interference management in order to facilitate low complexity and decentralized network operation in heterogeneous environments. The project methodology is based on novel optimization frameworks for interference control and suppression in HetNet. The research goal is to develop robust and reliable solutions for practical implementations of HetNet. The project results will facilitate novel technological directions that transcend multiple networks and multiple network layers. In particular, the results will assist the near term deployment of wireless HetNet, including the broad application of femtocell deployment. The technical impacts of this international collaboration project are broad both domestically and internationally. Results from successful execution of the project are expected to significantly impact the design, deployment, and operation of future wireless networks. The plan to disseminating research findings at quality journals and technical conferences will contribute directly to the wireless industry by providing critical information on interference control and management for high spectral efficiency and user satisfaction. The project outcomes can also establish new research directions for the international telecommunications community. The project activities will lead to new analytical tools and discoveries that can impact other science and engineering research fields. The project will further contribute to the training of highly qualified personnel for the hi-tech industry.

Economic Models for Collaborative Access Network Provisioning

Prof. Savo Glisic, University of Oulu, Finland
Assoc. Prof. Allen MacKenzie, Virginia Polytechnic Institute and State University, USA
Prof. Juha Röning, University of Oulu, Finland

Increased capacity in wireless networks has largely come from shrinking cell sizes, but continuing this trend has become impractical for large operators. Small wireless networks are also straining in overcrowded spectrum bands. The problems are particularly acute in high-density 802.11 deployments. It is clear that a collaborative approach, taking advantage of both large infrastructure deployment by operators and distributed deployments of 802.11 and femtocell networks could be extremely beneficial. This project focuses on three major problems related to heterogeneous wireless networks. First, models are developed that quantify the gains from cooperation between large operators and small-scale operators and end users deploying their own wireless access networks. Second, game theoretic and pricing models are developed to study incentive structures to support collaboration in heterogeneous wireless networks. Third, a threat model is developed to specifically model security threats that would impact a heterogeneous wireless network through a holistic vulnerability assessment. These three tasks are all complemented by frequent prototyping and experimentation. This work will be immediately applicable to real networks and will quantify the benefits of collaboration for network operators. In addition, the collaborative project will deepen technological collaboration between the United States and Finland. The models developed in this project will all be available and published in the scientific literature, providing a holistic understanding of heterogeneous wireless networks. These models will catalyze the further technical development of protocols and standards to support open, heterogeneous wireless networks.

Energy Efficient Cognitive Networking

Assoc. Prof. Alhussein Abouzeid, Rensselaer Polytechnic Institute, USA
Dr. Marian Codreanu, University of Oulu, Finland
Prof. Anthony Ephremides, University of Maryland College Park, USA

This project addresses two of the grand challenges of the next decade: green wireless communication systems and spectrum efficiency, through a collaborative research and education plan utilizing optimization theory, and involving researchers from the U.S. and Finland. This project considers energy efficiency for cognitive radio networks and introduces a novel optimization-based methodology. It builds on existing results to establish a new focus on green cognitive networking. The way in which energy is consumed in cognitive networks provides unique opportunities for exploiting the cognitive process to save energy and for using energy reduction techniques to modify and improve the performance of cognitive networks. A unique feature of this project is the introduction of an optimization-based methodology for establishing and attaining ultimate performance limits. In this project, PIs develop energy performance bounds that yield insights for design of general networks, derive optimal tradeoffs between fundamental performance criteria, use optimization formulations for establishing and achieving ultimate performance limits, and design protocols that are optimal in the presence of temporal cognitive systems evolution. Research results of this work will be widely promulgated through the usual means of publication and dissemination and will have significant impact on energy efficiency of spectrum-efficient wireless systems.

Reconfigurable Antenna-based Enhancement of Dynamic Spectrum Access Algorithms

Assoc. Prof. Kapil Dandekar, Drexel University, USA
Prof. Pentti Leppänen, University of Oulu, Finland
Prof. Aarne Mämmelä, VTT Technical Research Centre of Finland, Finland
Dr. Harri Saarnisaari, University of Oulu, Finland
Prof. Mikko Valkama, Tampere University of Technology, Finland
Assoc. Prof. Steven Weber, Drexel University, USA

While there is a tremendous amount of research in the algorithmic and protocol aspects of cognitive radios, very little attention is given to the antennas used in cognitive links. This project focuses on the enhancement of cognitive dynamic spectrum access (DSA) techniques with electrically reconfigurable antennas that are capable of dynamically adjusting their radiation patterns and operating frequency in response to the needs of overlying communication link and network. Based upon the results of field testing, new reconfigurable antennas are being designed that provide not only flexibility in radiation pattern, but also frequency agility. The design and performance of the cross-layer control stack is being evaluated for identification of the optimal control policy for secondary radios seeking to maximize their throughput. With the additional support of our collaborators in Finland, the Drexel SDC Testbed is being extended to provide real-time implementations of the proposed enhanced DSA algorithms. This research is enabled through the reconfigurable leaky wave metamaterial antenna technology, developed at Drexel University. The highly adaptive frequency agility and spatial filtering capabilities of this antenna will be used to develop new DSA algorithms to leverage these degrees of freedom. Enhanced performance will be demonstrated in terms of the user capacity of the cognitive radio network and increased throughput of secondary cognitive radio users. These antennas and control algorithms will be field tested and demonstrated using a FGPA-based SDR platform built to evaluate reconfigurable antenna-enhanced DSA algorithms.

Robust and Secure Cognitive Radio Networks

Prof. Randall Berry, Northwestern University, USA
Prof. Markku Juntti, University of Oulu, Finland
Prof. Olav Tirkkonen, Aalto University, Finland
Prof. Sennur Ulukus, University of Maryland College Park, USA

Cognitive radio is a promising paradigm for dramatically increasing the utilization of wireless spectrum to support the continuing exponential growth in wireless traffic. Research on cognitive networks has mainly focused on sensing of spectrum opportunities and managing radio resources such that the primary users’ quality of service is not compromised. Much less attention has been paid to the coexistence of secondary users, which may be associated with different cognitive networks and seek to operate in the same frequency bands. Effective coexistence of such users is essential for the success of future cognitive networks, and is the main objective of this project. In addition, the particularly open nature of cognitive radio raises significant new issues for the security and privacy of the transmitted data, as well as new opportunities for malicious behavior among cognitive or outside entities. The project addresses all of these issues in a holistic framework. Coexistence requires effective allocation of radio resources in time, frequency, and space among multiple cognitive secondary users, while respecting primary interference constraints. The investigators are developing theoretical bounds for such radio resource management schemes and designing low-overhead distributed algorithms, which account for the incentives of competing secondary service providers as well as the stronger security and privacy measures needed in a cognitive environment. Information-theoretic physical-layer security techniques are being utilized to develop provably secure paradigms for secondary cognitive users and game-theoretic models are being adapted to study the robustness of these networks to various jamming attacks and other malicious behavior.

Cognitive Radio with 2-D Cognition: Dynamic Spectrum vs. Power Accesses

*Project received funding only on the US side

Assoc. Shuguang Cui, Texas A&M Engineering Experiment Station, USA

This project focuses on the fundamental tradeoff between spectrum efficiency and energy efficiency in cognitive radio systems by exploring the correlations across both spectrum and energy domains, in the notions of both frequency holes and energy holes. The considered application scenario is a spectrum sharing system with both legacy and cognitive radios, where the nodes are powered by either smart grids or environment energy harvesters or a mix of two. The three main research objectives are: develop joint 2-D sensing scheme to explore the correlation between frequency holes and energy holes; derive efficiency maximizing resource allocation schemes considering constraints in both energy and spectrum domains; and study performance enhancement mechanisms in the framework of collaborative clouds via node conferencing. Novel interdisciplinary approaches are applied to combine the methods of 2-D statistical signal processing, non-convex optimization, and analytical energy harvesting system modeling to study the unique problem considered for the newly defined cognitive radio systems with 2-D cognition. The project provides both theories and algorithms for energy-efficient operation of future cognitive radio systems with accesses to both spectrum and energy dynamics. The research findings will be incorporated into graduate courses; the results will be disseminated to the community via journal papers and conference presentations

Cross-Layer Modeling and Design of Energy-Aware Cognitive Radio Networks

Prof. Shuvra Bhattacharyya, University of Maryland, USA
Prof. Joseph Cavallaro, Rice University, USA
Prof. Markku Juntti, University of Oulu, Finland
Prof. Mikko Valkama, Tampere University of Technology, Finland
Prof. Olli Silvén, University of Oulu, Finland

The project Cross-Layer Modeling and Design of Energy-Aware Cognitive Radio Networks aims at enhancing the flexibility and design processes required to realize forthcoming cognitive wireless devices. The project considers both flexible baseband and radio frequency processing, architectures, and computation. Also the radio system level algorithms and models for radio resource allocation and spectrum sharing are addressed together with realistic device implementation models. The overall targets and objectives include to enable and provide tools for 1) frequency agility and reconfiguration, 2) energy and bandwidth efficiency, 3) crosslayer optimization from radio resource allocation and spectrum sharing to device level computation, and 5) flexibility and fast design process for cost-efficient device realization.

Global RF Spectrum Opportunity Assessment

Assoc. Prof. Allen MacKenzie, Virginia Polytechnic Institute and State University, USA
Dr. Marja Matinmikko, VTT Technical Research Centre of Finland
Jarkko Paavola, Turku University of Applied Sciences, Finland
Prof. Dennis Roberson, Illinois Institute of Technology, USA
Prof. Juha Röning, University of Oulu, Finland

In order to apply emerging technologies (e.g. dynamic spectrum sharing) to address the wireless spectrum shortage problem, there is a critical need to understand global RF spectrum usage trends. To accomplish this, a three-pronged approach is being pursued: 1) deployment of geographically dispersed, temporally coordinated RF spectrum observatories in multiple U.S. locations, and through international collaboration, in Finland. The spectrum observatories use a common platform generating a single RF spectrum measurement dataset. 2) Development of empirically validated, statistical models of spectrum utilization for different wireless application types based on this dataset. 3) Use of “big data” analytical techniques to mine the dataset to discover temporal and spectral correlations not obvious using traditional approaches. As the models and relationships are refined, they will enable temporal and spectral occupancy predictions to support spectrum sharing for various circumstances and wireless applications. The generation of a high-resolution, multi-location, multi-national spectrum usage dataset using a common, consistent measurement and storage approach is unique and allows direct, unambiguous comparisons of spectrum usage across geographies and demographics. The statistical models of spectrum utilization and the identified similarities and differences between regions and wireless services are unique and inform dynamic spectrum sharing research and related regulatory action with “real-world” data. Importantly, this is the first time that “big data” analytic approaches are being systematically applied to RF utilization data providing new insights motivating novel dynamic spectrum sharing approaches and improved spectrum efficiency.

Joint Adaptation of Multiple Cognitive Systems without Explicit Coordination

Prof. Luiz DaSilva, Virginia Polytechnic Institute and State University, USA
Assoc. Prof.Zhu Han, University of Houston, USA
Dr. Zaheer Khan, University of Oulu, USA
Prof. Matti Latva-aho, University of Oulu, USA

Both the FCC and a recent presidential advisory committee report have recommended the adoption of spectrum sharing technologies, including cognitive radio (CR), to address the rising demand for high-bandwidth wireless service. Under the spectrum sharing paradigm, network entities, such as base stations, access points, and other types of nodes, of multiple wireless systems that operate in the same geographical area can coexist, compete and share resources. Most CR research has focused on how a CR would adapt to the environment in isolation from adaptation decisions of other cognitive systems. However, when multiple systems have to coexist and compete for shared spectrum resources then any adaptation by a CR would trigger adaptations by these other CR systems. In this project, we study multiple autonomous CR systems that are not only cognitive to an ever-changing environment but also need to react to each other’s adaptations. This project explores three aspects in the competition for resource sharing among CR systems: (i) non-homogeneity of resources; (ii) imperfect information about other CR systems’ actions; (iii) discouraging a self-interested CR system from manipulating the agreed spectrum etiquette. We expect the proposed work to have broad impacts on the regulatory environment in the US and Europe, which is currently defining how cognitive systems will be allowed to operate, as well as on standards and on the wireless industry, both of which are starting to adopt dynamic spectrum access capabilities. The research outputs of the project will be disseminated through jointly authored journal articles and papers in top conferences in the area.

Supporting Social Applications in a Hybrid Architecture with CR-Enabled Devices

Dr. Tao Chen, VTT Technical Research Centre of Finland, Finland
Assistant Prof. Wei Cheng, George Washington University, USA
Assoc. Prof. Xiuzhen Cheng, George Washington University, USA
Prof. Yevgeni Koucheryavy, Tampere University of Technology, Finland

The objective of this project is to investigate a number of challenging problems that play critical roles in enhancing the performance of social applications by taking advantage of the benefits brought by integrating cognitive radio networking (CRN) and mobile ad hoc networks (MANET). This research is motivated by the observations of (i) the lack of successful and practical applications of CRN and MANETs, though both have been extensively studied in recent years; and (ii) the benefits of integrating CRN and MANET to launch new and to enhance the performance of existing mobile social applications. In this project, graph theoretical approaches are employed to enable scalable HD video chat, to improve the performance of time-bounded information dissemination, and to enhance the privacy of information sharing among the CR-enabled devices. Moreover, network formation games are exploited to construct social-application-aware network topologies for capacity and performance enhancement; and statistical approaches are adopted to investigate the impact of topology control on social behaviors and vice version. The expected results of this project include novel methodologies and theories to enhance the performance of existing and to enable new mobile social applications. The success of this project will have strong impact on both the theoretical and the practical aspects of social applications in the foreseen hybrid environment of CRN and MANETs. The research findings will be disseminated through high-quality publications as well as presentations in focused workshops and conferences. The project outcomes will provide guidance to and may be adopted by industry for enhancing service availability and integrity.