Projects 2016-2017

Data-guided Resource Management for Dense Heterogeneous Networks

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

Device-to-Device Communications at Millimeter-Wave Frequencies

Prof. Katsuyuki Haneda, Aalto University, Finland
Prof. Andreas Molisch, University of Southern California, USA

The project investigates device-to-device (D2D) communications at millimeter-wave (mm-wave) frequencies. These systems have the promise of extremely high data rates because of the large available bandwidth in the mm-wave bands, and high spectral efficiency because of the high spatial frequency reuse in D2D networks. However, such systems also face challenges because of the inherent properties of the propagation channels that govern the behavior of such systems. In this project we aim to develop insights into the channel behavior through new measurements and models, and use those to develop improved systems that actively exploit the channel properties. We will also assess the system capacity and reliability of setups that combine communications at cellular/WiFi frequencies with D2D links at mm-wave frequencies. Our work will concentrate on 1) channel measurements and models, where we develop a new dynamic directional channel sounder, novel deterministic channel prediction method, and channel models that incorporate the correlations between mm-wave and microwave frequencies; 2) neighbor discovery, where we exploit the sparsity of the neighbor graph and multipath channels for efficient neighbor discovery. We also improve Zig-Zag schemes by exploiting correlation between channels at the different frequency bands; 3) beamforming and beam tracking, where we focus on combined analogue and digital beam forming; 4) performance of holistic systems, where we investigate the system capacity and outage probability of systems that combine mm-wave D2D and microwave D2D and cellular links.

Exploiting Social Structure for Cooperative Mobile Networking

Dr. Ulrico Celentano, University of Oulu, Finland
Dr. Tao Chen, VTT Technical Research Centre of Finland, Finland
Dr. Natalia Ermolova, Aalto University, Finland
Dr. Lei Yang, Arizona State University, USA
Prof. Junshan Zhang, Arizona State University, USA

In this project, we will investigate social-aware approaches to enable shared spectrum access, cooperative spectrum sensing, data mining, information dissemination, and intelligent device-to-device (D2D) communications, via exploiting the social structure among mobile users. By combining theoretical studies with practical applications, the project aims to integrate social elements into the design of cooperative mobile networks, so as to enrich the evolution of future mobile networks. Such social-structure-based cooperation among mobile devices will enable self-organizing networking, and be promising to improve spectral efficiency and network capacity of mobile networks. The outcomes from the project will be new knowledge, protocol and algorithm design, and performance analysis on social information integrated mobile communications.

Future Uncoordinated Small-Cell Networks Using Reconfigurable Antennas

Assoc. Prof. Kapil Dandekar, Drexel University, USA
Prof. Aarne Mämmelä, VTT Technical Research Centre of Finland, Finland
Dr. Harri Saarnisaari, University of Oulu, Finland
Mikko Valkama, Tampere University of Technology, Finland
Assoc. Prof. Steven Weber, Drexel University, USA
Assoc. Prof. Alexander Wyglinski, Worchester Polytechnic Institute, USA

In a dense wireless network, like small cells, performance is constrained heavily by the interference. The interference can be mitigated using directional antenna like reconfigurable antenna systems whose radiation characteristics can be adapted in response to the needs of the overlying small-cellular system. We will demonstrate how intelligent deployment of reconfigurable antenna systems in small-cell base stations can improve cellular network capacity, while coexisting with the overlaying macro network, by mitigating interference and allowing for densification of mobile users in a given spatial deployment. The research for this includes three parts. Algorithm and System Design – A vital component of this overall system design is the development of efficient and effective analytical tools and algorithms for downlink transmission, focusing on directional network design, algorithms for directionality selection, and base station user association. Antenna and Transceiver Design – We will adapt reconfigurable metamaterial and Alford loop antenna designs to provide new, compact reconfigurable antenna architectures with both beam steering along with DOA estimation and variable beam width capabilities. Testbed Implementation – The cornerstone of the proposed research is a fully implemented, programmable across-the-stack SDR platform with integrated reconfigurable antennas.

Heterogeneous Resource Allocation for Hierarchical Software-defined Radio Access Networks at the Edge

Dr. Mehdi Bennis, University of Oulu, Finland
Dr. Xianfu Chen, VTT Technical Research Centre of Finland, Finland
Assoc. Prof. Zhu Han, University of Houston, USA
Prof. Guoliang Xue, Arizona State University, USA

This project targets the development of a feasible and effective SDN-at-the-Edge type of architecture for large-scale RANs. The high centralization as well as the limited-capacity backhauls makes it difficult to perform centralized control plane functions on a large network scale. For a cellular network with very dense BS deployment, a number of clusters (i.e., multiple controllers) have to be dynamically set up or configured. In this way, BSs in each cluster are managed by a local controller in a programmable way, such that the communications within a single cluster are well coordinated. However, due to the frequency reuse, control plane decisions in different clusters are still coupled. Beyond that, future cellular network designs should be user-centered. That is, wireless resources are adaptively distributed across the network according to terminal users’ traffic characteristics, which requires a highly flexible software-defined architecture that is fitted to a dynamic networking scenario. The proposed research addresses many of the fundamental problems and challenges in creating a HSDRAN, with emphasis on a novel architecture design and network-wide resource allocation strategies. The project involves a complementary mix of network architecture design, theoretical modeling and analysis, and experimental simulations quantifying performance benefits of the developed protocols. In particular, the diverse expertise of our collaborative institutions in several research areas including network science, wireless communications, and machine learning allows us to investigate the interplay of these elements at different network layers from multiple perspectives.

Joint Network and Market Design for Content and Spectrum Sharing in Future 5G Networks

Adj. Prof. Petri Ahokangas, University of Oulu, Finland
Assoc. Prof. Abouzeid, Alhussein, Rensselaer Polytechnic Institute, USA
Prof. Hesham El Gamal, Ohio State University, USA
Assoc. Prof. Atilla Eryilmaz, Ohio State University, USA
Prof. Matti Latva-aho, University of Oulu, Finland

Future wireless networks, as represented by the 5G concept and associated set of future standards, are expected to meet a diverse range of new requirements, leverage technological and regulatory advancements, and overcome the spectrum scarcity challenges. However, the success of a new technology is not only determined by its technical strengths but also by an intricate interplay between the economic considerations of the consumers/users, competing service and content providers, and governing/regulating public agencies. This project explores new wireless spectrum and content sharing concepts from both technological and business perspectives for future 5G networks. The overall objective of this project is to investigate and develop fundamental technological and business aspects of new spectrum/content sharing for 5G networks, that potentially could lead to significant technical performance
improvements as well as revolutionize future wireless markets and operators business.
The intellectual merits of the proposed work can be described around its four research thrusts: (i) new and potentially transformative business models for future 5G markets, and in particular new business models for mobile operators, (ii) in-network dynamic spectrum and content sharing and pricing mechanisms under various possible future architectures that take into account the new business models and bridge the gap between technological and economic considerations, (iii) collaborative content distribution that could lead to win-win relationships for wireless stakeholders, and (iv) intelligent content caching for improved performance for different network and business scenarios. The unique aspects of the research plan are that it views content and spectrum as two resource dimensions that can be explored for future wireless networks, and that it stresses business and economic implications of various architectural choices, with formal models that capture technology performance as well as business/economic considerations.

Message and CSI Sharing for Cellular Interference Management with Backhaul Constraints

Prof. Markku Juntti, University of Oulu, Finland
Prof. Venugopal V. Veeravalli, University of Illinois at Urbana-Champaign, USA

The focus of this proposed project is to explore the potential benefits of exploiting these developments through the lens of information theoretic models of single hop wireless networks. The proposed project involves three research thrusts. The first is to study the fundamental limits of the rate of communication in large interference networks with a rate-limited backhaul that allows for sharing messages between base stations in both downlink and uplink scenarios. The second is to relax the perfect global channel knowledge assumption, and consider the achievable gains in settings with imperfect, local, or no channel knowledge at base stations and mobile users. Finally, we plan to study dynamic network models.

Sequential Inference and Learning for Agile Spectrum Use

Prof. Visa Koivunen, Aalto University, Finland
Prof. H. Vincent Poor, Princeton University, USA
Prof. Lifeng Lai, Worcester Polytechnic Institute, USA

Lack of availability of radio spectrum for wireless communication purposes is becoming a serious problem. Instead of the spectrum being actually fully in use, the scarcity of useful radio spectrum is mainly due to static allocation and rigid regulation of the spectrum use. Flexible spectrum use aims at exploiting under-utilized spectrum resources. Available spectrum opportunities may be non-contiguous, scattered over a large bandwidth, and are available locally and for a limited period of time due to the highly dynamic nature of wireless transmissions. There is a pressing need to understand how to discover, assess and utilize the time-frequency-location varying spectrum resources efficiently and with a minimal delay. It is critical to access identified idle spectrum in an agile manner.
In this project, we propose to design sequential inference and learning algorithms for the agile spectrum access when the state of the spectrum varies rapidly. The key advantage of sequential algorithms, as compared to block-wise algorithms, is that these sequential algorithms typically lead to significantly reduced decision delays. Although sequential analysis techniques have found great success in other areas, other than sequential detection, sequential analysis tools’ applications in wireless communications have been limited. Motivated by our initial success in designing sequential algorithms for spectrum sensing and cognitive radio networks, the overarching goal of this project is to design sequential inference and learning algorithms for agile spectrum utilization. In particular, we propose to employ advanced sequential inference and learning methods for the following three interconnected yet increasingly sophisticated and demanding tasks: 1) to employ sequential reinforcement learning and sequential inference algorithms to design sensing policies for rapid spectrum opportunities discovery; 2) to design sequential algorithms for fast and accurate spectrum quality assessment; and 3) to build, maintain and exploit an interference map of the area where our network operates and represent it as a spatial potential field.
This project is done in co-operation with Princeton University, NJ, USA, Worcester Polytechnic Institute, MA, USA and Aalto University, Finland.

Ubiquitous Video over Dynamic Spectrum

Prof. Mung Chiang, Princeton University, USA
Assist. Prof. Mario Di Francesco, Aalto University, Finland
Prof. Jussi Kangasharju, University of Helsinki, Finland

This project makes cognitive radio networks (CRNs) suitable as a platform to deliver ubiquitous wireless video. It takes a flexible approach that is applicable to diverse regulations across national boundaries and specifically targets mobile devices. The research addresses the major challenges affecting video delivery over CRNs: the highly-varying nature of the channel; the presence of misbehaving users; the dynamic availability of heterogeneous resources. It finally creates a cognitive phone, i.e., a smartphone with cognitive radio capabilities, to bridge the gap between the technologies behind CRNs and real applications. The project builds on two major research thrusts. First, it adopts spectrum crowdsensing as a means to model the availability of whitespace at multiple scales and support long-lived communications. Such an approach enables novel solutions to accurately characterize the channel and enforce the policies established by the communication authorities. Second, it leverages adaptive mechanisms as foundations to efficiently deliver video streams to end users. These mechanisms are implemented through streaming protocols and components in the network infrastructure that can deliver video content with a target quality of experience. The research addresses the challenges generated by the explosive growth of mobile devices and its consequences on both content distribution and load on the wireless infrastructure. The project also integrates synergistic activities between the United States and Finland in education, industry collaboration and entrepreneurship. In the long term, the research will allow the creation of novel value-added services related to streaming data for mobile wireless devices. For more information on the project, please visit the project website.

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, Finland
Prof. Matti Latva-aho, University of Oulu, Finland

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.