44 research outputs found
Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis
(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this[EN] Providing channel access opportunities for new service requests and guaranteeing continuous connections for ongoing flows until service completion are two challenges for service provisioning in wireless networks. Channel failures, which are typically caused by hardware and software failures or/and by intrinsic instability in radio transmissions, can easily result in network performance degradation. In cognitive radio networks (CRNs), secondary transmissions are inherently vulnerable to connection breaks due to licensed users' arrivals as well as channel failures. To explore the advantages of channel reservation on performance improvement in error-prone channels, we propose and analyze a dynamic channel reservation (DCR) algorithm and a dynamic spectrum access (DSA) scheme with three access privilege variations. The key idea of the DCR algorithm is to reserve a dynamically adjustable number of channels for the interrupted services to maintain service retainability for ongoing users or to enhance channel availability for new users. Furthermore, the DCR algorithm is embedded in the DSA scheme enabling spectrum access of primary and secondary users with different access privileges based on access flexibility for licensed shared access. The performance of such a CRN in the presence of homogeneous and heterogeneous channel failures is investigated considering different channel failure and repair rates.The work of V. Pla was supported by the Spanish Ministry of Economy, Industry and Competitiveness under Grant TIN2013-47272-C2-1-R.Balapuwaduge, IAM.; Li, F.; Pla, V. (2018). Dynamic Spectrum Reservation for CR Networks in the Presence of Channel Failures: Channel Allocation and Reliability Analysis. IEEE Transactions on Wireless Communications. 17(2):882-898. https://doi.org/10.1109/TWC.2017.2772240S88289817
Channel Access and Reliability Performance in Cognitive Radio Networks:Modeling and Performance Analysis
Doktorgradsavhandling ved Institutt for Informasjons- og kommunikasjonsteknologi, Universitetet i AgderAccording to the facts and figures published by the international telecommunication
union (ITU) regarding information and communication technology (ICT)
industry, it is estimated that over 3.2 billion people have access to the Internet in
2015 [1]. Since 2000, this number has been octupled. Meanwhile, by the end of
2015, there were more than 7 billion mobile cellular subscriptions in the world, corresponding
to a penetration rate of 97%. As the most dynamic segment in ICT,
mobile communication is providing Internet services and consequently the mobile broadband penetration rate has reached 47% globally. Accordingly, capacity,
throughput, reliability, service quality and resource availability of wireless services
become essential factors for future mobile and wireless communications. Essentially,
all these wireless technologies, standards, services and allocation policies
rely on one common natural resource, i.e., radio spectrum.
Radio spectrum spans over the electromagnetic frequencies between 3 kHz and
300 GHz. Existing radio spectrum access techniques are based on the fixed allocation
of radio resources. These methods with fixed assigned bandwidth for exclusive
usage of licensed users are often not efficient since most of the spectrum
bands are under-utilized, either/both in the space domain or/and in the time domain.
In reality, it is observed that many spectrum bands are largely un-occupied
in many places [2], [3]. For instance, the spectrum bands which are exclusively allocated
for TV broadcasting services in USA remain un-occupied from midnight to
early morning according to the real-life measurement performed in [4]. In addition
to the wastage of radio resources, spectrum under-utilization constraints spectrum
availability for other intended users. Furthermore, legacy fixed spectrum allocation
techniques are not capable of adapting to the changes and interactions in the system,
leading to degraded network performance.
Unlike in the static spectrum allocation, a fraction of the radio spectrum is
allocated for open access as license-free bands, e.g., the industrial, scientific and
medical (ISM) bands (902-928, 2400-2483.5, 5725-5850 MHz). In 1985, the federal
communications commission (FCC) permitted to use the ISM bands for private
and unlicensed occupancy, however, under certain restrictions on transmission
power [5]. Consequently, standards like IEEE 802.11 for wireless local area networks
(WLANs) and IEEE 802.15 for wireless personal area networks (WPAN)
have grown rapidly with open access spectrum policies in the 2.4 GHz and 5 GHz
ISM bands. With the co-existence of both similar and dissimilar radio technologies,
802.11 networks face challenges for providing satisfactory quality of service (QoS).
This and the above mentioned spectrum under-utilization issues motivate the spectrum
regulatory bodies to rethink about more flexible spectrum access for licenseexempt
users or more efficient radio spectrum management. Cognitive radio (CR) is
probably the most promising technology for achieving efficient spectrum utilization
in future wireless networks
Spectrum Efficiency in CRNs using Hybrid Dynamic Channel Reservation and Enhanced Dynamic Spectrum Access
Blocking of new arriving services and dropping of ongoing services are inherent problems in Cognitive Radio Networks (CRNs), which need to be addressed to enhance spectrum efficiency. In particular, Secondary Users (SUs) undergo service degradation in the face of Primary Users (PUs)’ arrivals. In this paper, we present a scheme called Efficient Spectrum Utilization (ESU) that reduces the dropping and blocking probabilities of existing and new services, respectively, to make efficient use of the available spectrum. The scheme divides the available spectrum into reserved and non-reserved bands. The reserved band is dynamically allocated a number of channels from the non-reserved band in order to accommodate those services which face interruptions while operating in the non-reserved band. The scheme renders dynamic access to the available spectrum and facilitates priority-based channel allocation and termination. SUs are divided into low and high priority levels depending on their Quality of Service (QoS) requirements. SUs with low priority level are granted direct access to both the bands to enhance channel utilization. SUs operating in the reserved band with high priority levels are granted uninterruptible status to ensure a certain level of service provisioning to SUs. The proposed ESU scheme is modeled using Continuous Time Markov Chain (CTMC) and mathematical expressions are derived for several QoS parameters. Performance of the proposed scheme is evaluated under various network conditions. Results demonstrate that ESU reasonably improves spectrum efficiency under channel failure in CRNs
Contribution to spectrum management in cognitive radio networks: a cognitive management framework
To overcome the current under-utilization of spectrum resources, the CR (Cognitive Radio) paradigm has gained an increasing interest to perform the so-called Dynamic Spectrum Access (DSA). In this respect, Cognitive Radio networks (CRNs) have been strengthened with cognitive management support to push forward their deployment and commercialization. This dissertation has assessed the relevance of exploiting several cognitive management functionalities in various scenarios and case studies.
Specifically, this dissertation has constructed a generic cognitive management framework, based on the fittingness factor concept, to support spectrum management in CRNs. Under this framework, the dissertation has addressed two of the most promising CR applications, namely an Opportunistic Spectrum Access (OSA) to licensed bands and open sharing of license-exempt bands. In the former application, several strategies that exploit temporal statistical dependence between primary activity/inactivity durations to perform a proactive spectrum selection have been discussed. A set of guidelines to select the most relevant strategy for a given environment have been provided. In the latter application, a fittingness factor-based spectrum selection strategy has been proposed to efficiency exploit the different bands. Several formulations of the fittingness factor have been compared, and their relevance have been assessed under different settings.
Drawing inspiration from these applications, a more general proactive strategy exploiting a characterization of spectrum resources at both the time and frequency domains has been developed to jointly assist spectrum selection (SS) and spectrum mobility (SM) functionalities. Several variants of the proposed strategy, each combining different choices and options of implementation, have been compared to identify which of its components have the most significant impact on performance depending on the working conditions of the CRN. To assess rationality of the proposed strategy with respect to other strategies, a cost-benefit analysis has been conducted to confront the introduced gain in terms of user satisfaction level to the incurred cost in terms of signaling amount.
Finally, the dissertation has conducted an analysis of practicality aspects in terms of robustness to environment uncertainty and applicability to realistic environments. With respect to the former aspect, robustness has been assessed in front of two sources of uncertainty, namely imperfection of the acquisition process and non-stationarity of the environment, and additional functionalities have been developed, when needed, to improve robustness. With respect to the latter, the proposed framework has been applied to a Digital Home (DH) environment to validate the obtained key findings under realistic conditions.Postprint (published version
Contribution to spectrum management in cognitive radio networks: a cognitive management framework
To overcome the current under-utilization of spectrum resources, the CR (Cognitive Radio) paradigm has gained an increasing interest to perform the so-called Dynamic Spectrum Access (DSA). In this respect, Cognitive Radio networks (CRNs) have been strengthened with cognitive management support to push forward their deployment and commercialization. This dissertation has assessed the relevance of exploiting several cognitive management functionalities in various scenarios and case studies.
Specifically, this dissertation has constructed a generic cognitive management framework, based on the fittingness factor concept, to support spectrum management in CRNs. Under this framework, the dissertation has addressed two of the most promising CR applications, namely an Opportunistic Spectrum Access (OSA) to licensed bands and open sharing of license-exempt bands. In the former application, several strategies that exploit temporal statistical dependence between primary activity/inactivity durations to perform a proactive spectrum selection have been discussed. A set of guidelines to select the most relevant strategy for a given environment have been provided. In the latter application, a fittingness factor-based spectrum selection strategy has been proposed to efficiency exploit the different bands. Several formulations of the fittingness factor have been compared, and their relevance have been assessed under different settings.
Drawing inspiration from these applications, a more general proactive strategy exploiting a characterization of spectrum resources at both the time and frequency domains has been developed to jointly assist spectrum selection (SS) and spectrum mobility (SM) functionalities. Several variants of the proposed strategy, each combining different choices and options of implementation, have been compared to identify which of its components have the most significant impact on performance depending on the working conditions of the CRN. To assess rationality of the proposed strategy with respect to other strategies, a cost-benefit analysis has been conducted to confront the introduced gain in terms of user satisfaction level to the incurred cost in terms of signaling amount.
Finally, the dissertation has conducted an analysis of practicality aspects in terms of robustness to environment uncertainty and applicability to realistic environments. With respect to the former aspect, robustness has been assessed in front of two sources of uncertainty, namely imperfection of the acquisition process and non-stationarity of the environment, and additional functionalities have been developed, when needed, to improve robustness. With respect to the latter, the proposed framework has been applied to a Digital Home (DH) environment to validate the obtained key findings under realistic conditions
Reliable and secure low energy sensed spectrum communication for time critical cloud computing applications
Reliability and security of data transmission and access are of paramount importance to enhance the dependability of time critical remote monitoring systems (e.g. tele-monitoring patients, surveillance of smart grid components). Potential failures for data transmissions include wireless channel unavailability and delays due to the interruptions. Reliable data transmission demands seamless channel availability with minimum delays in spite of interruptions (e.g. fading, denial-of-service attacks). Secure data transmissions require sensed data to be transmitted over unreliable wireless channels with sucient security using suitable encryption techniques. The transmitted data are stored in secure cloud repositories. Potential failures for data access include unsuccessful user authentications due to mis-management of digital identities and insucient permissions to authorize situation specic data access requests. Reliable and secure data access requires robust user authentication and context-dependent authorization to fulll situation specic data utility needs in cloud repositories. The work herein seeks to enhance the dependability of time critical remote monitoring applications, by reducing these failure conditions which may degrade the reliability and security of data transmission or access. As a result of an extensive literature survey, in order to achieve the above said security and reliability, the following areas have been selected for further investigations. The enhancement of opportunistic transmissions in cognitive radio networks to provide greater channel availability as opposed to xed spectrum allocations in conventional wireless networks. Delay sensitive channel access methods to ensure seamless connectivity in spite of multiple interruptions in cognitive radio networks. Energy ecient encryption and route selection mechanisms to enhance both secure and reliable data transmissions. Trustworthy digital identity management in cloud platforms which can facilitate ecient user authentication to ensure reliable access to the sensed remote monitoring data. Context-aware authorizations to reliably handle the exible situation specic data access requests. Main contributions of this thesis include a novel trust metric to select non-malicious cooperative spectrum sensing users to reliably detect vacant channels, a reliable delaysensitive cognitive radio spectrum hand-o management method for seamless connectivity and an energy-aware physical unclonable function based encryption key size selection method for secure data transmission. Furthermore, a trust based identity provider selection method for user authentications and a reliable context-aware situation specic authorization method are developed for more reliable and secure date access in cloud repositories. In conclusion, these contributions can holistically contribute to mitigate the above mentioned failure conditions to achieve the intended dependability of the timecritical remote monitoring applications
Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services
This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book
Proactive content caching in future generation communication networks: Energy and security considerations
The proliferation of hand-held devices and Internet of Things (IoT) applications has heightened demand for popular content download. A high volume of content streaming/downloading services during peak hours can cause network congestion. Proactive content caching has emerged as a prospective solution to tackle this congestion problem. In proactive content caching, data storage units are used to store popular content in helper nodes at the network edge. This contributes to a reduction of peak traffic load and network congestion.
However, data storage units require additional energy, which offers a challenge to researchers that intend to reduce energy consumption up to 90% in next generation networks. This thesis presents proactive content caching techniques to reduce grid energy consumption by utilizing renewable energy sources to power-up data storage units in helper nodes. The integration of renewable energy sources with proactive caching is a significant challenge due to the intermittent nature of renewable energy sources and investment costs. In this thesis, this challenge is tackled by introducing strategies to determine the optimal time of the day for content caching and optimal scheduling of caching nodes. The proposed strategies consider not only the availability of renewable energy but also temporal changes in network trac to reduce associated energy costs.
While proactive caching can facilitate the reduction of peak trac load and the integration of renewable energy, cached content objects at helper nodes are often more vulnerable to malicious attacks due to less stringent security at edge nodes. Potential content leakage can lead to catastrophic consequences, particularly for cache-equipped Industrial Internet of Things (IIoT) applications. In this thesis, the concept of \trusted caching nodes (TCNs) is introduced. TCNs cache popular content objects and provide security services to connected links. The proposed study optimally allocates TCNs and selects the most suitable content forwarding paths. Furthermore, a caching strategy is designed for mobile edge computing systems to support IoT task offloading. The strategy optimally assigns security resources to offloaded tasks while satisfying their individual requirements. However, security measures often contribute to overheads in terms of both energy consumption and delay. Consequently, in this thesis, caching techniques have been designed to investigate the trade-off between energy consumption and probable security breaches.
Overall, this thesis contributes to the current literature by simultaneously investigating energy and security aspects of caching systems whilst introducing solutions to relevant research problems
Towards Scalable Design of Future Wireless Networks
Wireless operators face an ever-growing challenge to meet the throughput and processing requirements of billions of devices that are getting connected. In current wireless networks, such as LTE and WiFi, these requirements are addressed by provisioning more resources: spectrum, transmitters, and baseband processors. However, this simple add-on approach to scale system performance is expensive and often results in resource underutilization. What are, then, the ways to efficiently scale the throughput and operational efficiency of these wireless networks? To answer this question, this thesis explores several potential designs: utilizing unlicensed spectrum to augment the bandwidth of a licensed network; coordinating transmitters to increase system throughput; and finally, centralizing wireless processing to reduce computing costs.
First, we propose a solution that allows LTE, a licensed wireless standard, to co-exist with WiFi in the unlicensed spectrum. The proposed solution bridges the incompatibility between the fixed access of LTE, and the random access of WiFi, through channel reservation. It achieves a fair LTE-WiFi co-existence despite the transmission gaps and unequal frame durations. Second, we consider a system where different MIMO transmitters coordinate to transmit data of multiple users.
We present an adaptive design of the channel feedback protocol that mitigates interference resulting from the imperfect channel information. Finally, we consider a Cloud-RAN architecture where a datacenter or a cloud resource processes wireless frames. We introduce a tree-based design for real-time transport of baseband samples and provide its end-to-end schedulability
and capacity analysis. We also present a processing framework that combines real-time scheduling with fine-grained parallelism. The framework reduces processing times by migrating parallelizable tasks to idle compute resources, and thus, decreases the processing deadline-misses at no additional cost.
We implement and evaluate the above solutions using software-radio platforms and off-the-shelf radios, and confirm their applicability in real-world settings.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133358/1/gkchai_1.pd
Cooperative Radio Communications for Green Smart Environments
The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin