Enabling Dynamic Spectrum Allocation in Cognitive Radio Networks

The last decade has witnessed the proliferation of innovative wireless technologies, such asWi-Fi, wireless mesh networks, operating in unlicensed bands. Due to the increasing popularity and the wide deployments of these technologies, the unlicensed bands become overcrowded. The wireless devices operating in these bands interfere with each other and hurt the overall performance. To support fast growths of wireless technologies, more spectrums are required. However, as most "prime" spectrum has been allocated, there is no spectrum available to expand these innovative wireless services. Despite the general perception that there is an actual spectral shortage, the recent measurement results released by the FCC (Federal Communications Commission) show that on average only 5% of the spectrum from 30MHz to 30 GHz is used in the US. This indicates that the inefficient spectrum usage is the root cause of the spectral shortage problem. Therefore, this dissertation is focused on improving spectrum utilization and efficiency in tackling the spectral shortage problem to support ever-growing user demands for wireless applications. This dissertation proposes a novel concept of dynamic spectrum allocation, which adaptively divides available spectrum into non-overlapping frequency segments of different bandwidth considering the number of potentially interfering transmissions and the distribution of traffic load in a local environment. The goals are (1) to maximize spectrum efficiency by increasing parallel transmissions and reducing co-channel interferences, and (2) to improve fairness across a network by balancing spectrum assignments. Since existing radio systems offer very limited flexibility, cognitive radios, which can sense and adapt to radio environments, are exploited to support such a dynamic concept. We explore two directions to improve spectrum efficiency by adopting the proposed dynamic allocation concept. First, we build a cognitive wireless system called KNOWS to exploit unoccupied frequencies in the licensed TV bands. KNOWS is a hardware-software platform that includes new radio hardware, a spectrum-aware MAC (medium access control) protocol and an algorithm for implementing the dynamic spectrum allocation. We show that KNOWS accomplishes a remarkable 200% throughput gain over systems based on fixed allocations in common cases. Second, we enhance Wireless LANs (WLANs), the most popular network setting in unlicensed bands, by proposing a dynamic channelization structure and a scalable MAC design. Through analysis and extensive simulations, we show that the new channelization structure and the scalable MAC design improve not only network capacity but per-client fairness by allocating channels of variable width for access points in a WLAN. As a conclusion, we believe that our proposed concept of dynamic spectrum allocation lays down a solid foundation for building systems to efficiently use the invaluable spectrum resource

Improving the Performance of Wireless LANs

This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids

Spectrum Sharing Methods in Coexisting Wireless Networks

Radio spectrum, the fundamental basis for wireless communication, is a finite resource. The development of the expanding range of radio based devices and services in recent years makes the spectrum scarce and hence more costly under the paradigm of extensive regulation for licensing. However, with mature technologies and with their continuous improvements it becomes apparent that tight licensing might no longer be required for all wireless services. This is from where the concept of utilizing the unlicensed bands for wireless communication originates. As a promising step to reduce the substantial cost for radio spectrum, different wireless technology based networks are being deployed to operate in the same spectrum bands, particularly in the unlicensed bands, resulting in coexistence. However, uncoordinated coexistence often leads to cases where collocated wireless systems experience heavy mutual interference. Hence, the development of spectrum sharing rules to mitigate the interference among wireless systems is a significant challenge considering the uncoordinated, heterogeneous systems. The requirement of spectrum sharing rules is tremendously increasing on the one hand to fulfill the current and future demand for wireless communication by the users, and on the other hand, to utilize the spectrum efficiently. In this thesis, contributions are provided towards dynamic and cognitive spectrum sharing with focus on the medium access control (MAC) layer, for uncoordinated scenarios of homogeneous and heterogeneous wireless networks, in a micro scale level, highlighting the QoS support for the applications. This thesis proposes a generic and novel spectrum sharing method based on a hypothesis: The regular channel occupation by one system can support other systems to predict the spectrum opportunities reliably. These opportunities then can be utilized efficiently, resulting in a fair spectrum sharing as well as an improving aggregated performance compared to the case without having special treatment. The developed method, denoted as Regular Channel Access (RCA), is modeled for systems specified by the wireless local resp. metropolitan area network standards IEEE 802.11 resp. 802.16. In the modeling, both systems are explored according to their respective centrally controlled channel access mechanisms and the adapted models are evaluated through simulation and results analysis. The conceptual model of spectrum sharing based on the distributed channel access mechanism of the IEEE 802.11 system is provided as well. To make the RCA method adaptive, the following enabling techniques are developed and integrated in the design: a RSS-based (Received Signal Strength based) detection method for measuring the channel occupation, a pattern recognition based algorithm for system identification, statistical knowledge based estimation for traffic demand estimation and an inference engine for reconfiguration of resource allocation as a response to traffic dynamics. The advantage of the RCA method is demonstrated, in which each competing collocated system is configured to have a resource allocation based on the estimated traffic demand of the systems. The simulation and the analysis of the results show a significant improvement in aggregated throughput, mean delay and packet loss ratio, compared to the case where legacy wireless systems coexists. The results from adaptive RCA show its resilience characteristics in case of dynamic traffic. The maximum achievable throughput between collocated IEEE 802.11 systems applying RCA is provided by means of mathematical calculation. The results of this thesis provide the basis for the development of resource allocation methods for future wireless networks particularly emphasized to operate in current unlicensed bands and in future models of the Open Spectrum Alliance

A Survey on Modality Characteristics, Performance Evaluation Metrics, and Security for Traditional and Wearable Biometric Systems

Biometric research is directed increasingly towards Wearable Biometric Systems (WBS) for user authentication and identification. However, prior to engaging in WBS research, how their operational dynamics and design considerations differ from those of Traditional Biometric Systems (TBS) must be understood. While the current literature is cognizant of those differences, there is no effective work that summarizes the factors where TBS and WBS differ, namely, their modality characteristics, performance, security and privacy. To bridge the gap, this paper accordingly reviews and compares the key characteristics of modalities, contrasts the metrics used to evaluate system performance, and highlights the divergence in critical vulnerabilities, attacks and defenses for TBS and WBS. It further discusses how these factors affect the design considerations for WBS, the open challenges and future directions of research in these areas. In doing so, the paper provides a big-picture overview of the important avenues of challenges and potential solutions that researchers entering the field should be aware of. Hence, this survey aims to be a starting point for researchers in comprehending the fundamental differences between TBS and WBS before understanding the core challenges associated with WBS and its design

Modelling and performability evaluation of Wireless Sensor Networks

This thesis presents generic analytical models of homogeneous clustered Wireless Sensor Networks (WSNs) with a centrally located Cluster Head (CH) coordinating cluster communication with the sink directly or through other intermediate nodes. The focus is to integrate performance and availability studies of WSNs in the presence of sensor nodes and channel failures and repair/replacement. The main purpose is to enhance improvement of WSN Quality of Service (QoS). Other research works also considered in this thesis include modelling of packet arrival distribution at the CH and intermediate nodes, and modelling of energy consumption at the sensor nodes. An investigation and critical analysis of wireless sensor network architectures, energy conservation techniques and QoS requirements are performed in order to improve performance and availability of the network. Existing techniques used for performance evaluation of single and multi-server systems with several operative states are investigated and analysed in details. To begin with, existing approaches for independent (pure) performance modelling are critically analysed with highlights on merits and drawbacks. Similarly, pure availability modelling approaches are also analysed. Considering that pure performance models tend to be too optimistic and pure availability models are too conservative, performability, which is the integration of performance and availability studies is used for the evaluation of the WSN models developed in this study. Two-dimensional Markov state space representations of the systems are used for performability modelling. Following critical analysis of the existing solution techniques, spectral expansion method and system of simultaneous linear equations are developed and used to solving the proposed models. To validate the results obtained with the two techniques, a discrete event simulation tool is explored. In this research, open queuing networks are used to model the behaviour of the CH when subjected to streams of traffic from cluster nodes in addition to dynamics of operating in the various states. The research begins with a model of a CH with an infinite queue capacity subject to failures and repair/replacement. The model is developed progressively to consider bounded queue capacity systems, channel failures and sleep scheduling mechanisms for performability evaluation of WSNs. Using the developed models, various performance measures of the considered system including mean queue length, throughput, response time and blocking probability are evaluated. Finally, energy models considering mean power consumption in each of the possible operative states is developed. The resulting models are in turn employed for the evaluation of energy saving for the proposed case study model. Numerical solutions and discussions are presented for all the queuing models developed. Simulation is also performed in order to validate the accuracy of the results obtained. In order to address issues of performance and availability of WSNs, current research present independent performance and availability studies. The concerns resulting from such studies have therefore remained unresolved over the years hence persistence poor system performance. The novelty of this research is a proposed integrated performance and availability modelling approach for WSNs meant to address challenges of independent studies. In addition, a novel methodology for modelling and evaluation of power consumption is also offered. Proposed model results provide remarkable improvement on system performance and availability in addition to providing tools for further optimisation studies. A significant power saving is also observed from the proposed model results. In order to improve QoS for WSN, it is possible to improve the proposed models by incorporating priority queuing in a mixed traffic environment. A model of multi-server system is also appropriate for addressing traffic routing. It is also possible to extend the proposed energy model to consider other sleep scheduling mechanisms other than On-demand proposed herein. Analysis and classification of possible arrival distribution of WSN packets for various application environments would be a great idea for enabling robust scientific research

Use of Inferential Statistics to Design Effective Communication Protocols for Wireless Sensor Networks

This thesis explores the issues and techniques associated with employing the principles of inferential statistics to design effective Medium Access Control (MAC), routing and duty cycle management strategies for multihop Wireless Sensor Networks (WSNs). The main objective of these protocols are to maximise the throughput of the network, to prolong the lifetime of nodes and to reduce the end-to-end delay of packets over a general network scenario without particular considerations for specific topology configurations, traffic patterns or routing policies. WSNs represent one of the leading-edge technologies that have received substantial research efforts due to their prominent roles in many applications. However, to design effective communication protocols for WSNs is particularly challenging due to the scarce resources of these networks and the requirement for large-scale deployment. The MAC, routing and duty cycle management protocols are amongst the important strategies that are required to ensure correct operations of WSNs. This thesis makes use of the inferential statistics field to design these protocols; inferential statistics was selected as it provides a rich design space with powerful approaches and methods. The MAC protocol proposed in this thesis exploits the statistical characteristics of the Gamma distribution to enable each node to adjust its contention parameters dynamically based on its inference for the channel occupancy. This technique reduces the service time of packets and leverages the throughput by improving the channel utilisation. Reducing the service time minimises the energy consumed in contention to access the channel which in turn prolongs the lifetime of nodes. The proposed duty cycle management scheme uses non-parametric Bayesian inference to enable each node to determine the best times and durations for its sleeping durations without posing overheads on the network. Hence the lifetime of node is prolonged by mitigating the amount of energy wasted in overhearing and idle listening. Prolonging the lifetime of nodes increases the throughput of the network and reduces the end-to-end delay as it allows nodes to route their packets over optimal paths for longer periods. The proposed routing protocol uses one of the state-of-the-art inference techniques dubbed spatial reasoning that enables each node to figure out the spatial relationships between nodes without overwhelming the network with control packets. As a result, the end-to-end delay is reduced while the throughput and lifetime are increased. Besides the proposed protocols, this thesis utilises the analytical aspects of statistics to develop rigorous analytical models that can accurately predict the queuing and medium access delay and energy consumption over multihop networks. Moreover, this thesis provides a broader perspective for design of communication protocols for WSNs by casting the operations of these networks in the domains of the artificial chemistry discipline and the harmony search optimisation algorithm