111 research outputs found

    Performance analysis of 4G wireless networks using system level simulator

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    Doutoramento em Engenharia ElectrotĂ©cnicaIn the last decade, mobile wireless communications have witnessed an explosive growth in the user’s penetration rate and their widespread deployment around the globe. In particular, a research topic of particular relevance in telecommunications nowadays is related to the design and implementation of mobile communication systems of 4th generation (4G). 4G networks will be characterized by the support of multiple radio access technologies in a core network fully compliant with the Internet Protocol (all IP paradigms). Such networks will sustain the stringent quality of service (QoS) requirements and the expected high data rates from the type of multimedia applications (i.e. YouTube and Skype) to be available in the near future. Therefore, 4G wireless communications system will be of paramount importance on the development of the information society in the near future. As 4G wireless services will continue to increase, this will put more and more pressure on the spectrum availability. There is a worldwide recognition that methods of spectrum managements have reached their limit and are no longer optimal, therefore new paradigms must be sought. Studies show that most of the assigned spectrum is under-utilized, thus the problem in most cases is inefficient spectrum management rather spectrum shortage. There are currently trends towards a more liberalized approach of spectrum management, which are tightly linked to what is commonly termed as Cognitive Radio (CR). Furthermore, conventional deployment of 4G wireless systems (one BS in cell and mobile deploy around it) are known to have problems in providing fairness (users closer to the BS are more benefited relatively to the cell edge users) and in covering some zones affected by shadowing, therefore the use of relays has been proposed as a solution. To evaluate and analyse the performances of 4G wireless systems software tools are normally used. Software tools have become more and more mature in recent years and their need to provide a high level evaluation of proposed algorithms and protocols is now more important. The system level simulation (SLS) tools provide a fundamental and flexible way to test all the envisioned algorithms and protocols under realistic conditions, without the need to deal with the problems of live networks or reduced scope prototypes. Furthermore, the tools allow network designers a rapid collection of a wide range of performance metrics that are useful for the analysis and optimization of different algorithms. This dissertation proposes the design and implementation of conventional system level simulator (SLS), which afterwards enhances for the 4G wireless technologies namely cognitive Radios (IEEE802.22) and Relays (IEEE802.16j). SLS is then used for the analysis of proposed algorithms and protocols.FC

    Synoptic analysis techniques for intrusion detection in wireless networks

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    Current system administrators are missing intrusion alerts hidden by large numbers of false positives. Rather than accumulation more data to identify true alerts, we propose an intrusion detection tool that e?ectively uses select data to provide a picture of ?network health?. Our hypothesis is that by utilizing the data available at both the node and cooperative network levels we can create a synoptic picture of the network providing indications of many intrusions or other network issues. Our major contribution is to provide a revolutionary way to analyze node and network data for patterns, dependence, and e?ects that indicate network issues. We collect node and network data, combine and manipulate it, and tease out information about the state of the network. We present a method based on utilizing the number of packets sent, number of packets received, node reliability, route reliability, and entropy to develop a synoptic picture of the network health in the presence of a sinkhole and a HELLO Flood attacker. This method conserves network throughput and node energy by requiring no additional control messages to be sent between the nodes unless an attacker is suspected. We intend to show that, although the concept of an intrusion detection system is not revolutionary, the method in which we analyze the data for clues about network intrusion and performance is highly innovative

    Enhancing spectrum utilization through cooperation and cognition in wireless systems

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections."February 2013." Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 201-217).We have seen a proliferation of wireless technologies and devices in recent years. The resulting explosion of wireless demand has put immense pressure on available spectrum. Improving spectrum utilization is therefore necessary to enable wireless networks to keep up with burgeoning demand. This dissertation presents a cognitive and cooperative wireless architecture that significantly enhances spectrum utilization. Specifically, it introduces four new systems that embody a cross-layer design for cognition and cooperation. The first system, SWIFT, is a cognitive cross technology solution that enables wideband devices to exploit higher layer network semantics to adaptively sense which portions of the spectrum are occupied by unknown narrowband devices, and weave the remaining unoccupied spectrum bands into a single high-throughput wideband link. Second, FARA is a cooperative system that enables multi-channel wireless solutions like 802.11 to dynamically use all available channels for all devices in a performance-aware manner by using information from the physical layer and allocating to each link the frequency bands that show the highest performance for that link. SourceSync, the third system, enables wireless nodes in last-hop and wireless mesh networks to cooperatively transmit synchronously in order to exploit channel diversity and increase reliability. Finally, MegaMIMO enables wireless throughput to scale linearly with the number of transmitters by enabling multiple wireless transmitters to transmit simultaneously in the same frequency bands to multiple wireless receivers without interfering with each other. The systems in this dissertation demonstrate the practicality of cognitive and cooperative wireless systems to enable spectrum sharing. Further, as part of these systems, we design several novel primitives - adaptive spectrum sensing, time alignment, frequency synchronization, and distributed phase-coherent transmission, that can serve as fundamental building blocks for wireless cognition and cooperation. Finally, we have implemented all four systems described in this dissertation, and evaluated them in wireless testbeds, demonstrating large gains in practice.by Hariharan Shankar Rahul.Ph.D

    Improving the Performance of Wireless LANs

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    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

    Bootstrapping Cognitive Radio Networks

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    Cognitive radio networks promise more efficient spectrum utilization by leveraging degrees of freedom and distributing data collection. The actual realization of these promises is challenged by distributed control, and incomplete, uncertain and possibly conflicting knowledge bases. We consider two problems in bootstrapping, evolving, and managing cognitive radio networks. The first is Link Rendezvous, or how separate radio nodes initially find each other in a spectrum band with many degrees of freedom, and little shared knowledge. The second is how radio nodes can negotiate for spectrum access with incomplete information. To address the first problem, we present our Frequency Parallel Blind Link Rendezvous algorithm. This approach, designed for recent generations of digital front-ends, implicitly shares vague information about spectrum occupancy early in the process, speeding the progress towards a solution. Furthermore, it operates in the frequency domain, facilitating a parallel channel rendezvous. Finally, it operates without a control channel and can rendezvous anywhere in the operating band. We present simulations and analysis on the false alarm rate for both a feature detector and a cross-correlation detector. We compare our results to the conventional frequency hopping sequence rendezvous techniques. To address the second problem, we model the network as a multi-agent system and negotiate by exchanging proposals, augmented with arguments. These arguments include information about priority status and the existence of other nodes. We show in a variety of network topologies that this process leads to solutions not otherwise apparent to individual nodes, and achieves superior network throughput, request satisfaction, and total number of connections, compared to our baselines. The agents independently formulate proposals based upon communication desires, evaluate these proposals based upon capacity constraints, create ariii guments in response to proposal rejections, and re-evaluate proposals based upon received arguments. We present our negotiation rules, messages, and protocol and demonstrate how they interoperate in a simulation environment

    A dynamic distributed multi-channel TDMA slot management protocol for ad hoc networks

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    With the emergence of new technologies and standards for wireless communications and an increase in application and user requirements, the number and density of deployed wireless ad hoc networks is increasing. For deterministic ad hoc networks, Time-Division Multiple Access (TDMA) is a popular medium access scheme, with many distributed TDMA scheduling algorithms being proposed. However, with increasing traffic demands and the number of wireless devices, proposed protocols are facing scalability issues. Besides, these protocols are achieving suboptimal spatial spectrum reuse as a result of the unsolved exposed node problem. Due to a shortage of available spectrum, a shift from fixed spectrum allocation to more dynamic spectrum sharing is anticipated. For dynamic spectrum sharing, improved distributed scheduling protocols are needed to increase spectral efficiency and support the coexistence of multiple co-located networks. Hence, in this paper, we propose a dynamic distributed multi-channel TDMA (DDMC-TDMA) slot management protocol based on control messages exchanged between one-hop network neighbors and execution of slot allocation and removal procedures between sender and receiver nodes. DDMC-TDMA is a topology-agnostic slot management protocol suitable for large-scale and high-density ad hoc networks. The performance of DDMC-TDMA has been evaluated for various topologies and scenarios in the ns-3 simulator. Simulation results indicate that DDMC-TDMA offers near-optimal spectrum utilization by solving both hidden and exposed node problems. Moreover, it proves to be a highly scalable protocol, showing no performance degradation for large-scale and high-density networks and achieving coexistence with unknown wireless networks operating in the same wireless domain

    Flexible Spectrum Assignment for Local Wireless Networks

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    In this dissertation, we consider the problem of assigning spectrum to wireless local-area networks (WLANs). In line with recent IEEE 802.11 amendments and newer hardware capabilities, we consider situations where wireless nodes have the ability to adapt not only their channel center-frequency but also their channel width. This capability brings an important additional degree of freedom, which adds more granularity and potentially enables more efficient spectrum assignments. However, it also comes with new challenges; when consuming a varying amount of spectrum, the nodes should not only seek to reduce interference, but they should also seek to efficiently fill the available spectrum. Furthermore, the performances obtained in practice are especially difficult to predict when nodes employ variable bandwidths. We first propose an algorithm that acts in a decentralized way, with no communication among the neighboring access points (APs). Despite being decentralized, this algorithm is self-organizing and solves an explicit tradeoff between interference mitigation and efficient spectrum usage. In order for the APs to continuously adapt their spectrum to neighboring conditions while using only one network interface, this algorithm relies on a new kind of measurement, during which the APs monitor their surrounding networks for short durations. We implement this algorithm on a testbed and observe drastic performance gains compared to default spectrum assignments, or compared to efficient assignments using a fixed channel width. Next, we propose a procedure to explicitly predict the performance achievable in practice, when nodes operate with arbitrary spectrum configurations, traffic intensities, transmit powers, etc. This problem is notoriously difficult, as it requires capturing several complex interactions that take place at the MAC and PHY layers. Rather than trying to find an explicit model acting at this level of generality, we explore a different point in the design space. Using a limited number of real-world measurements, we use supervised machine-learning techniques to learn implicit performance models. We observe that these models largely outperform other measurement-based models based on SINR, and that they perform well, even when they are used to predict performance in contexts very different from the context prevailing during the initial set of measurements used for learning. We then build a second algorithm that uses the above-mentioned learned models to assign the spectrum. This algorithm is distributed and collaborative, meaning that neighboring APs have to exchange a limited amount of control traffic. It is also utility-optimal -- a feature enabled both by the presence of a model for predicting performance and the ability of APs to collaboratively take decisions. We implement this algorithm on a testbed, and we design a simple scheme that enables neighboring APs to discover themselves and to implement collaboration using their wired backbone network. We observe that it is possible to effectively gear the performance obtained in practice towards different objectives (in terms of efficiency and/or fairness), depending on the utility functions optimized by the nodes. Finally, we study the problem of scheduling packets both in time and frequency domains. Such ways of scheduling packets have been made possible by recent progress in system design, which make it possible to dynamically tune and negotiate the spectrum band [...
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