An interactive visualization of self-organizing radio networks is developed. When the size and complexity of today’s radio networks grows, the need of automated network organizing methods increase to cut down on work, money and mistakes. The automation, however, leads the network operators to lose control over their own network and possible trust issues come along. Instead of giving back control to the operators, which would increase costs and work, Ericsson has suggested creating a visualization making clear that their self-organizing methods work as intended and letting the operator to efficiently explore their own network data. In this thesis project a visualization application is developed allowing the network operator to explore the settings and performance of their network organized by Ericsson’s automatic algorithm called Automatic Neighbor Relations (ANR). The user can interact with the visualization by picking, filtering, and more, to find potential patterns in the data, find bad data values, and see how settings affect the performance of the network. The visualization is built around a map where parameter and performance data is presented. Other visualization components come from the visualization framework GeoAnalytics Visualization (GAV), developed at Linköpings universitet, which also stands as a basis for the entire visualization.

Recently, with the fast development of wireless communications, the radio spectrum becomes a precious natural resource. Many researches and reports reveal the problems of inefficient spectrum utilization. Cognitive Radio (CR) technology is now developing for solving this critical problem. This technology will enable various kinds of wireless systems to look for and connect radio frequency spectrum that the locality leave unused by oneself, to offer the best service to user. The CR will pass in and out the idle frequency band according to the demand while receiving and dispatching the signal, avoid the frequency band that has been already used. In CR network, the objective is to maximize the throughput of secondary users while limiting the probability of colliding with primary users below a prescribed level. In this paper, we consider a distributed secondary networks model where users seek spectrum opportunities independently that overlaying the primary networks to analyze the system performance and the effect to the primary users with the existence of both primary users and secondary users under the cognitive radio networks. In the cognitive system, due to the existence of noise and fading effect, error detection cannot be avoided. Therefore, we made a comparison to the difference of the efficiency among environments of different probability of miss detection. We also propose a random hopping method for all secondary users in system will re-sensing after a random period of time. Hereby, efficiently decreases the ratio of time that influences the primary users by the secondary users, and further research the factor that influences its efficiency.

<p>An interactive visualization of self-organizing radio networks is developed. When the size and complexity of today’s radio networks grows, the need of automated network organizing methods increase to cut down on work, money and mistakes. The automation, however, leads the network operators to lose control over their own network and possible trust issues come along. Instead of giving back control to the operators, which would increase costs and work, Ericsson has suggested creating a visualization making clear that their self-organizing methods work as intended and letting the operator to efficiently explore their own network data.</p><p>In this thesis project a visualization application is developed allowing the network operator to explore the settings and performance of their network organized by Ericsson’s automatic algorithm called Automatic Neighbor Relations (ANR). The user can interact with the visualization by picking, filtering, and more, to find potential patterns in the data, find bad data values, and see how settings affect the performance of the network.</p><p>The visualization is built around a map where parameter and performance data is presented. Other visualization components come from the visualization framework GeoAnalytics Visualization (GAV), developed at Linköpings universitet, which also stands as a basis for the entire visualization.</p>

Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Akyildiz, Ian; Committee Member: Ingram, Mary Ann; Committee Member: Blough, Douglas; Committee Member: Dovrolis, Konstantinos; Committee Member: Li, Ye. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Includes bibliographical references (p. 124-131).

Radio spectrum is becoming scarce resource due to increase in the usage of wireless communication devices. However studies have revealed that most of the allotted spectrum is not used effectively. Given the demand for more bandwidth and the amount of underutilized spectrum, DSA (Dynamic Spectrum Access) networks employing cognitive radios are a solution that can revolutionize the telecommunications industry, significantly changing the way we use spectrum resources, and design wireless systems and services. Cognitive radio has improve the spectral efficiency of licensed radio frequency bands by accessing unused part of the band opportunistically without interfering with a license primary user PU. In this thesis we investigate the effects on the quality of service (QoS) performance of spectrum management techniques for the connection-based channel usage behavior for Secondary user (SU). This study also consider other factors such as spectrum sensing time, spectrum handoff and generally distributed service time and channel contention for different SUs. The preemptive resume priority M/G/1 queuing theory is used to characterize the above mentioned effects. The proposed structure of the model can integrate various system parameters such spectrum sensing, spectrum decision, spectrum sharing and spectrum handoff. / Sajid Mahmood 0046-762788990 Mujeeb Abdullah 0046-760908069

Dynamic spectrum access based on cognitive radio has been regarded as a prospective solution to improve spectrum utilization for wireless communications. By considering the allocation efficiency, fairness, and economic incentives, spectrum marketing has been attracting more and more attentions in recent years. In this thesis, we focus on one of the most effective spectrum marketing methods, i.e., auction approach, in multi-channel cognitive radio networks. After presenting some fundamentals and related works, we begin our discussion in a recall-based auction system where buyers have various service requirements and the seller could recall some sold items after the auction to deal with a sudden increase of its own demand. Both single-winner and multi-winner auctions are designed and analyzed. In addition, we also consider the heterogeneity of radio resource sellers and formulate a framework of combinatorial spectrum auction. With theoretical analyses and simulation results, we show that our proposed algorithms can improve spectrum utilization while satisfy the heterogeneous requirements of different wireless users.

Radio spectrum is scarce in wireless communication. While there is an increasing demand for spectrum due to the substantial growth of wireless communication systems, extensive measurements observe that conventional static spectrum allocation policies introduce significant inefficiency in spectrum utilization. To achieve higher spectrum efficiency, cognitive radio networks have emerged as a revolutionary technology by allowing unlicensed (secondary) users to utilize licensed bands opportunistically without harming licensed (primary) users. In this thesis, we seek to design a new framework that addresses three important issues in cognitive radio networks simultaneously: protection of primary users, incentives for primary networks to share their spectrum and the performance guarantee for secondary users. Leveraging the idea of Value at Risk from economics, in our solution, primary networks maximize their profits by charging secondary users for opportunistic spectrum access, while in the meantime secondary users impose utility constraints to manage the risks and guarantee performance probabilistically.

Radio spectrum is scarce in wireless communication. While there is an increasing demand for spectrum due to the substantial growth of wireless communication systems, extensive measurements observe that conventional static spectrum allocation policies introduce significant inefficiency in spectrum utilization. To achieve higher spectrum efficiency, cognitive radio networks have emerged as a revolutionary technology by allowing unlicensed (secondary) users to utilize licensed bands opportunistically without harming licensed (primary) users. In this thesis, we seek to design a new framework that addresses three important issues in cognitive radio networks simultaneously: protection of primary users, incentives for primary networks to share their spectrum and the performance guarantee for secondary users. Leveraging the idea of Value at Risk from economics, in our solution, primary networks maximize their profits by charging secondary users for opportunistic spectrum access, while in the meantime secondary users impose utility constraints to manage the risks and guarantee performance probabilistically.

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 120-126).