Delay Sensitive Communications over Cognitive Radio Networks

Supporting the quality of service of unlicensed users in cognitive radio networks is very challenging, mainly due to dynamic resource availability because of the licensed users' activities. In this paper, we study the optimal admission control and channel allocation decisions in cognitive overlay networks in order to support delay sensitive communications of unlicensed users. We formulate it as a Markov decision process problem, and solve it by transforming the original formulation into a stochastic shortest path problem. We then propose a simple heuristic control policy, which includes a threshold-based admission control scheme and and a largest-delay-first channel allocation scheme, and prove the optimality of the largest-delay-first channel allocation scheme. We further propose an improved policy using the rollout algorithm. By comparing the performance of both proposed policies with the upper-bound of the maximum revenue, we show that our policies achieve close-to-optimal performance with low complexities.Comment: 11 pages, 8 figure

Spectrum leasing in cognitive radio networks: a survey

Cognitive Radio (CR) is a dynamic spectrum access approach, in which unlicensed users (or secondary users, SUs) exploit the underutilized channels (or white spaces) owned by the licensed users (or primary users, PUs). Traditionally, SUs are oblivious to PUs, and therefore the acquisition of white spaces is not guaranteed. Hence, a SU must vacate its channel whenever a PU reappears on it in an unpredictablemanner,which may affect the SUs’ network performance. Spectrumleasing has been proposed to tackle the aforementioned problem through negotiation between the PU and SU networks, which allows the SUs to acquire white spaces for a guaranteed period of time.Through spectrumleasing, the PUs and SUs enhance their network performances, and additionally PUs maximize their respective monetary gains. Numerous research efforts have been made to investigate the CR, whereas the research into spectrum leasing remains at its infancy. In this paper, we present a comprehensive review on spectrum leasing schemes in CR networks by highlighting some pioneering approaches and discuss the gains, functionalities, characteristics, and challenges of spectrum leasing schemes along with the performance enhancement in CR networks. Additionally, we discuss various open issues in order to spark new interests in this research area

Delay sensitive and power-aware SMDP-based connection admission control mechanism in cognitive radio sensor networks

© 2017 Elsevier B.V. Due to the opportunistically resource usage of users in cognitive radio sensor networks (CRSNs), the availability of network resources is highly variable. Therefore, admission control is an essential mechanism to manage the traffic of cognitive radio users in order to satisfy the quality of service (QoS) requirements of applications. In this study, a connection admission control (CAC) mechanism is introduced to satisfy the requirements of delay sensitivity and power consumption awareness. This proposed mechanism is modeled through a semi Markov decision process (SMDP) and a linear programming problem is derived with the aim of obtaining the optimal policy to control the traffic of CRSNs and achieving maximum reward. The number of required channels at each network state is estimated through a graph coloring approach. An end to end delay constraint is defined for the optimization problem which is inspired from Kleinrock independence approximation. Furthermore, a power-aware weighting method is proposed for this mechanism. We conduct different simulation-based scenarios to investigate the performance of the proposed mechanism. The experimental results demonstrate the efficiency of this SMDP-based mechanism in comparison to the last CAC mechanism in CRSNs

Efficient Identification and Utilization of Spectrum Opportunities in Cognitive Radio Networks.

There has been an exponential increase in spectrum demands due to new emerging wireless services and applications, making it harder to find unallocated spectrum bands for future usage. This potential resource scarcity is rooted at inefficient utilization of spectrum under static spectrum allocation. Therefore, a new concept of dynamic spectrum access (DSA) has been proposed to opportunistically utilize the legacy spectrum bands by cognitive radio (CR) users. Cognitive radio is a key technology for alleviating this inefficient spectrum utilization, since it can help discover spectrum opportunities (or whitespaces) in which legacy spectrum users do not temporarily use their assigned spectrum bands. In a DSA network, it is crucial to efficiently identify and utilize the whitespaces. We address this issue by considering spectrum sensing and resource allocation. Spectrum sensing is to discover spectrum opportunities and to protect the legacy users (or incumbents) against harmful interference from the CR users. In particular, sensing is an interaction between PHY and MAC layers where in the PHY-layer signal detection is performed, and in the MAC-layer spectrum sensing is scheduled and spectrum sensors are coordinated for collaborative sensing. Specifically, we propose an efficient MAC-layer sensing scheduling algorithm that discovers spectrum opportunities as much as possible for better quality-of-service (QoS), and as fast as possible for seamless service provisioning. In addition, we propose an optimal in-band spectrum sensing algorithm to protect incumbents by achieving the detectability requirements set by regulators (e.g., FCC) while incurring minimal sensing overhead. For better utilization of discovered spectrum opportunities, we pay our attention to resource allocation in the secondary spectrum market where legacy license holders temporarily lease their own spectrum to secondary wireless service providers (WSPs) for opportunistic spectrum access by CR users. In this setting, we investigate how a secondary WSP can maximize its profit by optimally controlling the admission and eviction of its customers (i.e., CR users). In addition, we also focus on the price and quality competition between co-located WSPs where they contend for enticing customers by providing more competitive service fee while leasing the channels with best matching quality.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78741/1/hyoilkim_1.pd

Quality of Service Provisioning for Heterogeneous Services in Cognitive Radio-enabled Internet of Things

IEEE The Internet of Things (IoT) is a network of interconnected objects, in which every object in the world seeks to communicate and exchange information actively. This exponential growth of interconnected objects increases the demand for wireless spectrum. However, providing wireless channel access to every communicating object while ensuring its guaranteed quality of service (QoS) requirements is challenging and has not yet been explored, especially for IoT-enabled mission-critical applications and services. Meanwhile, Cognitive Radio-enabled Internet of Things (CR-IoT) is an emerging field that is considered the future of IoT. The combination of CR technology and IoT can better handle the increasing demands of various applications such as manufacturing, logistics, retail, environment, public safety, healthcare, food, and drugs. However, due to the limited and dynamic resource availability, CR-IoT cannot accommodate all types of users. In this paper, we first examine the availability of a licensed channel on the basis of its primary users' activities (e.g., traffic patterns). Second, we propose a priority-based secondary user (SU) call admission and channel allocation scheme, which is further based on a priority-based dynamic channel reservation scheme. The objective of our study is to reduce the blocking probability of higher-priority SU calls while maintaining a sufficient level of channel utilization. The arrival rates of SU calls of all priority classes are estimated using a Markov chain model, and further channels for each priority class are reserved based on this analysis. We compare the performance of the proposed scheme with the greedy non-priority and fair proportion schemes in terms of the SU call-blocking probability, SU call-dropping probability, channel utilization, and throughput. Numerical results show that the proposed priority scheme outperforms the greedy non-priority and fair proportion schemes

Resource Management in Cognitive Radio Networks

In the last decade, the world has witnessed rapid increasing applications of wireless networks. However, with the fixed spectrum allocation policy that has been used since the beginning of the spectrum regulation to assign different spectrum bands to different wireless applications, it has been observed that most of the allocated spectrum bands are underutilized. Therefore, if these bands can be opportunistically used by new emerging wireless networks, the spectrum scarcity can be resolved. Cognitive Radio (CR) is a revolutionary and promising technology that can identify and then exploit the spectrum opportunities. In Cognitive Radio Networks (CRNs), the spectrum can be utilized by two kinds of users: Primary Users (PUs) having exclusive licenses to use certain spectrum bands for specific wireless applications, and Secondary Users (SUs) having no spectrum licenses but seeking for any spectrum opportunities. The SUs can make use of the licensed unused spectrum if they do not make any harmful interference to the PUs. However, the variation of the spectrum availability over the time and locations, due to the coexistence with the PUs, and the spread of the spectrum opportunities over wide spectrum bands create a unique trait of the CRNs. This key trait poses great challenges in different aspects of the radio resource management in CRNs such as the spectrum sensing, spectrum access, admission control, channel allocation, Quality-of-Service (QoS) provisioning, etc. In this thesis, we study the resource management of both single-hop and multi-hop CRNs. Since most of the new challenges in CRNs can be tackled by designing an efficient Medium Access Control (MAC) framework, where the solutions of these challenges can be integrated for efficient resource management, we firstly propose a novel MAC framework that integrates a kind of cooperative spectrum sensing method at the physical layer into a cooperative MAC protocol considering the requirements of both the SUs and PUs. For spectrum identification, a computationally simple but efficient sensing algorithm is developed, based on an innovative deterministic sensing policy, to assist each sensing user for identifying the optimum number of channels to sense and the optimum sensing duration. We then develop an admission control scheme and channel allocation policy that can be integrated in the proposed MAC framework to regulate the number of sensing users and number of access users; therefore, the spectrum identification and exploitation can be efficiently balanced. Moreover, we propose a QoS-based spectrum allocation framework that jointly considers the QoS provisioning for heterogeneous secondary Real-Time (RT) and Non-Real Time (NRT) users with the spectrum sensing, spectrum access decision, and call admission control. We analyze the proposed QoS-based spectrum allocation framework and find the optimum numbers of the RT and NRT users that the network can support. Finally, we introduce an innovative user clustering scheme to efficiently manage the spectrum identification and exploitation in multi-hop ad hoc CRNs. We group the SUs into clusters based on their geographical locations and occurring times and use spread spectrum techniques to facilitate using one frequency for the Common Control Channels (CCCs) of the whole secondary network and to reduce the co-channel interference between adjacent clusters by assigning different spreading codes for different clusters. The research results presented in this thesis contribute to realize the concept of the CRNs by developing a practical MAC framework, spectrum sensing, spectrum allocation, user admission control, and QoS provisioning for efficient resource management in these promising networks

To Avoid the Unimaginable : Neoliberalism and the Struggle for American Democracy Since the 1960s

This study explores the structural, tactical, and strategic legacies of 1960s era activism on subsequent American social movements. Specifically, this project explains how the ascendancy of neoliberal policies on both national and global scales has dramatically shifted opportunities for social change. Case studies for these developments include Earth First! and the punk rock movement during the 1980s, the Student-Farmworker Alliance in the 1990s, and a variety of anti-war organizations in the 2000s