An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Simulation
DRiVE-ing to the Internet: Dynamic Radio for IP services in Vehicular Environments
LCN '00 Proceedings of the 25th Annual IEEE Conference on Local Computer Networks
Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework
IEEE Journal on Selected Areas in Communications
Dynamic spectrum access in WLAN channels: empirical model and its stochastic analysis
TAPAS '06 Proceedings of the first international workshop on Technology and policy for accessing spectrum
Myopic sensing for opportunistic spectrum access using channel correlation
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Modeling and analysis of opportunistic spectrum sharing with unreliable spectrum sensing
IEEE Transactions on Wireless Communications
Nearly optimal power saving policies for mobile stations in wireless networks
Computer Communications
Anderson-darling sensing of existence of unknown signals in a fading channel
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Effective capacity analysis of cognitive radio channels for quality of service provisioning
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A framework for statistical wireless spectrum occupancy modeling
IEEE Transactions on Wireless Communications
A geometric approach to improve spectrum efficiency for cognitive relay networks
IEEE Transactions on Wireless Communications
EURASIP Journal on Advances in Signal Processing - Special issue on advanced signal processing for cognitive radio networks
A non-selfish and distributed channel selection scheme for cognitive radio ad hoc networks
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Effective capacity analysis of cognitive radio channels for quality of service provisioning
IEEE Transactions on Wireless Communications
A linear mixed-effects model of wireless spectrum occupancy
EURASIP Journal on Wireless Communications and Networking
Routing and QoS provisioning in cognitive radio networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Model based bandwidth scavenging for device coexistence in wireless LANs
ICDCN'11 Proceedings of the 12th international conference on Distributed computing and networking
An overview of spectrum occupancy models for cognitive radio networks
NETWORKING'11 Proceedings of the IFIP TC 6th international conference on Networking
Spectrum sensing and power/rate control in CDMA cognitive radio networks
International Journal of Communication Systems
Fast track article: Bandwidth scavenging for device coexistence in pervasive computing systems
Pervasive and Mobile Computing
Assessing the appropriateness of using markov decision processes for RF spectrum management
Proceedings of the 16th ACM international conference on Modeling, analysis & simulation of wireless and mobile systems
Primary weight measure and its support in stochastic routing for dynamic cognitive radio networks
Proceedings of the 1st ACM workshop on Cognitive radio architectures for broadband
Sequential sensing based spectrum handoff in cognitive radio networks with multiple users
Computer Networks: The International Journal of Computer and Telecommunications Networking
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In this paper we consider dynamically sharing the spectrum in the time-domain by exploiting whitespace between the bursty transmissions of a set of users, represented by an 802.11b based wireless LAN (WLAN). Realizing that exploiting the under-utilization of the channel requires a good model of the these users' medium access, we propose a continuous-time semi-Markov model that captures the WLAN's behavior yet remains tractable enough to be used for deriving optimal control strategies within a decision-theoretic framework. Our model is based on actual measurements in the 2.4GHz ISM band using a vector signal analyzer to collect complex baseband data. We explore two different sensing strategies to identify spectrum opportunities depending on whether the primary user's transmission scheme is known. The collected data is used to statistically characterize the idle and busy periods of the channel. Furthermore, we show that a continuous-time semi-Markov model is able to capture the data with good accuracy. The Kolmogorov-Smirnov test is used to validate the model and to assess the model's goodness-of-fit quantitatively. A conclusion summarizes the main results of the paper.