ABSTRACT
The development of the Dynamic Spectrum Access/Cognitive Radio (DSA/CR) technology can significantly benefit from the availability of realistic models able to accurately capture and reproduce the statistical properties of spectrum usage in real wireless communication systems. Relying on field measurements of real systems, this paper analyzes the joint time-frequency statistical properties of spectrum usage and develops adequate models describing the observed characteristics. Based on such models, a sophisticated method is also proposed to generate artificial spectrum data for simulation or other purposes. The proposed method is able to accurately reproduce the statistical time-frequency characteristics of spectrum usage in real systems.
- I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty. NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comp. Networks, 50(13):2127--2159, 2006. Google ScholarDigital Library
- M. C. Jones. Kumaraswamy's distribution: A beta-type distribution with some tractability advantages. Statistical Methodology, 6(1):70--81, Jan. 2009.Google ScholarCross Ref
- P. Kumaraswamy. A generalized probability density function for double-bounded random processes. Journal of Hydrology, 46(1--2):79--88, Mar. 1980.Google ScholarCross Ref
- M. López-Benítez and F. Casadevall. Methodological aspects of spectrum occupancy evaluation in the context of cognitive radio. European Trans. on Telecomms., 21(8):680--693, 2010.Google ScholarCross Ref
- M. López-Benítez and F. Casadevall. Discrete-time spectrum occupancy model based on markov chain and duty cycle models. In Proc. IEEE 5th Int'l. Symp. on Dynamic Spectrum Access Networks (DySPAN 2011), pages 1--10, May 2011.Google ScholarCross Ref
- M. López-Benítez and F. Casadevall. Modeling and simulation of time-correlation properties of spectrum use in cognitive radio. In Proc. 6th Int'l. ICST Conf. on Cognitive Radio Oriented Wireless Networks (CrownCom 2011), June 2011.Google ScholarCross Ref
- M. López-Benítez and F. Casadevall. A radio spectrum measurement platform for spectrum surveying in cognitive radio. In Proc. 7th Int'l. ICST Conf. on Testbeds and Research Infrastructures for the Development of Networks and Communities (TridentCom 2011), pages 1--16, Apr. 2011.Google Scholar
- M. A. McHenry et al. Spectrum occupancy measurements. Technical report, Shared Spectrum Company, 2004--2005.Google Scholar
- A. Papoulis and S. U. Pillai. Probability, random variables, and stochastic processes. McGraw-Hill, Boston, 4 edition, 2002.Google Scholar
- H. Urkowitz. Energy detection of unknown deterministic signals. Proceedings of the IEEE, 55(4):523--531, Apr. 1967.Google ScholarCross Ref
Index Terms
- Modeling and simulation of joint time-frequency properties of spectrum usage in cognitive radio
Recommendations
An overview of spectrum occupancy models for cognitive radio networks
NETWORKING'11: Proceedings of the IFIP TC 6th international conference on NetworkingThe Dynamic Spectrum Access (DSA) paradigm based on the Cognitive Radio (CR) technology has emerged as a promising solution to conciliate the existing conflicts between spectrum demand growth and current spectrum underutilization without changes to the ...
Dynamic spectrum access in underlay cognitive radio system with SINR constraints
WiCOM'09: Proceedings of the 5th International Conference on Wireless communications, networking and mobile computingHow to improve the spectrum utility of the unlicensed uses (secondary users) without interfering the licensed spectrum holders' usage becomes a key issue in the cognitive radio system. In this paper, we consider an underlay cognitive radio system in ...
Dynamically optimized spatiotemporal prioritization for spectrum sensing in cooperative cognitive radio
In this paper, an enhanced cooperative, statistics-driven spectrum sensing algorithm, called Dynamically Optimized Spatiotemporal Prioritization (DOSP), is developed for improving spectrum sensing efficiency in the media access control (MAC) layer of ...
Comments