The traffic on cellular wireless networks is growing rapidly, mainly due to the support for high quality, data centric services like high speed internet, video, or other broadband applications. In addition, usually multiple cellular operators are sharing the available radio spectrum by applying interference management mechanisms. Besides the increase of the transfer speed in such a networks the above mentioned applications during their service time don't utilize the available channel uniformly. Considering those services as primary users, the above behaviour allows to join secondary users using the same frequency at the free time slots. Novel technologies, like Cognitive Radio (CR) could improve the efficiency of these networks by increasing the primary user satisfaction besides the possibility of secondary user services. In this paper our main goal is to express the opportunity to use the spectrum as a shared resource and allocate it both for primary and secondary users. As an example a local wireless network will serve as a primary channel. The ON/OFF statistical properties for this channel are derived from real measurements. After aggregation multiple primary user activity processes, a more sophisticated partitioned Markov model will be fitted to the aggregated process. In order to simulate the various secondary user activity, several ON/OFF Markov models with user behaviour specific parameter set is used. Secondary users are taken in account as internet users; therefore this model is parameterized from latest internet usage statistics, extended with parameter variability functionality. It will be proved with simulations that the aggregated activity-free length distribution of primary users gives the opportunity for secondary users to join to the same network. Our method is a general tool; it is intended to implement in the Cognitive Manager (CM) subsystem to support the decision mechanisms of the resource and spectrum management system.
[1]
Janne Riihijarvi,et al.
Modelling Primary System Activity in Dynamic Spectrum Access Networks by Aggregated ON/OFF-Processes
,
2009,
2009 6th IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops.
[2]
Jean-Yves Chouinard,et al.
Estimation of Gilbert's and Fritchman's models parameters using the gradient method for digital mobile radio channels
,
1988
.
[3]
Bruce D. Fritchman,et al.
A binary channel characterization using partitioned Markov chains
,
1967,
IEEE Trans. Inf. Theory.
[4]
Balasubramaniam Natarajan,et al.
Modeling and Forecasting Secondary User Activity in Cognitive Radio Networks
,
2008,
2008 Proceedings of 17th International Conference on Computer Communications and Networks.
[5]
Sami Akin,et al.
Performance Analysis of Cognitive Radio Systems under QoS Constraints and Channel Uncertainty
,
2010,
IEEE Transactions on Wireless Communications.
[6]
Shuguang Cui,et al.
Power and Rate Control with Dynamic Programming for Cognitive Radios
,
2007,
IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.
[7]
Qing Zhao,et al.
Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game
,
2009,
IEEE Transactions on Communications.