scholarly journals An Improved Scheduling Algorithm for Cognitive Radio Networks under Different Traffic Patterns

2021 ◽  
Vol 1964 (4) ◽  
pp. 042014
Author(s):  
P Shyamala Bharathi
Author(s):  
Ju Bin Song ◽  
Zhu Han

In cognitive radio networks a secondary user needs to estimate the primary users' air traffic patterns so as to optimize its transmission strategy. In this chapter, the authors describe a nonparametric Bayesian method for identifying traffic applications, since the traffic applications have their own distinctive air traffic patterns. In the proposed algorithm, the collapsed Gibbs sampler is applied to cluster the air traffic applications using the infinite Gaussian mixture model over the feature space of the packet length, the packet inter-arrival time, and the variance of packet lengths. The authors analyze the effectiveness of their proposed technique by extensive simulation using the measured data obtained from the WiMax networks.


Author(s):  
Sylwia Romaszko ◽  
Petri Mähönen

In the case of Opportunistic Spectrum Access (OSA), unlicensed secondary users have only limited knowledge of channel parameters or other users' information. Spectral opportunities are asymmetric due to time and space varying channels. Owing to this inherent asymmetry and uncertainty of traffic patterns, secondary users can have trouble detecting properly the real usability of unoccupied channels and as a consequence visiting channels in such a way that they can communicate with each other in a bounded period of time. Therefore, the channel service quality, and the neighborhood discovery (NB) phase are fundamental and challenging due to the dynamics of cognitive radio networks. The authors provide an analysis of these challenges, controversies, and problems, and review the state-of-the-art literature. They show that, although recently there has been a proliferation of NB protocols, there is no optimal solution meeting all required expectations of CR users. In this chapter, the reader also finds possible solutions focusing on an asynchronous channel allocation covering a channel ranking.


Author(s):  
Omar Sweileh ◽  
Mohamed S. Hassan ◽  
Hasan S. Mir ◽  
Mahmoud H. Ismail

In this article, an opportunistic inter-frame spectrum scheduler that maximizes the throughput of cognitive radio networks over a span of multiple time-slots is proposed. An optimization problem is formulated to find the optimum inter-frame scheduler while taking into account the switching delay, the primary user (PU) activity, historical information on the PU behavior, the channel quality as well as the secondary user (SU) status. Simulation results show that the proposed inter-frame scheduler significantly improved the overall aggregate throughput and average switching delay of the cognitive radio network when compared to the values obtained when scheduling is done on a slot-by-slot basis.


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