2016
DOI: 10.1049/iet-com.2015.1054
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Improving the quality of service for users in cognitive radio network using priority queueing analysis

Abstract: The usage of the radio spectrum for wireless communication is considered to be inefficient. Therefore, through cognitive radio, unlicensed users can occupy idle spectrum bands without interference with the primary user. Generally, when the arrival rate of licensed users is high, secondary users may starve. In this paper, we propose two models to improve the average total waiting time for the secondary user. They are the M/D/1 model of a primary user delay system with non-pre-emptive priority and pre-emptive pr… Show more

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Cited by 10 publications
(3 citation statements)
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“…While there is a rich literature on CR focusing on spectrum sensing and dynamic spectrum access, there have been few studies on the original vision of CR in being Self-Aware. As claimed in [5], [21] and [22], the original vision of CR goes beyond the spectrum sensing (which is, of course, one of the main components of the cognition cycle) and aims to improve Quality of Service (QoS) [23], Quality of Information (QoI) [24] and optimizing the wireless users' configuration [10]. Several recent studies (as in [10] and [11]) tried to highlight this fact by spotting the light on the original vision of CR and focusing on new functionalities rather than spectrum sensing, encouraged by the recent advances in Artificial Intelligence (AI) methods and their effectiveness in achieving detection, classification and prediction tasks that can empower the CR realization and support it to effectuate the desired functionalities.…”
Section: Related Workmentioning
confidence: 99%
“…While there is a rich literature on CR focusing on spectrum sensing and dynamic spectrum access, there have been few studies on the original vision of CR in being Self-Aware. As claimed in [5], [21] and [22], the original vision of CR goes beyond the spectrum sensing (which is, of course, one of the main components of the cognition cycle) and aims to improve Quality of Service (QoS) [23], Quality of Information (QoI) [24] and optimizing the wireless users' configuration [10]. Several recent studies (as in [10] and [11]) tried to highlight this fact by spotting the light on the original vision of CR and focusing on new functionalities rather than spectrum sensing, encouraged by the recent advances in Artificial Intelligence (AI) methods and their effectiveness in achieving detection, classification and prediction tasks that can empower the CR realization and support it to effectuate the desired functionalities.…”
Section: Related Workmentioning
confidence: 99%
“…Nonetheless, some literatures have considered a CR user priority challenges. In [19][20][21][22][23], a CR user priority in CRNs have been discussed. However, most CR user priority-schemes usually permit higher priority CR users to always interrupt lower priority CR users, leading to frequent SHs and resulting in a degraded network performance, particularly in high traffic networks.…”
Section: Related Workmentioning
confidence: 99%
“…With the era of mobile Internet around the corner, a vast number of data services have poured into the network, claiming more consideration on the burst traffic. Without loss of generality, an M/D/1 queue model with packet generation rate λ and service rate µ per subchannel is taken into account [31], [32]. The probability of a failure transmission of an SUE u l on subchannel n has a similar expression to that of the eavesdropper and from (9) we can get…”
Section: Traffic Modelmentioning
confidence: 99%