A novel hybrid priority discipline for multi-class secondary users in cognitive radio networks

Fahim, Tamer E.; Zakariya, Ahmed Y.; Rabia, Sherif I.

doi:10.1016/j.simpat.2018.01.007

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…Considering the increasing number of data types in realworld communication networks, many researchers introduced graded cognitive users into CRNs to ensure the QoS of SUs. Just as described in [14,15], this grading mechanism can improve system performance of CRNs effectively. In [16], Tumuluru et al divided the SUs into two classes with different priorities and studied the spectrum switching priorities in the centralized and distributed CRN architectures by using a novel dynamic SAS.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis and Optimization of CRNs Based on Fixed Feedback Probability Mechanism with Two Classes of Secondary Users

Zhao

Liu

2019

Mathematical Problems in Engineering

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In this paper, we conduct a research based on the classified secondary users (SUs). SUs are divided into two categories: higher-priority SU1 and lower-priority SU2, and two types of users generate two types of packets, respectively. Due to the lowest spectrum usage rights of SU2 packets, the SU2 packets’ transmission is easily interrupted by other packets with higher rights. With the purpose of controlling the SU2 packets’ retransmission behavior, we introduce two system parameters, namely, feedback threshold T and feedback probability q. When the amount of SU2 packets in the buffer reaches the feedback threshold T, the interrupted SU2 packets either enter the buffer with probability q for retransmission or leave the channel by probability 1−q, where q is a fixed parameter. We construct a three-dimensional Markov model based on the presented retransmission control mechanism and derive some important performance indicators of SU2 packets based on the one-step transfer probability matrix and steady-state distribution. Then, we analyze the impact of some key parameters on the performance indicators through numerical experiments. Finally, we establish a cost function and use particle swarm optimization algorithm to optimize the feedback threshold and feedback probability.

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Section: Related Workmentioning

confidence: 99%

Performance Analysis and Optimization of CRNs Based on Fixed Feedback Probability Mechanism with Two Classes of Secondary Users

Zhao

Liu

2019

Mathematical Problems in Engineering

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“…Controlling the preemption behavior is another way to ensure the transmission continuity of SUs. In [15], considering hierarchical SUs, a service principle combining preemption and nonpreemption was proposed. When the number of interruptions of low-level SUs reached the threshold, the high-level SUs would no longer preempt the low-level SUs, while the PUs could always preempt any kind of SUs.…”

Section: Introductionmentioning

confidence: 99%

A Multichannel Allocation Strategy Based on Preemption Threshold and Preemption Probability in Cognitive Radio Networks

Zhao

Xiang

2021

Mobile Information Systems

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In traditional multichannel cognitive radio networks (CRNs), users are split into two different priorities. Because of the low priority of secondary users (SUs), SU packets’ transmissions are easily interrupted by primary users (PUs). In this paper, two control parameters, called preemption threshold H and preemption probability q, are used to regulate the preemption behavior of PU packets to improve the transmission performance of SU packets. When all channels in the system are occupied, the preemption behavior of PU packets will be adjusted according to the amount of SU packets that are transmitting in the system. If the amount is larger than H, the recently arrived PU packet either preempts a channel with probability q or leaves the system with probability 1 − q . The central controller manages the system’s channel usage right and determines a series of access behaviors of user packets. Considering the possible imperfect sensing, a discrete-time queueing model is developed with the proposed preemption control mechanism. Then we obtain some performance index expressions of PU and SU packets founded on the system’s state transition matrix and make the corresponding performance figures through numerical experiment. Finally, we construct a system utility function and determine the optimal preemption threshold and preemption probability through the seagull optimization algorithm (SOA). Experimental data show that the proposed mechanism by setting preemption threshold and preemption probability can significantly reduce SU packets’ outage rate and improve SU packets’ throughput rate.

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“…The pre-emption and non-preemption priorities attracted many attentions in the previous works. In this topic, we will investigate the authors' contributions in [16][17][18]. A hybrid approach is exposed in [16], at which low priority SUs are no longer pre-empted by high priority SUs, when their number of interruptions reaches a certain threshold value.…”

mentioning

confidence: 99%

“…In this topic, we will investigate the authors' contributions in [16][17][18]. A hybrid approach is exposed in [16], at which low priority SUs are no longer pre-empted by high priority SUs, when their number of interruptions reaches a certain threshold value. Therefore, the authors showed that the threshold adjustment according to the performance metric provided a promising performance.…”

mentioning

confidence: 99%

Parallelising reception and transmission in queues of secondary users

sad¹

2019

IJECE

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In a cognitive radio network, the secondary users place the packets to be transmitted on a queue to control the order of arrival and to adapt to the network state. Previous conceptions<br />assigned to each secondary user a single queue that contains both received and forwarded packets. Our present article divides the main queue into two sub queues: one to receive the arrived packets and the other to transmit the available packets. This approach reduces the transmission delay due on the one hand; to the shifting of data placed on the single queue, and on the other hand; to the sequential processing of reception and transmission, in theprevious designs. All without increasing the memory capacity of the queue, in the new approach.

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A novel hybrid priority discipline for multi-class secondary users in cognitive radio networks

Cited by 12 publications

References 19 publications

Performance Analysis and Optimization of CRNs Based on Fixed Feedback Probability Mechanism with Two Classes of Secondary Users

Performance Analysis and Optimization of CRNs Based on Fixed Feedback Probability Mechanism with Two Classes of Secondary Users

A Multichannel Allocation Strategy Based on Preemption Threshold and Preemption Probability in Cognitive Radio Networks

Parallelising reception and transmission in queues of secondary users

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