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

Abstract

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.

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

“…, respectively. According to the Early Arrival System (EAS) assumption, each service completion of user packets occurs at the end of the slot (t − , t), and each arrival occurs at the beginning of the slot (t, t + ) [17]. We mark PU packets' amount at time t + as P t and SU packets' amount at time t + as S t and call P t system level and S t system phase.…”

A PSD Maps Estimation Algorithm for Underlay Cognitive Radio Networks Based on the Convolutional Neural Network

“…e cognitive radio (CR) technology is a promising technology to solve the spectrum resource scarcity problem. On the basis of sensing and adjusting the working parameters, the secondary users or unlicensed users can dynamically access the spectrum holes, i.e., the unused radio resources, which are initially owned by the primary users or licensed users [1,2].…”