Stochastic Analysis of Throughput of Cognitive Radio Network

Publication

[1] Barnwal S, Choi YS, and Kim D. Stochastic Optimization of Throughput of Cognitive Radio Network with Multiple Primary Users. In International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT) 2019, pp. 354-358. IEEE. doi: https://www.doi.org/10.1109/ICEECCOT46775.2019.9114729

Overview

We consider a Cognitive Radio Network(CRN) with multiple Primary Users(PUs). Since the PUs hold license over their frequencies, they demand to have a Quality of Service Constraint imposed on any component of the network using it. These frequencies are available to the Secondary User(SU), provided it meets their Outage Probability Constraints.

In this project, we explored various stochastic optimization algorithms and designed the one most suitable for throughput maximization. A unique way of combining the underlay and interweave techniques probabilistically is proposed. The effect of Imperfect Spectrum Sensing, PU Traffic Load, sensing time, the order of sensing, interference channel gains, and number of PUs, on the throughput has been investigated.

The work will be much useful in determining the ratio in which to use the underlay and interweave techniques, given the parameters of the CRN, such as achievable sensing accuracy, and the sensing time.

Manuscript

Duration: May - July 2017

Status: Completed

Members: Simran Barnwal, Yun Sung Choi, Prof. Dongwoo Kim

Note: The project was started during the summer break of 2017. This 10-weeks long internship at Hanyang University ERICA, South Korea was funded by the Hanyang Summer Internship Programme.

CRN System model

Results of Statiscal Analysis

Throughput of Secondary User against Transmission Probability showing (i) the behaviour of throughput with changing False Alarm Probability (ii) the values the optimal Transmission Probability can take (iii) the optimal transmission probability(p*) in each case

Throughput of Secondary User against Transmission Probability showing (i) the behaviour of throughput with changing Detection Probability (ii) the values the optimal Transmission Probability can take (iii) the optimal transmission probability(p*) in each case

Throughput of Secondary User against ratio of mean of interference channel gain between PU Transmitter and SU Reciever (mean of |h_p,s 1|^2/mean of |h_p,s 2|^2) showing (i) a better performance if the PU having the smaller mean of interference channel gain is sensed first (ii) the throughput of SU at various transmission probabilities

Optimal Throughput of Secondary User against Number of Primary Users showing (i) the best number of PUs for a given sensing_time/Time_frame ratio (ii) the behaviour of the Optimal Throughput with changing number of PUs (iii) the corresponding sensing_time/Time_frame values

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