Power and Contention Control Scheme: As a Good Candidate for Interference Modeling in Cognitive Radio Network

Abstract

Due to the ever growing need for spectrum, the cognitive radio (CR) has been proposed to improve the radio spectrum utilization. In this scenario, the secondary users (SU) are permitted to share spectrum with the licensed primary users (SU) with a strict condition that they do not cause harmful interference to the cognitive network. In this work, we have proposed an interference model for cognitive radio network that utilizes power or contention control interference management schemes. We derived the probability density function (PDF) with the power control scheme, where the power of transmission of the CR transmitter is guided by the power control law and also with contention control scheme that has a fixed transmission power for all CR transmitter controlled by a contention control protocol. This protocol makes a decision on which CR transmitter can transmit at any point in time. In this work, we have shown that power and contention control schemes are good candidates for interference modeling in cognitive radio system. The impact of the unknown location of the primary receiver on the resulting interference generated by the CR transmitters was investigated and the results shows that the challenges of the hidden primary receivers lead to higher CR-primary interference in respect to higher mean and variance. Finally, the presented results show power control and the contention control scheme are good candidates in reducing the interference generated by the cognitive radio network.

Authors and Affiliations

Ireyuwa Igbinosa, Olutayo Oyerinde, Viranjay Srivastava, Stanley Mneney

Keywords

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  • EP ID EP90234
  • DOI 10.14569/IJACSA.2015.061018
  • Views 65
  • Downloads 0

How To Cite

Ireyuwa Igbinosa, Olutayo Oyerinde, Viranjay Srivastava, Stanley Mneney (2015). Power and Contention Control Scheme: As a Good Candidate for Interference Modeling in Cognitive Radio Network. International Journal of Advanced Computer Science & Applications, 6(10), 127-135. https://europub.co.uk/articles/-A-90234