Outage and energy-efficiency analysis of cognitive radio networks: A stochastic approach to transmit antenna selection |
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| Affiliation: | 1. Institute for Information Industry, Taipei, Taiwan;2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;1. Department of Computer Science, University of California, Santa Barbara, USA;2. Electronics and Communications Engineering Dept., Faculty of Engineering, Cairo University, Giza 12613, Egypt;3. Department of Computer Science, University College Cork, Ireland;4. Computer Science and Engineering Dept., The American University in Cairo, AUC Avenue, New Cairo 11835, Egypt;5. Computer and Information Science and Engineering Department, University of Florida, Gainesville, USA |
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| Abstract: | Cognitive radio networks have recently attracted significant research attention owing to their promise for application in future cellular communication. In this light, given the intense power consumption of wireless networks, considerable research is now being directed at designing random cognitive radio networks with enhanced energy efficiency. In this study, we investigate the outage probability and energy efficiency in a cognitive radio network, modeling the locations of the primary users and cognitive users as a Poisson point process. We derive closed-form expressions for the outage probability and energy efficiency with consideration of the probabilities of unoccupied (not utilized by the primary users) channel selection and successful transmission for imperfect detection in an interference-limited environment of cognitive radio network. Furthermore, we propose a transmit antenna selection method for the cognitive transmitter in such networks and accordingly develop closed-form expressions for the outage probability and energy efficiency. The study reported here highlights the importance of combining the capabilities of unoccupied channel selection and successful transmission in cognitive radio networks to achieve optimal performance regarding outage probability and energy efficiency. In terms of energy efficiency, there is an optimal threshold that maximizes the energy efficiency. For implementation in transmit antenna selection, the outage probability can be significantly decreased by increasing the number of transmit antennas, even though the energy efficiency is maximized at the target outage probability. |
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| Keywords: | Cognitive radio network Stochastic geometry Poisson point process Energy efficiency |
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