An Energy-Efficient Model of Random Cognitive Radio Network: Rayleigh-Lognormal Environment
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An Energy‑Efficient Model of Random Cognitive Radio Network: Rayleigh‑Lognormal Environment Saifur Rahman Sabuj1 · Tabassum E Nur2 · Masanori Hamamura3
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Motivated by the current demand for improvements in transmission rate and energy efficiency of random wireless cellular networks, we investigate the theoretical model of random cognitive radio network in Rayleigh-lognormal fading environment. In such a network, we derive an analytical expression for the connection probability, transmission rate, and energy efficiency of a secondary network in a single-tier downlink scenario, considering the probabilities of unoccupied channel selection and of successful transmission, where source-destination pairs are randomly located according to Poisson point processes. Moreover, we approach the problem of optimization of transmission rate and energy efficiency using a required connection probability constraint to improve the system performance. Our numerical results indicate that there exists an optimal combination of transmission power and secondary transmitter density where transmission rate and energy efficiency are maximized. Keywords Cognitive radio network · Energy efficiency · Stochastic geometry · Rayleighlognormal fading
Some parts of this paper were presented at the IEEE CCNC conference, 2017 [22]. * Saifur Rahman Sabuj [email protected] Tabassum E Nur [email protected] Masanori Hamamura hamamura.masanori@kochi‑tech.ac.jp 1
Department of Electronics and Control Engineering, Hanbat National University, Daejeon, South Korea
2
Department of Electrical and Electronic Engineering, Bangladesh University, Dhaka, Bangladesh
3
Graduate School of Engineering, Kochi University of Technology, Kami, Japan
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1 Introduction The exchange of information over wireless cellular networks has grown exponentially in recent years. Consequently, research has investigated the scarcity of radio frequency spectrum which remains fixed for a particular wireless network with an ever-increasing number of users. Within that research trend, the concept of cognitive radio (CR) network has been introduced; this targets the enhancement of the efficiency of utilized spectrum by accommodating unlicensed users in an intelligent way that does not cause any interruption in service of licensed users [6, 26]. On the other hand, the design of modern wireless cellular networks has moved from deterministic to random, with the emergence of different types of base stations (BSs), cell patterns and configurations to increase user capacity and enhance spectral efficiency [8, 9]. Utilization of energy is a crucial consideration in the design of random wireless networks. Due to the increase in the number of wireless applications and in the volume of wireless data, the wireless network sector has contributed substantially to CO2 emissions and to global energy consumption. A recent study reported that energy consumption by cellular
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