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Recent Advances in Computer Science and Communications

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ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

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Research Article

Energy Harvesting in Cognitive Networks Using Feasible Channel Selection Assignment

Author(s): M. Balasubramanian* and V. Rajamani

Volume 13, Issue 2, 2020

Page: [173 - 182] Pages: 10

DOI: 10.2174/2213275912666190227164215

Price: $65

Abstract

Background: The importance of this paper is to achieve maximum spectrum efficiency and proper channel allotment between Primary and Secondary User. The licensed and unlicensed users gets promoted as the channel allotment is properly carried out. To improve energy capability and spectral proficiency consider energy collecting cognitive radio systems to update both energy feasibility and spectral viability. Energy Harvesting Provides possibility of sharing energy in wireless networks which improves the performance of channel capacity.

Methods: In this paper an Token Passing algorithm is proposed that switches the channels between Primary User and Secondary User. The energy efficiency decision is taken according to when primary user is idle or not. When the primary user is idle the secondary user cannot harvest any energy and when the primary channel is occupied the secondary channel harvest energy from primary user so that the harvested energy will be used by the secondary user during channel allotment. This proposed algorithm provides energy harvesting and spectrum efficiency.

Results: The result shows that the most extraordinary achievable throughput R (eh) of the energy harvesting cognitive radio. The State Transition will move from busy to idle and idle to busy which is represented as S0 and S1. The other parameters are Sensing Energy es, Sampling frequency fs, Primary Signal which accepts a noise SNR γp. As Token Passing Algorithm provides tokens for primary and secondary user it takes lesser time and achieves better throughput than the FDMA and suboptimal algorithm.

Conclusion: This paper achieves the maximum spectrum efficiency and energy harvesting by properly allotting spectrum for both primary and secondary user. The primary user and secondary user and spectrum management perform the channel allotment efficiently through the idle and busy state and Token Passing Algorithm does energy harvesting. An efficient scheme is developed for allocating energy in energy harvesting cognitive radio systems.

Keywords: Cognitive radio, spectrum sensing, energy harvesting, primary user, secondary user, token passing algorithm.

Graphical Abstract

[1]
G. Hani, J.K. Zhang, and X. Mui, "Joint optimization of energy harvesting and detection threshold for energy harvesting cognitive radio networks", IEEE Access, vol. 4, pp. 7212-7222, 2016.
[http://dx.doi.org/10.1109/ACCESS.2016.2616353]
[2]
T. Yucek, and H. Arslan, "“A survey of spectrum sensing algorithms for cognitive radio applications”, IEEE Communication", Surveys Tutorials, vol. 11, no. 1, pp. 116-130, 2009.
[http://dx.doi.org/10.1109/SURV.2009.090109]
[3]
S. Park, and D. Hong, "Achievable throughput of energy harvesting cognitive radio networks", IEEE Trans. Wirel. Commun., vol. 13, no. 2, pp. 1010-1022, 2014.
[http://dx.doi.org/10.1109/TWC.2013.121713.130820]
[4]
R. Deng, J. Chen, C. Yuen, P. Cheng, and Y. Sun, "Energy efficient cooperative spectrum sensing by optimal scheduling in sensor-aided cognitive radio networks", IEEE Trans. Vehicular Technol., vol. 61, no. 2, pp. 716-725, 2012.
[http://dx.doi.org/10.1109/TVT.2011.2179323]
[5]
E.C.Y. Peh, Y.C. Liang, Y.L. Guan, and Y. Zeng, "Cooperative spectrum sensing in cognitive radio networks with weighted decision fusion schemes", IEEE Trans. Wirel. Commun., vol. 9, no. 2, pp. 3838-3847, 2010.
[http://dx.doi.org/10.1109/TWC.2010.092810.100320]
[6]
S. Lee, and R. Zhang, "Cognitive wireless powered network spectrum sharing models and throughput maximization", TCCN, vol. 1, no. 3, pp. 335-346, 2015.
[http://dx.doi.org/10.1109/TCCN.2015.2508028]
[7]
C. Yang, J. Li, M. Guizani, A. Anpalagan, and M. Elkashlan, "Advanced spectrum sharing in 5G cognitive", IEEE Wireless Communications, vol. 23, no. 2, pp. 94-101, 2016.
[8]
X. Lu, P. Wang, D. Niyato, and K. Hossain, "Dynamic spectrum access in cognitive radio networks with RF energy harvesting", IEEE Wirel. Commun., vol. 21, no. 3, pp. 102-110, 2014.
[http://dx.doi.org/10.1109/MWC.2014.6845054]
[9]
S. Lee, R. Zhang, and K. Huang, "Opportunistic wireless energy harvesting in cognitive radio networks", IEEE Trans. Wirel. Commun., vol. 2, no. 9, pp. 4788-4799, 2013.
[http://dx.doi.org/10.1109/TWC.2013.072613.130323]
[10]
F. Yuan, Q.T. Zhang, S. Jin, and H. Zhu, "Optimal harvest-use-store strategy for energy harvesting wireless systems", IEEE Trans. Wirel. Commun., vol. 14, no. 2, pp. 698-710, 2015.
[http://dx.doi.org/10.1109/TWC.2014.2358215]
[11]
M.L. Ku, W. Li, Y. Chen, and K.J.R. Liu, "Advances in energy harvesting communications: Past, present, and future challenges", IEEE Comm. Surv. and Tutor., vol. 18, no. 2, pp. 1384-1412, 2016.
[http://dx.doi.org/10.1109/COMST.2015.2497324]
[12]
N. Pappas, J. Jeon, A. Ephremides, and A. Traganitis, "Optimal utilization of a cognitive shared channel with a rechargeable primary source node", J. Commun. Netw. (Seoul), vol. 14, no. 2, pp. 162-168, 2012.
[http://dx.doi.org/10.1109/JCN.2012.6253064]
[13]
A. Sultan, "Sensing and transmit energy optimization for an energy harvesting cognitive radio", IEEE Wirel. Commun., vol. 1, no. 5, pp. 45-40, 2012.
[14]
S. Park, H. Kim, and D. Hong, "“Cognitive radio networks with energy harvesting”, IEEE T WIREL COMMUN", ISSN, vol. 12, no. 3, pp. 1386-1397, 2013.
[http://dx.doi.org/10.1109/TWC.2013.012413.121009]
[15]
S. Park, and D. Hon, "Optimal spectrum access for energy harvesting cognitive radio networks", IEEE Trans. Wirel. Commun., vol. 12, no. 2, pp. 6166-6179, 2013.
[http://dx.doi.org/10.1109/TWC.2013.103113.130018]
[16]
W. Chung, S. Park, S. Lim, and D. Hong, "Spectrum sensing optimization for energy-harvesting cognitive radio systems", IEEE Trans. Wirel. Commun., vol. 13, no. 5, pp. 2601-2613, 2014.
[http://dx.doi.org/10.1109/TWC.2014.032514.130637]
[17]
S. Park, and D. Hong, "Achievable throughput of energy harvesting cognitive radio networks", IEEE T. Wirel. Commun., vol. 13, no. 2, pp. 1010-1022, 2014.
[http://dx.doi.org/10.1109/TWC.2013.121713.130820]
[18]
H.S. Dhillon, Y. Li, P. Nuggehalli, Z. Pi, and J.G. Andrews, "Fundamentals of heterogeneous cellular networks with energy harvesting", IEEE Trans. Wirel. Commun., vol. 13, no. 5, pp. 2782-2797, 2014.
[http://dx.doi.org/10.1109/TWC.2014.040214.131201]
[19]
D. Niyato, P. Wang, and D.I. Kim, "Channel selection in cognitive radio networks with opportunistic RF energy harvesting", 2014 IEEE International Conference on Communications (ICC), 2014pp. 1555-1560
[20]
S. Yin, E. Zhang, L. Yin, and S. Li, "Optimal saving-sensing-transmitting structure in self-powered cognitive radio systems with wireless energy harvesting", IEEE International Conference on Communications(ICC). Hungary, pp. 1-5, 2013
[http://dx.doi.org/10.1109/ICC.2013.6654965]

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