Abstract
The design of energy and throughput efficient cognitive radio system holds great importance in the present scenario of wireless communications. The distinctive point of the paper is that it proposes a scheme that optimizes both energy consumption and throughput simultaneously in a cognitive radio network. To do the optimization, an optimal ratio is formulated considering both consumed energy and throughput in the cognitive radio network. Moreover, to make the system more energy efficient, energy harvesting is done. The optimization of throughput and energy consumption in the cognitive radio system is done using swarm intelligence techniques like particle swarm optimization (PSO), human behavior-based particle swarm optimization (HPSO), and particle swarm optimization with aging leader and challengers (ALCPSO). Finally, it is shown that the proposed optimization scheme can improve the energy consumption and throughput in the cognitive radio network as compared to that of the conventional schemes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Spectrum Efficiency Working Group, Report of the Spectrum Efficiency Working Group,” Federal Communications Commission (Tech, Rep, 2002).
J. Mitola, G.Q. Maguire, Cognitive radio: making software radios more personal. IEEE Pers. Commun. 6, 13–18 (1999)
A. J. Gogoi, H. A. Choudhury and K. L. Baishnab, Swarm Intelligence Based Optimization of Energy Consumption in Cognitive Radio Network, vol. 36, no. 3, pp. 2399–2407 (2019)
Y.Pei,A.T. Hoang, Y.C Liang, Sensing-Throughput tradeoff in cognitive radio networks: how frequently should spectrum sensing be carried out? in The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (2007)
L. Li, X. Zhou, H. Xu, G. Li., D. Wang, and A. Soong, Energy-Efficient transmission in cognitive radio networks, in 7th IEEE Consumer Communications and Networking Conference, pp. 1–5 (2010)
S. Huang, H. Chen, Y. Zhang, Optimal power allocation for spectrum sensing and data transmission in cognitive relay networks. IEEE Wirel. Commun. Lett. 1(1), 26–29 (2012)
S. Chatterjee, S.P. Maity, T. Acharya, Energy efficient cognitive radio system for joint spectrum sensing and data transmission. IEEE J. Emerging Sel. Topics Circ. Syst. 4(3), 292–300 (2014)
A. Banerjee, S.P. Maity, S. Roy, On residual energy maximization in energy harvesting cognitive radio network, in IEEE International Conference on Wireless Communications and Networking Conference (WCNC), pp. 1–6 (2017)
A.J. Gogoi, N.M Laskar, C.L Singh, K.L. Baishnab, Throughput Optimization of Cognitive Radio Network Using Swarm Intelligence Techniques, vol. 14, no. 11, p. 443 (2016)
R.A. Rashid et al., Efficient in-band spectrum sensing using swarm intelligence for cognitive radio network. Can. J. Electr. Comput. Eng. 38(2), 106–115 (2015)
P. Verma, B. Singh, Threshold optimization in energy detection scheme for maximizing the spectrum utilization. Proc. Comput. Sci. 33, 191–198 (2016)
A.O. Ercan, M.O. Sunay, Energy sensing strategy optimization for opportunistic spectrum access. IEEE Commun. Lett. 16(6), 828–830 (2012)
P. Yiyang, L. Ying-Chang, Energy-Efficient design of sequential channel sensing in cognitive radio networks: optimal sensing strategy, power allocation, and sensing order. IEEE J. Sel. Areas Commun. IEEE J. 29(8), 1648–1659 (2001)
Y. Wu, D.H.K. Tsang, Energy-efficient spectrum and transmission for cognitive radio system. IEEE Commun. Lett. 15(5), 545–547 (2011)
M. Abdallah, J. Costantine, A.H. Ramadan, C.G. Christodoulou, K.Y. Kabalan, Wide power range RF energy harvesting circuit, in IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2011, pp. 1296–1297
J. Kennedy, Particle swarm optimization, in Encyclopedia of Machine Learning (Springer, US, 2011), pp. 760–766
L. Hao, Human behavior-based particle swarm optimization. Sci. World J. (2014)
W.-N. Chen, Particle swarm optimization with an aging leader and challengers. IEEE Trans. Evol. Comput. 17(2), 241–258 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gogoi, A.J., Gogoi, R., Gogoi, A., Talukdar, D. (2021). Optimization of Energy Consumption and Throughput in Cognitive Radio Network Using Swarm Intelligence Techniques. In: Tavares, J.M.R.S., Chakrabarti, S., Bhattacharya, A., Ghatak, S. (eds) Emerging Technologies in Data Mining and Information Security. Lecture Notes in Networks and Systems, vol 164. Springer, Singapore. https://doi.org/10.1007/978-981-15-9774-9_25
Download citation
DOI: https://doi.org/10.1007/978-981-15-9774-9_25
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9773-2
Online ISBN: 978-981-15-9774-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)