A Linear Weighted Sum Multi-objective Optimization Algorithm Based on PSO for Wideband Spectrum Sensing

Authors

  • Yonghua Wang
  • Yuehong Li
  • Yiquan Zheng
  • Ting Liang
  • Yuli Fu

DOI:

https://doi.org/10.3991/ijoe.v11i9.5058

Keywords:

Cognitive Radio Sensor Networks, Wideband Spectrum Sensing, Multi-objective Optimization, Particle Swarm Optimization

Abstract


In order to maximize throughput and minimize interference of the wideband spectrum sensing problem in OFDM cognitive radio sensor networks, a linear weighted sum multi-objective algorithm based on the Particle Swarm Optimization is proposed. The multi-objective optimization advantages of Particle Swarm Optimization are utilized to solve the optimal threshold vector of the spectrum sensing problem in OFDM cognitive radio sensor networks. So the network can get a larger throughput under the condition of small interference. The simulation results show that the proposed algorithm can make larger throughput while keeping the interference is smaller in OFDM cognitive radio sensor networks. Thus the spectrum resources are used more effectively.

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Published

2015-10-29

How to Cite

Wang, Y., Li, Y., Zheng, Y., Liang, T., & Fu, Y. (2015). A Linear Weighted Sum Multi-objective Optimization Algorithm Based on PSO for Wideband Spectrum Sensing. International Journal of Online and Biomedical Engineering (iJOE), 11(9), pp. 9–16. https://doi.org/10.3991/ijoe.v11i9.5058