Abstract
The traditional graph coloring spectrum allocation algorithm takes into account the efficiency in the different spectrum, but in one allocation period, it can only be assigned one spectrum to the corresponding user. Spectrum allocation algorithm based on maximal independent set can assign a spectrum to multiple users simultaneously and does not constitute interference. However, it does not consider the efficiency in the different spectrum as well as the aggregated interference as it allocates one spectrum to multiple users simultaneously. Based on this, we propose an improved maximal weighted independent set-based graph coloring spectrum allocation algorithm in cognitive radio networks. The algorithm allocates spectrum to the nodes with maximal weighted independent set and fully considers the differences in spectral efficiency and interference spectral differences. The simulation results validates the feasibility of the algorithm, and with the usage of power control technology, it improves the spectrum utilization at the premise of ensuring the received signal to interference plus noise ratio at each intended cognitive radio receivers.
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Acknowledgments
Shubin Wang (wangshubin@imu.edu.cn) is the correspondent author and this work was supported by the National Natural Science Foundation of China (61261020), and the Natural Science Foundation of Inner Mongolia, China (2012MS0903), and PetroChina Innovation Foundation (2014D-5006-0603), and the Scientific Research Initial Fund for Higher Talents Program of Inner Mongolia University, China.
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Bao, Y., Wang, S., Yan, B., Liu, K., Meng, F. (2016). Research on Maximal Weighted Independent Set-Based Graph Coloring Spectrum Allocation Algorithm in Cognitive Radio Networks. In: Liang, Q., Mu, J., Wang, W., Zhang, B. (eds) Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 386. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49831-6_27
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DOI: https://doi.org/10.1007/978-3-662-49831-6_27
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