Statistical information in terms of spectrum occupancy is useful for the efficient and smart dynamic spectrum sharing, and it can be obtained by long-term, broadband, and wide-area spectrum measurements. In this paper, we investigate an energy detection (ED)-based spectrum measurements, in which the noise floor (NF) estimation is a key functionality for the appropriate ED threshold setting. Typically, the NF has the slowly time- varying property and frequency-dependency, and several NF estimation algorithms, including forward consecutive mean excision (FCME) algorithm-based method, have been proposed. However, these methods did not deeply consider the slowly time varying property of the NF and is computationally inefficient. Accordingly, we propose a computational complexity reduction algorithm based on NF level change detection. This algorithm is computationally efficient, since it skips the NF estimation process when the NF does not change. In numerical evaluations, we show the efficiency and the validity of the proposed algorithm.
Iwata Hiroki, Umebayashi Kenta, Al-Tahmeesschi Ahmed, Joshi Satya, López-Benítez Miguel, Lehtomäki Janne J.
A4 Article in conference proceedings
Place of publication:
2020 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2020
H. Iwata, K. Umebayashi, A. Al-Tahmeesschi, S. Joshi, M. Lopez-Benitez and J. J. Lehtomaki, “A Study on High-Efficiency Energy Detection-Based Spectrum Measurements,” 2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Seoul, Korea (South), 2020, pp. 1-6, doi: 10.1109/WCNCW48565.2020.9124906
Read the publication here: