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- Title
Spectrum Sensing Algorithm to Detect Small-Scale Primary Users Based on Maximum-Minimum Eigenvalue.
- Authors
Weichao ZHONG; Pin WAN; Yonghua WANG; Ting LIANG; Yiquan ZHENG
- Abstract
In cognitive radio networks (CRNs), primary users can be divided into large-scale primary users and small-scale mobile primary users (SSPU), such as wireless microphones. SSPU's transmission power is weak, its signal is easily influenced by external factors in the process of detection. The Maximum-Minimum Eigenvalue based algorithm (MME) with no prior knowledge about the PU signal can still be effective under low SNR. So the MME is used to detect the SSPU signal in this paper, and its performances are compared with the energy detection (ED). The detection performance of the traditional MME algorithm can still be improved. Then the algorithm is improved by adding the weight coefficient, and we propose a new MME algorithm for SSPU detection. This paper discusses the impact on detection performance of the number of SUs and the number of samples. The simulation results show that the improved MME algorithm can effectively sense SSPU signal in low SNR environment, and achieve the purpose of improving the detection probability.
- Subjects
RADIO networks; RADIO transmitters &; transmission; TELEVISION networks
- Publication
International Journal of Simulation: Systems, Science & Technology, 2016, Vol 17, Issue 44, p39.1
- ISSN
1473-8031
- Publication type
Article
- DOI
10.5013/IJSSST.a.17.44.39