Abstract
The present contribution proposes a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach in a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. In this context, exact analytic expressions are first derived for the corresponding probability of detection, probability of false alarm, and secondary throughput, assuming that each secondary user (SU) sends its detection outcome to a fusion center only when it has detected a primary signal. Capitalizing on the findings of the analysis, the effects of critical measures, such as the detection threshold, the number of SUs, and the number of employed antennas, on the overall system performance are also quantified. In addition, the optimal detection threshold for each antenna based on the Neyman-Pearson criterion is derived and useful insights are developed on how to maximize the system throughput with a reduced number of SUs. It is shown that the C-CSS approach provides two distinct benefits compared with the conventional sensing approach, i.e., without censoring: i) the sensing tail problem, which exists in imperfect sensing environments, can be mitigated; and ii) less SUs are ultimately required to obtain higher secondary throughput, rendering the system more sustainable.
Original language | English |
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Pages (from-to) | 48-60 |
Number of pages | 13 |
Journal | IEEE Transactions on Sustainable Computing |
Volume | 5 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2020 |
Publication type | A1 Journal article-refereed |
Keywords
- censoring
- cooperative spectrum sensing
- energy detection
- energy efficiency
- imperfect reporting channels
- multi-antenna systems
- Sustainble computing
Publication forum classification
- Publication forum level 1
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Hardware and Architecture
- Software
- Renewable Energy, Sustainability and the Environment
- Control and Optimization