Approximating the standard condition number for cognitive radio spectrum sensing with finite number of sensors
| dc.contributor.author | Kobeissi, Hussein | |
| dc.contributor.author | Nafkha, Amor | |
| dc.contributor.author | Nasser, Youssef | |
| dc.contributor.author | Louët, Yvës | |
| dc.contributor.author | Bazzi, Oussama | |
| dc.contributor.department | Department of Electrical and Computer Engineering | |
| dc.contributor.faculty | Maroun Semaan Faculty of Engineering and Architecture (MSFEA) | |
| dc.contributor.institution | American University of Beirut | |
| dc.date.accessioned | 2025-01-24T11:29:25Z | |
| dc.date.available | 2025-01-24T11:29:25Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | In this study, the authors consider the standard condition number (SCN) detector for a cognitive radio with finite number of cooperative sensors. They derive an exact nested form of the distribution of the SCN for the central uncorrelated, non-central uncorrelated and central semi-correlated Wishart matrices under ℋ0 and ℋ1 hypotheses. Due to the complexity of these expressions, the authors approximate the distribution of the SCN by the generalised extreme value distribution using moment matching. They derive the exact form of the pth moment of the SCN for these cases. Consequently, the performance probabilities are approximated and a simple decision threshold formula is provided. In addition, a similar approximation for the detection probability is provided using non-central/central approximation. They show that the proposed analytical approximations provide high accuracy using Monte-Carlo simulations. © The Institution of Engineering and Technology. | |
| dc.identifier.doi | https://doi.org/10.1049/iet-spr.2016.0146 | |
| dc.identifier.eid | 2-s2.0-85016470593 | |
| dc.identifier.uri | http://hdl.handle.net/10938/27214 | |
| dc.language.iso | en | |
| dc.publisher | Institution of Engineering and Technology | |
| dc.relation.ispartof | IET Signal Processing | |
| dc.source | Scopus | |
| dc.subject | Intelligent systems | |
| dc.subject | Monte carlo methods | |
| dc.subject | Number theory | |
| dc.subject | Radio systems | |
| dc.subject | Analytical approximation | |
| dc.subject | Decision threshold | |
| dc.subject | Detection probabilities | |
| dc.subject | Generalised extreme value distributions | |
| dc.subject | Moment-matching | |
| dc.subject | Semi-correlated | |
| dc.subject | Standard condition numbers | |
| dc.subject | Wishart matrices | |
| dc.subject | Cognitive radio | |
| dc.title | Approximating the standard condition number for cognitive radio spectrum sensing with finite number of sensors | |
| dc.type | Article |
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