Abstract
The core component of a cognitive radio is its detector. When a device is equipped with multiple antennas, the detection method is usually based on an eigenvalue analysis. This paper explores the performance of the most common largest eigenvalue detector, for the case of a narrowband temporally white signal and calibrated receiver noise. In contrast to popular Gaussian assumption, our performance bounds are valid for any signal and noise that belong to the wide class of sub-Gaussian random processes. Moreover, the results are given in closed-form for any finite number of observations and antennas, in contrary to the widespread asymptotic analysis approach.
Original language | English |
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Title of host publication | 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2936-2940 |
Number of pages | 5 |
ISBN (Electronic) | 9781479999880 |
DOIs | |
State | Published - 18 May 2016 |
Externally published | Yes |
Event | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: 20 Mar 2016 → 25 Mar 2016 |
Publication series
Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
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Volume | 2016-May |
ISSN (Print) | 1520-6149 |
Conference
Conference | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 |
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Country/Territory | China |
City | Shanghai |
Period | 20/03/16 → 25/03/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Keywords
- Chernoff bound
- Sensor array
- cognitive radio
- random matrix
- sub-Gaussian random variables