Abstract / Description of output
In this paper, we study the tradeoff between sensing time and achievable throughput of the secondary user that employs robust eigenvalue-based spectrum sensing techniques in the presence of noise uncertainty. First, we study exact distributions of the test statistics for two types of robust eigenvalue-based sensing techniques, namely, the blind generalized likelihood ratio test (B-GLRT) detection and energy with minimum eigenvalue (EME) detection. The developed threshold setting is more accurate than benchmark methods in achieving a target constant false alarm rate (CFAR). Second, prior to the throughput analysis, the necessary asymptotic detection and false alarm probabilities under noise uncertainty are formulated for eigenvalue-based detectors such as maximum eigenvalue detection (MED) and maximum-minimum eigenvalue (MME) detection. Finally, the throughput is maximized using eigenvalue-based spectrum sensing techniques which are B-GLRT, EME, MME, and MED detectors. The results are compared with the commonly used energy detector (ED). An improved achievable throughput is obtained under low-signal-to-noise-ratio (SNR) regime by incorporating the robust eigenvalue-based techniques, which are insusceptible to noise uncertainty.
Original language | English |
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Article number | 6601644 |
Pages (from-to) | 1480-1486 |
Number of pages | 7 |
Journal | IEEE Transactions on Vehicular Technology |
Volume | 63 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jan 2014 |
Keywords / Materials (for Non-textual outputs)
- Cognitive radio (CR)
- eigenvalue-based detection
- sensing-throughput tradeoff
- spectrum sensing