Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
Lei WANG, Baoyu ZHENG, Qingmin MENG, Chao CHEN, "Cooperative Spectrum Sensing Using Free Probability Theory" in IEICE TRANSACTIONS on Communications,
vol. E93-B, no. 6, pp. 1547-1554, June 2010, doi: 10.1587/transcom.E93.B.1547.
Abstract: Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E93.B.1547/_p
Copy
@ARTICLE{e93-b_6_1547,
author={Lei WANG, Baoyu ZHENG, Qingmin MENG, Chao CHEN, },
journal={IEICE TRANSACTIONS on Communications},
title={Cooperative Spectrum Sensing Using Free Probability Theory},
year={2010},
volume={E93-B},
number={6},
pages={1547-1554},
abstract={Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.},
keywords={},
doi={10.1587/transcom.E93.B.1547},
ISSN={1745-1345},
month={June},}
Copy
TY - JOUR
TI - Cooperative Spectrum Sensing Using Free Probability Theory
T2 - IEICE TRANSACTIONS on Communications
SP - 1547
EP - 1554
AU - Lei WANG
AU - Baoyu ZHENG
AU - Qingmin MENG
AU - Chao CHEN
PY - 2010
DO - 10.1587/transcom.E93.B.1547
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E93-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2010
AB - Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.
ER -