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Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels

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Standard

Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels. / Al Hammadi, Ahmed; Al Hussein, Omar; Sofotasios, Paschalis; Muhaidat, Sami; Al Qutayri, Mahmoud ; Al Araji, Saleh; Karagiannidis, George; Liang, Jie.

julkaisussa: IEEE Transactions on Vehicular Technology, Vuosikerta 65, Nro 9, 2016, s. 6949-6961.

Tutkimustuotosvertaisarvioitu

Harvard

Al Hammadi, A, Al Hussein, O, Sofotasios, P, Muhaidat, S, Al Qutayri, M, Al Araji, S, Karagiannidis, G & Liang, J 2016, 'Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels', IEEE Transactions on Vehicular Technology, Vuosikerta. 65, Nro 9, Sivut 6949-6961. https://doi.org/10.1109/TVT.2015.2487320

APA

Al Hammadi, A., Al Hussein, O., Sofotasios, P., Muhaidat, S., Al Qutayri, M., Al Araji, S., ... Liang, J. (2016). Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels. IEEE Transactions on Vehicular Technology, 65(9), 6949-6961. https://doi.org/10.1109/TVT.2015.2487320

Vancouver

Al Hammadi A, Al Hussein O, Sofotasios P, Muhaidat S, Al Qutayri M, Al Araji S et al. Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels. IEEE Transactions on Vehicular Technology. 2016;65(9):6949-6961. https://doi.org/10.1109/TVT.2015.2487320

Author

Al Hammadi, Ahmed ; Al Hussein, Omar ; Sofotasios, Paschalis ; Muhaidat, Sami ; Al Qutayri, Mahmoud ; Al Araji, Saleh ; Karagiannidis, George ; Liang, Jie. / Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels. Julkaisussa: IEEE Transactions on Vehicular Technology. 2016 ; Vuosikerta 65, Nro 9. Sivut 6949-6961.

Bibtex - Lataa

@article{c56a32aa92024aa2b37d6ff17e05c203,
title = "Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels",
abstract = "In this paper, we investigate the performance of cooperative spectrum sensing (CSS) with multiple-antenna nodes over generalized and composite fading channels. To this end, we approximate the probability density function (pdf) of the signalto- noise ratio (SNR) of various fading channels using the mixture Gamma (MG) distribution. Based on this, we derive an exact closed-form expression and a generic infinite series representation for the corresponding probability of energy detection, along with a finite upper bound for the involved truncation error. Both expressions have a relatively simple algebraic form that gives them convenience in handling both analytically and numerically. Furthermore, the composite effect of multipath fading and shadowing scenarios in CSS is mitigated by applying an optimal fusion rule that minimizes the total error rate (TER), where the optimal number of nodes is derived under the Bayesian criterion, assuming erroneous feedback channels. We also extend the derived average detection probability to include diversity reception techniques, namely, maximal-ratio combining, square-law combining, and square-law selection (SLS). For the SLS, we demonstrate the existence of an error rate floor as the number of antennas of the cognitive radio nodes increases in erroneous decision feedback channels. Accordingly, we derive the optimal rule for the number of antennas that minimizes the TER in the SLS framework. Monte Carlo simulations are presented to corroborate the analytical results and to provide illustrative performance comparisons and insights between different composite fading channels.",
author = "{Al Hammadi}, Ahmed and {Al Hussein}, Omar and Paschalis Sofotasios and Sami Muhaidat and {Al Qutayri}, Mahmoud and {Al Araji}, Saleh and George Karagiannidis and Jie Liang",
year = "2016",
doi = "10.1109/TVT.2015.2487320",
language = "English",
volume = "65",
pages = "6949--6961",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
publisher = "Institute of Electrical and Electronics Engineers",
number = "9",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels

AU - Al Hammadi, Ahmed

AU - Al Hussein, Omar

AU - Sofotasios, Paschalis

AU - Muhaidat, Sami

AU - Al Qutayri, Mahmoud

AU - Al Araji, Saleh

AU - Karagiannidis, George

AU - Liang, Jie

PY - 2016

Y1 - 2016

N2 - In this paper, we investigate the performance of cooperative spectrum sensing (CSS) with multiple-antenna nodes over generalized and composite fading channels. To this end, we approximate the probability density function (pdf) of the signalto- noise ratio (SNR) of various fading channels using the mixture Gamma (MG) distribution. Based on this, we derive an exact closed-form expression and a generic infinite series representation for the corresponding probability of energy detection, along with a finite upper bound for the involved truncation error. Both expressions have a relatively simple algebraic form that gives them convenience in handling both analytically and numerically. Furthermore, the composite effect of multipath fading and shadowing scenarios in CSS is mitigated by applying an optimal fusion rule that minimizes the total error rate (TER), where the optimal number of nodes is derived under the Bayesian criterion, assuming erroneous feedback channels. We also extend the derived average detection probability to include diversity reception techniques, namely, maximal-ratio combining, square-law combining, and square-law selection (SLS). For the SLS, we demonstrate the existence of an error rate floor as the number of antennas of the cognitive radio nodes increases in erroneous decision feedback channels. Accordingly, we derive the optimal rule for the number of antennas that minimizes the TER in the SLS framework. Monte Carlo simulations are presented to corroborate the analytical results and to provide illustrative performance comparisons and insights between different composite fading channels.

AB - In this paper, we investigate the performance of cooperative spectrum sensing (CSS) with multiple-antenna nodes over generalized and composite fading channels. To this end, we approximate the probability density function (pdf) of the signalto- noise ratio (SNR) of various fading channels using the mixture Gamma (MG) distribution. Based on this, we derive an exact closed-form expression and a generic infinite series representation for the corresponding probability of energy detection, along with a finite upper bound for the involved truncation error. Both expressions have a relatively simple algebraic form that gives them convenience in handling both analytically and numerically. Furthermore, the composite effect of multipath fading and shadowing scenarios in CSS is mitigated by applying an optimal fusion rule that minimizes the total error rate (TER), where the optimal number of nodes is derived under the Bayesian criterion, assuming erroneous feedback channels. We also extend the derived average detection probability to include diversity reception techniques, namely, maximal-ratio combining, square-law combining, and square-law selection (SLS). For the SLS, we demonstrate the existence of an error rate floor as the number of antennas of the cognitive radio nodes increases in erroneous decision feedback channels. Accordingly, we derive the optimal rule for the number of antennas that minimizes the TER in the SLS framework. Monte Carlo simulations are presented to corroborate the analytical results and to provide illustrative performance comparisons and insights between different composite fading channels.

U2 - 10.1109/TVT.2015.2487320

DO - 10.1109/TVT.2015.2487320

M3 - Article

VL - 65

SP - 6949

EP - 6961

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 9

ER -