TY - GEN
T1 - Censor-Based Multi-Antenna Cooperative Spectrum Sensing over Erroneous Feedback Channels
AU - Li, Meiling
AU - Alhussein, Omar
AU - Sofotasios, Paschalis C.
AU - Muhaidat, Sami
AU - Yoo, Paul D.
AU - Liang, Jie
AU - Wang, Anhong
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China (Grant No. 61672373), the Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi(Grant No. 201802090), the Program of One hundred Talented People of Shanxi Province, the Scientific and Technology Innovation Program of Shanxi Province (Grant No. 201705D131025), The Key Innovation Team of the 1331 Project of Shanxi Province, and by Khalifa University under Grant No. KU/RC1-C2PS-T2/8474000137 and Grant No. KU/FSU-8474000122.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - We propose a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach for a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. First, analytic expressions are derived for the corresponding probabilities of detection and false alarm, assuming that each secondary user sends its detection outcome to a fusion center only when it believes to have detected a primary user's signal. Second, we derive lower bounds for the probability of false alarm, where we show that a sensing tail problem, which exist in the conventional (non-censor-based) scheme, can be effectively mitigated with the aid of the proposed C-CSS scheme. Simulation results are presented to corroborate the derived analytic results, and to provide theoretical and technical insights that are useful for the design of cognitive radio networks.
AB - We propose a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach for a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. First, analytic expressions are derived for the corresponding probabilities of detection and false alarm, assuming that each secondary user sends its detection outcome to a fusion center only when it believes to have detected a primary user's signal. Second, we derive lower bounds for the probability of false alarm, where we show that a sensing tail problem, which exist in the conventional (non-censor-based) scheme, can be effectively mitigated with the aid of the proposed C-CSS scheme. Simulation results are presented to corroborate the derived analytic results, and to provide theoretical and technical insights that are useful for the design of cognitive radio networks.
UR - http://www.scopus.com/inward/record.url?scp=85074785435&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2019.8885833
DO - 10.1109/WCNC.2019.8885833
M3 - Conference contribution
AN - SCOPUS:85074785435
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Y2 - 15 April 2019 through 19 April 2019
ER -