TY - GEN
T1 - Rapid spectrum sensing with multiple antennas for cognitive radio
AU - Wang, Pu
AU - Fang, Jun
AU - Han, Ning
AU - Li, Hongbin
PY - 2011
Y1 - 2011
N2 - We consider the problem of detecting a primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios typically transit regions with differing densities of primary users. Therefore, speed of detection is key, so detection based on a small number of samples is particularly advantageous for vehicular applications. Without assuming any prior knowledge of the primary user's signaling scheme, the channels between the primary user and the cognitive user, and the variance of the noise seen at the cognitive user, a generalized likelihood ratio test (GLRT) is developed to detect the presence/absence of the primary user. Asymptotic performance analysis for the proposed GLRT is also presented. Performance comparison between the proposed GLRT and other existing methods such as the energy detector and several eigenvalue-based methods under the condition of unknown or inaccurately known noise variance is provided. Our results show that the proposed GLRT exhibits better performance than other existing techniques, especially when the number of samples is small, which is particularly critical in vehicular applications.
AB - We consider the problem of detecting a primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios typically transit regions with differing densities of primary users. Therefore, speed of detection is key, so detection based on a small number of samples is particularly advantageous for vehicular applications. Without assuming any prior knowledge of the primary user's signaling scheme, the channels between the primary user and the cognitive user, and the variance of the noise seen at the cognitive user, a generalized likelihood ratio test (GLRT) is developed to detect the presence/absence of the primary user. Asymptotic performance analysis for the proposed GLRT is also presented. Performance comparison between the proposed GLRT and other existing methods such as the energy detector and several eigenvalue-based methods under the condition of unknown or inaccurately known noise variance is provided. Our results show that the proposed GLRT exhibits better performance than other existing techniques, especially when the number of samples is small, which is particularly critical in vehicular applications.
KW - Cognitive radio
KW - generalized likelihood ratio test
KW - spectrum sensing
UR - http://www.scopus.com/inward/record.url?scp=82955237707&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=82955237707&partnerID=8YFLogxK
U2 - 10.1109/AFRCON.2011.6072049
DO - 10.1109/AFRCON.2011.6072049
M3 - Conference contribution
AN - SCOPUS:82955237707
SN - 9781612849928
T3 - IEEE AFRICON Conference
BT - IEEE Africon'11
T2 - IEEE Africon'11
Y2 - 13 September 2011 through 15 September 2011
ER -