TY - JOUR
T1 - Wideband spectrum sensing for cognitive radio networks
T2 - a survey
AU - Sun, Hongjian
AU - Nallanathan, Arumugam
AU - Wang, Cheng-Xiang
AU - Chen, Yunfei
N1 - INSPEC Accession Number: 13474041
PY - 2013/4
Y1 - 2013/4
N2 - Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented, together with a discussion of the pros and cons of each algorithm and the challenging issues. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing and multichannel sub-Nyquist sampling techniques.
AB - Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented, together with a discussion of the pros and cons of each algorithm and the challenging issues. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing and multichannel sub-Nyquist sampling techniques.
KW - SIGNALS
U2 - 10.1109/MWC.2013.6507397
DO - 10.1109/MWC.2013.6507397
M3 - Article
SN - 1536-1284
VL - 20
SP - 74
EP - 81
JO - IEEE Wireless Communications
JF - IEEE Wireless Communications
IS - 2
ER -