Traditional spectrum allocation policies are facing scarce radio frequency (RF) resources due to the proliferation of wireless services. To improve spectral utilization, the Federal Communications Commission (FCC) has recently allowed unlicensed wireless devices to opportunistically use vacant frequency bands, especially vacant TV broadcast bands, provided that they do not cause harmful interference. To this end, cognitive radio has emerged as an intelligent wireless communication technology to revolutionize spectral utilization. A fundamental problem arising in cognitive ratio implementations is spectrum sensing; the term refers to the need to reliably detect weak primary signals over a wide frequency band in order to identify spectral holes for opportunistic communications. However, it is generally difficult for cognitive radios to reliably detect weak primary signals due to the absence of cooperation between the primary and secondary users. This dissertation addresses three important design challenges for spectrum sensing in cognitive radio networks: spectrum sensing at very low SNR, cooperative spectrum sensing, and wideband spectrum sensing. We propose and develop advanced signal processing techniques to optimize spectrum sensing performance for cognitive radio systems.
Acknowledgment This work was supported in part by the National Science Foundation under grants ECS-0601266 and ECS-0725441. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.