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This paper considers wide-band spectrum sensing and optimization forcognitive radio (CR) networks with noise variance uncertainty. It is assumedthat the considered wide-band contains one or more white sub-bands. Under thisassumption, we consider throughput maximization of the CR network whileappropriately protecting the primary network. We address this problem asfollows. First, we propose novel ratio based test statistics for detecting theedges of each sub-band. Second, we employ simple energy comparison approach tochoose one reference white sub-band. Third, we propose novel generalized energydetector (GED) for examining each of the remaining sub-bands by exploiting thenoise information of the reference white sub-band. Finally, we optimize thesensing time ($T_o$) to maximize the CR network throughput using the detectionand false alarm probabilities of the GED. The proposed GED does not suffer fromsignal to noise ratio (SNR) wall and outperforms the existing signal detectors.Moreover, the relationship between the proposed GED and conventional energydetector (CED) is quantified analytically. We show that the optimal $T_o$depends on the noise variance information. In particular, with $10$TV bands,SNR=$-20$dB and $2$s frame duration, we found that the optimal $T_o$ is$28.5$ms ($50.6$ms) with perfect (imperfect) noise variance scenario.

Wideband Sensing and Optimization for Cognitive Radio Networks with Noise Variance Uncertainty