Abstract
In this paper we propose a soft-hard combination scheme, called SHC scheme, for cooperative spectrum sensing in cognitive radio networks. The SHC scheme deploys a cluster based network in which Likelihood Ratio Test (LRT)-based soft combination is applied at each cluster, and weighted decision fusion rule-based hard combination is utilized at the fusion center. The novelties of the SHC scheme are as follows: the structure of the SHC scheme reduces the complexity of cooperative detection which is an inherent limitation of soft combination schemes. By using the LRT, we can detect primary signals in a low signal-to-noise ratio regime (around an average of −15 dB). In addition, the computational complexity of the LRT is reduced since we derive the closed-form expression of the probability density function of LRT value. The SHC scheme also takes into account the different effects of large scale fading on different users in the wide area network. The simulation results show that the SHC scheme not only provides the better sensing performance compared to the conventional hard combination schemes, but also reduces sensing overhead in terms of reporting time compared to the conventional soft combination scheme using the LRT.
Highlights
According to IEEE 802.22 standard, customer premise equipment (CPE) Wireless Regional Area Network (WRAN) devices which are considered as the secondary users, will use the vacant channels in the VHF and UHF bands that are allocated to the Television Broadcasting Service in the frequency range between 54 MHz and 862 MHz while avoiding interference to the broadcast incumbents, which are considered as primary users, in these bands
We propose a Soft-Hard Combination (SHC) scheme that combines soft combination and hard combination into one spectrum sensing scheme
Cluster heads combine the test statistics of other secondary users (SUs) and conduct the Likelihood Ratio Test (LRT) with the optimal cluster threshold which is determined by the minimum error probability criterion
Summary
SUs first turn the local decisions into one-bit decision, i.e., 0 or 1 implies that a primary user is absent or present, respectively, based on their observations of the primary signal They send these one-bit decisions to the fusion center. SUs directly send their local observations which are energy values of the received signals from the primary user to the fusion center. Location information has been applied in hard combination scheme for cooperative detection [13] or in concurrence transmission in cognitive radio networks [18].Since we consider the large network where each cluster experiments a different primary signal SNR, the weighted decision fusion rule is used at the fusion center for distinguishing the different contribution of each cluster to the global decision at the fusion center
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