Abstract
Resource Allocation in Spectrum Deployment for Cognitive Third-party Users
Highlights
The evolution of wireless communication has resulted in the interfacing of various advanced services on portable communication devices, with many new services being integrated at a rapid pace
In [5] for multipath and multi-channel conditions a window-based blind spectrum estimation is proposed. This approach improved the energy detection performance and the spectrum sensing in cognitive radio
The approach is a centralized monitoring scheme of spectrum sensing where the network is divided into two clusters and the spectrum sensing observations are monitored at the fusion center (FC) in deciding for spectrum sensing based on defined fusion rules
Summary
The evolution of wireless communication has resulted in the interfacing of various advanced services on portable communication devices, with many new services being integrated at a rapid pace. In [5] for multipath and multi-channel conditions a window-based blind spectrum estimation is proposed This approach improved the energy detection performance and the spectrum sensing in cognitive radio. The author in [12] proposed a multi-channel cooperative spectrum sensing (MCSS) method for optimizing spectrum sensing in a cognitive radio network This approach develops a novel game theory of node selection to extend energy savings in a cognitive device. In [16] a reinforcement learning (RL) method for cooperative spectrum seeing in CRN operation is presented This approach developed a channel scanning approach for spectrum sensing and requesting, where a confidence bound approach was proposed for secondary user (SU) spectrum sensing.
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