Comprehensive performance analysis of data-fusion aided cooperative cognitive radio network over η − μ fading channel

摘要

In this paper, analytical performance of efficient soft-data combining schemes (SDCSs) for cognitive radio network (CRN) is investigated. The performance is investigated in the presence of noise and generalized eta-mu fading. In more detail, each CRU senses the PU and reports its sensing information to the fusion center (FC). At FC, different SDCSs, which differ in process of fusing the sensing data, are implemented to make the global decision on the status of a PU. In the present work, first the novel mathematical expressions, subject to SDCS and eta-mu fading are derived. Next, the performance is evaluated through receiver operating characteristics (ROC) and average error rate (AER), considering the significant impact of network and channel parameters. The performance of hard-decision combining schemes (HDCSs) is also studied for comparison purpose. The analysis presented in this paper eliminates the need of analysis of SDCSs over individual fading channels. An optimal sensing threshold and an optimal number of CRUs where AER attains its minimum value are also determined for all HDCSs and SDCSs. Finally, the derived expressions are validated by computer based simulations for several parameter values of the network.