Spectrum sensing performance of wireless cognitive radio sensor network with hard‐decision fusion over generalizedα−μfading channels

Abstract

Summary The analysis of spectrum sensing performance of energy detection (ED)‐based wireless cognitive radio sensor network (ED‐WCRSN) with hard‐decision combining (HDC) is presented in this paper. Particularly, several network parameters are derived to estimate the performance of ED‐WCRSN, considering channel errors, noise, and generalized α−μ fading. In the considered network, first, cognitive radio sensor (CRS) senses a primary user (PU), gets sensing data, and then uses an ED to make a local binary decisions about PU's active or inactive status. In both sensing and reporting channels, the channel error probability is also taken into account. Next, HDC technique is used at control center (CC) to combine the locally obtained decisions, and a final decision about the status of the PU is made. To do so, first, the expression for the novel and analytical, which incorporates noise and α−μ fading, detection probability in a CRS is derived and validated using Monte Carlo simulations in MATLAB and using an experimental setup. Then, utilizing derived mathematical expressions, closed‐form expressions of an average error rate (AER), optimal numbers of CRSs, and detection thresholds under noisy and α−μ fading conditions are developed. The substantial influence of channel and network factors is assessed using receiver operating characteristics (ROC), complementary ROC, and AER. Finally, the impacts of channel and network parameters on ED‐WCRSN performance are explored. For numerous parameters of the considered network, the optimal values detection threshold and number of CRSs are also found.