Cooperative Spectrum Sensing in Log-normal Shadowing Environment with Erroneous Sensing and Reporting Channels

In the present work, we study the performance of a cooperative spectrum sensing network (CSSN) based on energy detection technique in presence of noise and Log-normal shadowing (LNS). All the cognitive radio (CR) nodes use identical energy detectors (EDs), sense a primary user (PU), and report the sensed data in the form of binary-decision to the fusion center (FC). The wireless links between CR nodes and PU are considered as erroneous sensing (S) channels whereas links connecting from CR nodes to the FC are erroneous reporting (R) channels. Various hard-decision fusion rules are performed at FC to make a final decision on the status of the PU (either active or inactive). The analytical frameworks subject to noise and LNS fading, for evaluating missed detection and total error rate (TER) performances, for all the system and channel conditions are developed. Through computer simulations, developed analytical frameworks are validated. Further, the CSSN performance for different network parameters such as channel error probability, LNS parameter, number of samples, average S-channel signal-to-noise ratio (SNR), number of CR nodes, under various fusion rules is investigated. Finally, an optimal number of CR nodes for different fusion rules are also indicated.