Performance Evaluation of EVM based Primary User Monitoring in Cognitive Radio Systems

Continuous sensing and transmission by secondary users (SUs) in cognitive radio (CR) allows efficient use of available spectrum. In this approach, the SU receiver continuously senses the spectrum while it transmits in the same frequency band. Leveraging this advantage, we study the performance of error vector magnitude (EVM) based detection to detect the reappearance of the primary user (PU) signal during ongoing SU data transmission. We exploit the pilot tones that are inherent to many OFDM based standards to measure the EVM. We consider two models of PU namely an unknown deterministic signal and a Gaussian random signal with additive white Gaussian noise (AWGN). We derive an analytical form of the probability density function (PDF) of the EVM based detector based on the exact representation of Chi-square distributions. We analyze the performance of our detector by deriving the type I (false positive) and type II (false negative) error probabilities. Simulation results show that the EVM based approach achieves better performance than energy detection.