Performance Of Quickest Spectrum Sensing For Evm-Based Change Detection

In cognitive radio (CR) systems, secondary users (SUs) equipped with a single transceiver are unable to sense and transmit simultaneously. Due to this limitation, most of the models intended to describe spectrum sensing focus on pre-transmission sensing and consider that primary users (PUs) only change their activity state in the beginning of each SU's operation cycle. This study characterises the more practical scenario which considers the reappearing PU during ongoing SU communication. The authors study a quickest detection scheme that uses an error vector magnitude (EVM) of the received signal. They consider two models of PUs namely an unknown deterministic signal and a Gaussian random signal with additive white Gaussian noise. The probability density function of the EVM test statistic is derived for both cases. The authors develop an exact quickest detection scheme by using a traditional cumulative sum (CUSUM) test. They show that CUSUM EVM outperforms CUSUM ED using theoretical analysis and numerical simulations.