Opportunistic Spectrum Access in OFDMA Systems

This paper presents the novel idea for opportunity detection (detecting unoccupied sub-carriers/sub-channels) in downlink (DL) orthogonal frequency division multiple access (OFDMA) systems using cognitive radio (CR) sensing techniques and sub-channel utilization history information. Assuming availability of information about the basic parameters of the primary system as well as time and frequency synchronization of CR user with primary system, three techniques have been proposed for detection of unoccupied sub-channels in DL OFDMA systems: 1) Detection Method- it identifies unoccupied sub-carriers/sub-channel in DL OFDMA systems by exploiting the CR sensing techniques (i.e. matched filter and energy detection). 2) Prediction Method- it forecasts the future sub-channel state (empty or occupied) by classifying sub-channel history into different traffic patterns using `Traffic Classification Algorithm´. 3) Hybrid of Detection and Prediction Method- it also utilizes `Traffic Classification Algorithm´ to decide when to use detection and prediction methods in order to determine either sub-channel will remain empty or occupied in next time slot.