Opportunity Detection for OFDMA-Based Cognitive Radio Systems with Timing Misalignment

Abstract-Accurate detection of spectrum opportunities within the frequency band of an orthogonal frequency division multiple access (OFDMA) system carries critical importance for OFDMAbased cognitive radios. In this paper, we analyze the opportunity detection performances of energy detection and ESPRIT (estimation of signal parameters by rotational invariance techniques) algorithms in the presence of timing misalignments in uplink (UL) OFDMA. For the energy detector, the statistics of subcarrier power are derived considering timing misalignments, and they are verified through computer simulations. Using these statistics, which take inter-carrier-interference (ICI) effects into account, receiver operating characteristics (ROCs) of the energy detector receiver are obtained. It is shown that energy detection has a considerably better performance than ESPRIT, especially when the subcarrier assignment changes frequently. Moreover, a closed form expression is derived for the UL-OFDMA synchronization point that minimizes the ICI. Finally, it is shown that employing resource allocation blocks with larger sizes in the primary network yields better opportunities for the cognitive radio