OFDM Blind Parameter Identification in Cognitive Radios

In this paper we introduce a blind parameter identification algorithm for orthogonal frequency division multiplexing (OFDM) signals. The algorithm correlation-based processes automatically estimate all parameters of OFDM signals with a blind process that works from a limited amount of data without any prior information. We also derive novel identification performances of algorithms under various conditions, assuming actual conditions in feasible systems: data offset, AWGN, frequency offset, and fading channels. The algorithm is essential for two systems: first, cognitive radios, one of the most exciting being radios that change fundamental parameters frequently to provide high throughput and high quality of services; and, second, radio monitoring systems that detect illegal signals transmitted by unlicensed devices