Spectrum characterization for opportunistic cognitive radio systems
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
ML estimation of time and frequency offset in OFDM systems
IEEE Transactions on Signal Processing
On the extraction of the channel allocation information in spectrum pooling systems
IEEE Journal on Selected Areas in Communications
EURASIP Journal on Wireless Communications and Networking
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A cognitive radio system needs accurate knowledge of the radio spectrum it operates in. Blind modulation recognition techniques have been proposed to discriminate between single-carrier and multicarrier modulations and to estimate their parameters. Some powerful techniques use autocorrelation-and cyclic autocorrelation-based features of the transmitted signal applying to OFDM signals using a Cyclic Prefix time guard interval (CP-OFDM). In this paper, we propose a blind parameter estimation technique based on a power autocorrelation feature applying to OFDM signals using a Zero Padding time guard interval (ZP-OFDM) which in particular excludes the use of the autocorrelation-and cyclic autocorrelation-based techniques. The proposed technique leads to an efficient estimation of the symbol duration and zero padding duration in frequency selective channels, and is insensitive to receiver phase and frequency offsets. Simulation results are given for WiMAX and WiMedia signals using realistic Stanford University Interim (SUI) and Ultra-Wideband (UWB) IEEE 802.15.4a channel models, respectively.