Blind detection and estimation of OFDM signals in cognitive radio contexts

Cognitive radio has been seen as a promising technique to address the frequency resource scarcity problem. It is a key issue to reliably detect the activity of primary users' (PUs) for cognitive radio users. As orthogonal frequency division multiplexing (OFDM) has becoming a popular technique for modern wireless communications systems. It is necessary to identify the existence and estimate the key parameters OFDM systems in cognitive radio contexts. In this paper, we propose a scheme to identify the Pus signals with OFDM. This scheme involves three steps. Firstly, we propose a method to identify the activity of signals through spectrum sensing. Then, we provide a scheme to distinguish whether an active signal is OFDM signal or single-carrier signal. At last, the key parameters of OFDM such as the number of subcarriers and the cyclic prefix length are estimated blindly. Simulation results validate the proposed method.

[1]  Hüseyin Arslan,et al.  OFDM Signal Identification and Transmission Parameter Estimation for Cognitive Radio Applications , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[2]  Danijela Cabric,et al.  Physical layer design issues unique to cognitive radio systems , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Philippe Loubaton,et al.  Asymptotic analysis of blind cyclic correlation based symbol rate estimation , 2000, 2000 10th European Signal Processing Conference.

[4]  J. I. Mararm,et al.  Energy Detection of Unknown Deterministic Signals , 2022 .

[5]  W. Akmouche,et al.  Detection of multicarrier modulations using 4th-order cumulants , 1999, MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341).

[6]  Brian M. Sadler,et al.  Hierarchical digital modulation classification using cumulants , 2000, IEEE Trans. Commun..

[7]  P. Loubaton,et al.  Cyclic correlation based symbol rate estimation , 1999, Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020).

[8]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[9]  Georgios B. Giannakis,et al.  Time-domain tests for Gaussianity and time-reversibility , 1994, IEEE Trans. Signal Process..

[10]  Hiroyuki Ishii,et al.  OFDM Blind Parameter Identification in Cognitive Radios , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.

[11]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[12]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[13]  U. Reimers,et al.  Digital video broadcasting , 1998, IEEE Commun. Mag..