Cyclostationary Signatures in Practical Cognitive Radio Applications

We define a cyclostationary signature as a feature which may be intentionally embedded in a digital communications signal, detected through cyclostationary analysis and used as a unique identifier. The purpose of this paper is to demonstrate how cyclostationary signatures can be exploited to overcome a number of the challenges associated with network coordination in emerging cognitive radio applications and spectrum sharing regimes. In particular we show their uses for signal detection, network identification and rendezvous and discuss these in the context of dynamic spectrum access. We present a theoretical discussion followed by application-oriented examples of the cyclostationary signatures used in practical cognitive radio and dynamic spectrum usage scenarios. We focus on orthogonal frequency division multiplexing (OFDM) based systems and present an analysis of a transceiver implementation employing these techniques developed on a cognitive radio test platform.

[1]  William A. Gardner,et al.  Cyclostationarity in communications and signal processing , 1994 .

[2]  Linda Doyle,et al.  Fluid wireless -dynamic spectrum allocation and spectrum-monitoring application using reconfigurable radio and OFDM , 2005 .

[3]  Hao Nan,et al.  Distributed Coordinated Spectrum Sharing MAC Protocol for Cognitive Radio , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[4]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

[5]  D.N. Hatfield,et al.  Property rights in spectrum: taking the next step , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[6]  William A. Gardner,et al.  Measurement of spectral correlation , 1986, IEEE Trans. Acoust. Speech Signal Process..

[7]  Donald C. Cox,et al.  Robust frequency and timing synchronization for OFDM , 1997, IEEE Trans. Commun..

[8]  W. Lehr,et al.  Managing shared access to a spectrum commons , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[9]  A. De Vany.  Property Rights in the Electromagnetic Spectrum , 1996 .

[10]  Jeffrey H. Reed,et al.  A new approach to signal classification using spectral correlation and neural networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[11]  Helmut Bölcskei,et al.  Blind estimation of symbol timing and carrier frequency offset in wireless OFDM systems , 2001, IEEE Trans. Commun..

[12]  Milind M. Buddhikot,et al.  DIMSUMnet: new directions in wireless networking using coordinated dynamic spectrum , 2005, Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks.

[13]  L.E. Doyle,et al.  Cyclostationary Signatures for Rendezvous in OFDM-Based Dynamic Spectrum Access Networks , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[14]  Paul H. Moose,et al.  A technique for orthogonal frequency division multiplexing frequency offset correction , 1994, IEEE Trans. Commun..

[15]  Jun Zhao,et al.  Distributed coordination in dynamic spectrum allocation networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[16]  William A. Gardner,et al.  Signal interception: a unifying theoretical framework for feature detection , 1988, IEEE Trans. Commun..

[17]  Linda Doyle,et al.  Cyclostationary Signature Detection in Multipath Rayleigh Fading Environments , 2007, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[18]  Georgios B. Giannakis,et al.  Frequency offset and symbol timing recovery in flat-fading channels: a cyclostationary approach , 1998, IEEE Trans. Commun..

[19]  William A. Gardner,et al.  Signal interception: performance advantages of cyclic-feature detectors , 1992, IEEE Trans. Commun..

[20]  Philip Mackenzie.  Reconfigurable software radio systems , 2004 .

[21]  beotel. yu.  Spectral Correlation of OFDM Signals Related to Their PLC Applications , 2002 .

[22]  William Gardner,et al.  Spectral Correlation of Modulated Signals: Part I - Analog Modulation , 1987, IEEE Transactions on Communications.

[23]  P. Weiser,et al.  Policing the Spectrum Commons , 2005 .

[24]  Brian M. Sadler,et al.  Nonparametric Estimation of the Cyclic Cross Spectrum , 1998, IEEE Trans. Inf. Theory.

[25]  Oriol Sallent,et al.  A novel on-demand cognitive pilot channel enabling dynamic spectrum allocation , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[26]  Linda Doyle,et al.  A Reconfigurable Platform for Cognitive Networks , 2006, 2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[27]  W. Gardner.  Exploitation of spectral redundancy in cyclostationary signals , 1991, IEEE Signal Processing Magazine.

[28]  M Failli.  Cost 207: Digital Land Mobile Radio Communications , 1989 .

[29]  T. Ohya,et al.  Recognition Among OFDM-Based Systems Utilizing Cyclostationarity-Inducing Transmission , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[30]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[31]  William A. Gardner,et al.  Spectral Correlation of Modulated Signals: Part II - Digital Modulation , 1987, IEEE Transactions on Communications.

[32]  Robert W. Heath,et al.  Exploiting input cyclostationarity for blind channel identification in OFDM systems , 1999, IEEE Trans. Signal Process..

[33]  Tao Chen,et al.  CogMesh: A Cluster-Based Cognitive Radio Network , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.