Collaborative spectrum sensing for opportunistic access in fading environments

Traditionally, frequency spectrum is licensed to users by government agencies in a fixed manner where licensee has exclusive right to access the allocated band. This policy has been de jure practice to protect systems from mutual interference for many years. However, with increasing demand for the spectrum and scarcity of vacant bands, a spectrum policy reform seems inevitable. Meanwhile, recent measurements suggest the possibility of sharing spectrum among different parties subject to interference-protection constraints. In this paper we study spectrum-sharing between a primary licensee and a group of secondary users. In order to enable access to unused licensed spectrum, a secondary user has to monitor licensed bands and opportunistically transmit whenever no primary signal is detected. However, detection is compromised when a user experiences shadowing or fading effects. In such cases, user cannot distinguish between an unused band and a deep fade. Collaborative spectrum sensing is proposed and studied in this paper as a means to combat such effects. Our analysis and simulation results suggest that collaboration may improve sensing performance significantly

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

[2]  Larry J. Greenstein,et al.  An empirically based path loss model for wireless channels in suburban environments , 1999, IEEE J. Sel. Areas Commun..

[3]  Pramod K. Varshney,et al.  Distributed Detection and Data Fusion , 1996 .

[4]  Jon M. Peha,et al.  Approaches to spectrum sharing , 2005, IEEE Communications Magazine.

[5]  William D. Horne,et al.  Adaptive Spectrum Access: Using the Full Spectrum Space , 2003 .

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

[7]  M. Gudmundson Correlation Model for Shadow Fading in Mobile Radio Systems , 1991 .

[8]  A. Sonnenschein,et al.  Radiometric detection of spreadspectrum signals in noise of uncertain power , 1992 .

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

[10]  P. Lawson,et al.  Federal Communications Commission , 2004, Bell Labs Technical Journal.

[11]  Friedrich Jondral,et al.  Calculation of detection and false alarm probabilities in spectrum pooling systems , 2005, IEEE Communications Letters.

[12]  Albert H. Nuttall,et al.  Some integrals involving the QM function (Corresp.) , 1975, IEEE Trans. Inf. Theory.

[13]  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..

[14]  Mohamed-Slim Alouini,et al.  On the Energy Detection of Unknown Signals Over Fading Channels , 2007, IEEE Transactions on Communications.