Modeling and analysis of interference in Listen‐Before‐Talk spectrum access schemes

Spectrum measurement studies have shown that substantial portions of the allocated wireless spectrum are highly underutilized. Frequency-agile radios (FARs) have the potential to make opportunistic use of such spectrum holes without causing harmful interference to users of the allocated spectrum. Toward this goal, we develop a framework for modeling the interference caused by FARs employing spectrum access mechanisms based on the simple Listen-Before-Talk (LBT) scheme. Two variations of LBT are considered: individual LBT, whereby the FARs act independently of each other; and collaborative LBT, whereby the FARs communicate with each other in order to more accurately identify the spectrum holes. Our analysis of the LBT scheme reveals the fundamental interdependencies among key system design metrics and provides a basis for analyzing more complex spectrum access methods. In particular, the analysis of LBT provides a lower bound on the capacity gain achievable by FARs employing spectrum-sharing schemes. Our numerical results show that the individual LBT scheme can provide substantial capacity gains, while even more gain can be achieved using the collaborative LBT schemes. Our analysis suggests that much greater gains should be achievable via spectrum access schemes that incorporate location information and/or more sophisticated group behaviors.

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

[2]  Robert C. Spicer,et al.  Author's biography , 1993 .

[3]  M. Lustgarten,et al.  An Empirical Propagation Model (EPM-73) , 1977, IEEE Transactions on Electromagnetic Compatibility.

[4]  J. Bates,et al.  Ultra sensitive TV detector measurements , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[5]  Henry L. Bertoni,et al.  Coverage prediction for mobile radio systems operating in the 800/900 MHz frequency range , 1988 .

[6]  G. Staple,et al.  The end of spectrum scarcity [spectrum allocation and utilization] , 2004, IEEE Spectrum.

[7]  Ainslie,et al.  CORRELATION MODEL FOR SHADOW FADING IN MOBILE RADIO SYSTEMS , 2004 .

[8]  Brian L. Mark,et al.  Modeling and analysis of fast handoff algorithms for microcellular networks , 2002, Proceedings. 10th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunications Systems.

[9]  Dipankar Raychaudhuri,et al.  A spectrum etiquette protocol for efficient coordination of radio devices in unlicensed bands , 2003, 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003..

[10]  Otilia Popescu,et al.  Water filling may not good neighbors make , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[11]  M. McHenry,et al.  The probe spectrum access method , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[12]  A. G. Longley,et al.  PREDICTION OF TROPOSPHERIC RADIO TRANSMISSION LOSS OVER IRREGULAR TERRAIN. A COMPUTER METHOD-1968 , 1968 .

[13]  N. K. Shankaranarayanan,et al.  Radio resource allocation in fixed broadband wireless networks , 1998, IEEE Trans. Commun..

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