Influence of transmitter configurations on spatial statistics of radio environment maps

We study the influence of the configuration and distribution of transmitters on radio environment maps. We adopt a statistical approach, treating total received power as a random field characterised with second-order statistics. Using extensive simulations we characterise the effects of changing node counts, distribution of node locations, transmit powers and propagation environments on the studied statistics. We also comment and discuss applications of these results and the methods employed especially from the dynamic spectrum access point of view.

[1]  M. Hata,et al.  Empirical formula for propagation loss in land mobile radio services , 1980, IEEE Transactions on Vehicular Technology.

[2]  Jung-Sun Um,et al.  Applying Radio Environment Maps to Cognitive Wireless Regional Area Networks , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[3]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[4]  C.S. Hood,et al.  Long-Term, Wide-Band Spectral Monitoring in Support of Dynamic Spectrum Access Networks at the IIT Spectrum Observatory , 2008, 2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[5]  N. Cressie.  Fitting variogram models by weighted least squares , 1985 .

[6]  Janne Riihijärvi,et al.  Characterization and modelling of spectrum for dynamic spectrum access with spatial statistics and random fields , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[8]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[9]  Janne Riihijärvi,et al.  Spatial Statistics of Spectrum Usage: From Measurements to Spectrum Models , 2009, 2009 IEEE International Conference on Communications.

[10]  Janne Riihijarvi,et al.  Exploiting Spatial Statistics of Primary and Secondary Users towards Improved Cognitive Radio Networks , 2008 .

[11]  Tobias Renk,et al.  Occupation Measurements Supporting Dynamic Spectrum Allocation for Cognitive Radio Design , 2007, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[12]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[13]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[14]  Adrian Baddeley,et al.  spatstat: An R Package for Analyzing Spatial Point Patterns , 2005 .

[15]  Anant Sahai,et al.  Cooperative Sensing among Cognitive Radios , 2006, 2006 IEEE International Conference on Communications.

[16]  Petri Mähönen,et al.  Lessons learned from an extensive spectrum occupancy measurement campaign and a stochastic duty cycle model , 2009, TRIDENTCOM.