RadioHound: A Pervasive Sensing Network for Sub-6 GHz Dynamic Spectrum Monitoring

We design a custom spectrum sensing network, called RadioHound, capable of tuning from 25 MHz to 6 GHz, which covers nearly all widely-deployed wireless activity. We describe the system hardware and network infrastructure in detail with a view towards driving the cost, size, and power usage of the sensors as low as possible. The system estimates the spatial variation of radio-frequency power from an unknown random number of sources. System performance is measured by computing the mean square error against a simulated radio-frequency environment. We find that the system performance depends heavily on the deployment density of the sensors. Consequently, we derive an expression for the sensor density as a function of environmental characteristics and confidence in measurement quality.

[1]  D. H. McLain,et al.  Two Dimensional Interpolation from Random Data , 1976, Comput. J..

[2]  Michael L. Honig,et al.  Spectrum markets: motivation, challenges, and implications , 2010, IEEE Communications Magazine.

[3]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[4]  Ben Y. Zhao,et al.  Towards commoditized real-time spectrum monitoring , 2014, HotWireless@MobiCom.

[5]  Hao Wu,et al.  A Survey of Localization in Wireless Sensor Network , 2012, Int. J. Distributed Sens. Networks.

[6]  Shang-Liang Chen,et al.  Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.

[7]  R. Bansal,et al.  Antenna theory; analysis and design , 1984, Proceedings of the IEEE.

[8]  Martin Haenggi,et al.  Stochastic Geometry for Wireless Networks , 2012 .

[9]  Bhaskar Krishnamachari,et al.  Ecolocation: a sequence based technique for RF localization in wireless sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

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

[11]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[12]  J.-E. Berg,et al.  Path loss and fading models for microcells at 900 MHz , 1992, [1992 Proceedings] Vehicular Technology Society 42nd VTS Conference - Frontiers of Technology.

[13]  Martin Haenggi,et al.  Unique coverage in Boolean models , 2016, ArXiv.

[14]  Ben Y. Zhao,et al.  Empirical Validation of Commodity Spectrum Monitoring , 2016, SenSys.

[15]  D. Shepard.  A two-dimensional interpolation function for irregularly-spaced data , 1968, ACM National Conference.

[16]  D. T. Lee,et al.  Two algorithms for constructing a Delaunay triangulation , 1980, International Journal of Computer & Information Sciences.

[17]  A. D. Maude.  Interpolation - Mainly for Graph Plotters , 1973, Comput. J..

[18]  Juhani Hallio,et al.  Distributed Spectrum Sensing Using Low Cost Hardware , 2016, J. Signal Process. Syst..

[19]  Zhi Ding,et al.  Opportunistic spectrum access in cognitive radio networks , 2008, IJCNN.

[20]  I. K. Grain.  Computer interpolation and contouring of two-dimensional data: A review , 1970 .