Algorithm for Electromagnetic Power Estimation in Radio Environment Map

International Journal of Electronics and Communication Engineering
© 2020 by SSRG - IJECE Journal
Volume 7 Issue 5
Year of Publication : 2020
Authors : Tilal Elsheikh Ahmed Osman, Osman Mudathir ELFadil2
How to Cite?

Tilal Elsheikh Ahmed Osman, Osman Mudathir ELFadil2, "Algorithm for Electromagnetic Power Estimation in Radio Environment Map," SSRG International Journal of Electronics and Communication Engineering, vol. 7,  no. 5, pp. 46-55, 2020. Crossref,


Perhaps the most important part of building a radio environment map is estimating the electromagnetic field strength. The more efficient the estimation algorithm used, the more accurate the radio environment map reached. A new hybrid algorithm to estimate electromagnetic power - using sensing data gathered by monitoring sensors - is proposed in this paper. A certain propagation model was used considering all physical phenomena along the whole path of the electromagnetic wave (including losses, attenuation).A theoretical variogram based on a certain propagation model was used and fitted using a real variogram through regression. This method simulates the real physical phenomenon more accurately. The proposed algorithm is mainly based on weighting parameters (that rely on the variogram method) and a factor taking the similarities because of the neighborhood. Experimental results showed close similarity between given and computed electromagnetic power through regression curves and objective evaluation indices. The proposed method's main contribution is gathering the merits of using a suitable propagation model and a theoretical variogram, besides getting merits of traditional methods(like Inverse Distance Weight) using new vision.


Radio environment map, Histogram, Propagation model


[1] Zhao, L.Morales, J.Gaaeddert, K.KBae, J.Sum and J.H.Reed, “applying radio environment map to cognitive
wireless regional area network,” 2007, 2nd IEE international symposium on new Frontiers in the dynamic spectrum access network. Dublin, 2007, pp115-118.
[2] Ojaniemi, J.Kalliovaara, A.Alam, J.Poikonen and R.Wichman,” optimal field measurement design for radio environment mapping,”2013 47th Annual Conference on Information Sciences and Systems (CISS), Bltimore, MD,2013, PP.1-6.
[3] M.Pesko, T.Jovorink, A.Kosir, M.Sutlar, M.Mohorcic, “radio environment maps: a survey of construction methods,” ks11 transaction on internet and information systems, vol -8, no.11, 2014, pp 3789-3809.
[4] J.Riihijarvi, P.Mahonen, W.Wellens, and M. Gordziel, “characterization and modeling of spectrum for Dynamic spectrum Access with spatial statistics and random field,” In IEEE 19th international symposium on personal, indoor and mobile radio communications, Cannes PP.1-6.
[5] D.Denkovski, V.Atanasovski, L.Gavrilovska, J.Riihijarive and P.mahonen “ Reliability of Radio Environment Map (REM): a case of spatial interpolation technique,” in the 7th international ICI Conference On Cognitive Radio Oriented Wireless Networks And Communications ( CROWNCOM), in Stockholm, pp.248-253.
[6] C. Phillips, M.Ton, D. Sicker, and D.Grunwald, “practical Radio environment mapping with geostatistics,” in IEEE international symposium on Dynamic spectrum Access Network, in Bellevue, WA, PP.422- 433.
[7] S. Ulaganathan, D.Deschrijver, M. Pakparvar, I. CouKuyt, W.Liu, D. Plets, W. Josph, T. Dhaene, L. Martens and I. Moerman “ Building accurate radio environment map from Multi – Fidelity spectrum sensing data,” in wireless networks, vol. 22, no.8, pp. 2551- 2562.
[8] K.Sato, and T. Fujii, proposed a paper titled “Kriging – based interference power constraint: integrated Design of the Radio Environment Map (REM) and transmission power,” in IEEE transactions on cognitive communications and Networking, pp (99), pp. 1-1.