Abstract

A novel coverage-prediction method for outdoor radio propagation based on the inversion theory is proposed here. Coverage prediction in a wireless cellular network is treated as an inverse problem instead of using high-precision geometric modeling. More precisely, the problem is solved by an inversion of the measured data under some <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> constraints, and the complicated propagation-prediction problem is reduced to solving a system of large-scale ill-condition equations. The effectiveness of the proposed method is demonstrated by using experiments under various radio environments in Guangdong, China. The prediction results are approximately consistent with independent checking samples, and the proposed strategy is compared with other existing approaches.

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