Improving coverage prediction for primary multi-transmitter networks operating in the TV whitespaces

Future wireless networks will be able to exploit unused spectrum whitespaces in the currently underutilized terrestrial TV bands. In order to protect incumbent broadcasting systems from extensive interference from whitespace devices, accurate signal power estimations are needed. Reliable and robust models for predicting the radio propagation in those bands are thus a key enabler of secondary operations. Depending on their level of abstraction and the complexity of the environment, these models can perform quite well, but they require a significant amount of auxiliary information and fine-tuning. Additionally, they usually consider transmitters in one frequency band to have uncorrelated signals, an uncommon scenario in today's digital TV networks where the same geographical area is often served by multiple towers that form a single-frequency network (SFN). Using data from a measurement campaign carried out in a mid-sized Central European city we assess the accuracy of three widely used propagation models in predicting TV signal strengths for configurations of multiple high-power transmitters. We empirically show that the standard deviation of the estimation error is up to 4 dB higher in a multi-transmitter scenarios with correlated signals than in the single-transmitter case. We put the results in contrast to the prediction capabilities of a generic propagation model that estimates pathloss coefficients and individual correction factors from measurements and combines them with information on transmitter locations, power emissions and antenna patterns. Finally, we study the use of spatial statistics based techniques for directly estimating the coverage characteristics without relying on explicit transmitter information. We show that with only a small subset of measurement locations accuracy beyond standard pathloss models can be achieved.