In order to overcome the GPS positioning defects and realize the accurate positioning in the complex indoor environment, many practical indoor localization schemes are introduced, such as infrared, WIFI, Bluetooth, ZigBee, ultrasound, radio frequency identification (RFID), and ultra-wideband (UWB).
This scheme has many practical advantages in that it leverages known-fertile samples.
Modular operations are expensive in terms of energy consumption and computation time, which could make our in-situ schemes unapplicable to many practical sensor network settings.
Many experimentally successful systems offer efficient, practical schemes of close inbreeding.
Many surveys have implemented more convenient and economically practical schemes, though at the expense of sample quality.
However, while these schemes are theoretically feasible, there are many practical implementation difficulties on real world public cloud computing platforms.
All these aspects highlight the importance of the general scope of our contribution and the necessity to avoid an exclusive focus on the well-known OFDM or other case-specific schemes, which might be suboptimal in many practical cases.
There are many schemes for managing traffic, but not very many practical ways to reduce the number of vehicles on the roads.
Note that our adaptive algorithm only requires the FSMC model which can be found for many practical fading channels [21] and do not depend on Rayleigh fading assumption or Modulation schemes.
This fact, combined with the accuracy and the mass conservation of the exponential propagation scheme, makes the presented method a good candidate for solving many practical problems, including numerical weather prediction.
