Limited Log-Distance Path Loss Model Path Loss Exponent Estimation using Deep Deterministic Policy Gradient

Low-cost wireless devices often rely on the log-distance path loss model for determining the distance between two devices based on radio signal strength. The log-distance path loss model relies on a properly determined path-loss exponent to produce accurate results; however, this variable can be difficult to obtain or estimate accurately, especially indoors. While many statistical models and methods can be utilized to estimate the path-loss exponent, it is often determined experimentally, which is both impractical and error-prone. This work explores the feasibility of a novel application of Deep Deterministic Policy Gradient to learn the path-loss exponent of a small limited indoor space based on the RSSI information transmitting between three wireless beacons. This will be accomplished with no prior knowledge of the structural complexities of the indoor building.