Genetic Algorithm Optimization in a Cognitive Radio for Autonomous Vehicle Communications

Abstract

Autonomous vehicles travel through a varying environment that is not limited to the physical terrain but also includes the "RF terrain". The autonomous vehicle must be able to adapt to the varying RF conditions. "Cognitive radios" are being developed that address this issue. This paper discusses the use of genetic algorithms (GA) to implement the adaptive processes for a cognitive radio on an autonomous vehicle. Specifically GA's are used to solve the optimization of RF parameters for a wireless network. In particular, a fitness measure is derived which provides a figure of merit for the performance of the GA in relation to overall RF performance. Additionally, a chromosome structure is derived which consists of "RF genes". Each gene is a binary string representing some aspect or parameter of the RF environment. Finally the GA determines a set of RF parameters for optimal radio communications in the varying RF environment.