Robotics Inspired Opportunistic Routing for Cognitive Radio Using Potential Fields

Abstract

Potential field based routing is proposed for cognitive radio networks. This approach is inspired by the analogy between packet routing in cognitive radio networks and robot navigation in the presence of obstacles. Using this analogy a general framework for packet routing using potential fields is introduced, in which desired communication destinations can be considered as attractive forces and sources of interference as repulsive forces. Furthermore, three examples of how to construct such potential fields are proposed. Two optimal potential field models with respect to delay and energy and one suboptimal, but computationally simple, potential field based on virtual forces are derived. The potential field approach facilitates using physics-based models of propagation in interference modeling. This paper shows that potential field techniques from robotics can provide an attractive solution to routing in a cognitive radio network and that they can achieve good performance in terms of end-to-end delay and energy consumption.