  Cognitive Autonomous Networks (CAN) are promoted to advance Self Organizing
Network (SON), replacing rule-based SON Functions (SFs) with Cognitive
Functions (CFs), which learn optimal behavior by interacting with the network.
As in SON, CFs do encounter conflicts due to overlap in parameters or
objectives. However, owing to the non-deterministic behavior of CFs, these
conflicts cannot be resolved using rulebased methods and new solutions are
required. This paper investigates the CF deployments with and without a
coordination mechanism, and proves both heuristically and mathematically that a
coordination mechanism is required. Using a two-CF Multi-Agent-System model
with the possible types of conflicts, we show that the challenge is a typical
bargaining problem, for which the optimal response is the Nash bargaining
Solution (NBS). We use NBS to propose a coordination mechanism design that is
capable of resolving the conflicts and show via simulations how implementation
of the proposed solution is feasible in real life scenario.
