A new theoretic framework for cross-layer optimization with message exchanges

Existing cross-layer optimization solutions are often based on the assumption that each layer’s parameters are fully accessible to other layers or a centralized optimizer, thereby violating the layered network architecture of the protocol stack. This paper presents a new systematic framework named layered Markov decision process (MDP) for cross-layer optimization, which allows each layer to make autonomous decisions individually and determine the optimal message to be exchanged among layers in order to cooperatively maximize the utility of the wireless station. Hence, this layered cross-layer framework does not change the current layered architecture and is suitable for the delay-sensitive applications over wireless networks.