A New Systematic Framework for Autonomous Cross-Layer Optimization

Cross-layer optimization solutions have been proposed in recent years to improve the performance of wireless users that operate in a time-varying, error-prone network environment. However, these solutions often rely on centralized cross-layer optimization solutions that violate the layered network architecture of the protocol stack by requiring layers to provide access to their internal protocol parameters to other layers. This paper presents a new systematic framework for cross-layer optimization, which allows each layer to make autonomous decisions to maximize the wireless user´s utility by optimally determining what information should be exchanged among layers. Hence, this cross-layer framework preserves the current layered network architecture. Since the user interacts with the wireless environment at various layers of the protocol stack, the cross-layer optimization problem is solved in a layered fashion such that each layer adapts its own protocol parameters and exchanges information (messages) with other layers that cooperatively maximize the performance of the wireless user. Based on the proposed layered framework, we also design a message-exchange mechanism that determines the optimal cross-layer transmission strategies, given the user´s experienced environment dynamics.