Distributed Cross-Layer Optimization for Cognitive Radio Networks

This paper presents a distributed cross-layer optimization algorithm for a multi-hop cognitive radio network, with the objective of maximizing data rates for a set of user communication sessions. The authors study this problem with joint consideration of power control, scheduling, and routing. Even under a centralized approach, such a problem has a mixed integer nonlinear program formulation and is likely NP-hard. Thus, a distributed problem is very challenging. The main contribution of this paper is the development of a distributed optimization algorithm that iteratively increases data rates for user communication sessions. During each iteration, the algorithm has routing, minimalist scheduling, and power control/scheduling modules to improve the current solution at all three layers.