The characterization of the global maximum of energy efficiency (EE) problems in wireless networks is a chal- lenging problem due to its nonconvex nature in interference channels. The aim of this work is to develop a new and general framework to achieve globally optimal power control solutions. First, the hidden monotonic structure of the most common EE maximization problems is exploited jointly with fractional programming theory to obtain globally optimal solutions whose complexity, however, turns out to be exponential. To overcome this issue, we also propose a framework to compute suboptimal power control strategies characterized by affordable complexity. This achieved by merging fractional programming and sequential optimization. The proposed monotonic framework is used to shed lights on the ultimate performance of wireless networks in terms of EE and also to benchmark the performance of the practical, but suboptimal, solutions. Numerical results show that the sequential fractional programming approach attains global optimality in many cases.