Energy-efficient resource allocation in future wireless networks by sequential fractional programming

This overview paper discusses the framework of sequential fractional programming for energy efficiency maximization in future 5G networks. One of the main features of future systems will be the presence of severe multi-user interference and the need of improved energy efficiency compared to present systems. However, present approaches to energy efficiency maximization, which are based on the theory of fractional programming, result in an exponential complexity in interference-limited networks. In this context, the work shows how to extend available fractional programming approaches to obtain radio resource allocations enjoying strong optimality properties, while at the same time requiring an affordable complexity to be computed. The resulting framework is termed sequential fractional programming, and several examples of its applications to leading 5G candidate technologies are discussed in detail.