Joint optimization of energy efficiency and spectrum efficiency in 5G ultra-dense networks

The heterogeneous deployment of ultra dense small cells such as femtocells in the coverage area of the traditional macrocells is seen as a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the fifth generation wireless network. However, the unplanned and ultra-dense deployment of femtocells will lead to increase in total energy consumption, cross-tier interference (interference between macrocells and femtocells), co-tier interference (interference between neighbouring femtocells) and inadequate QoS provisioning. Therefore, there is a need to develop a radio resource allocation algorithm that will jointly maximize the energy efficiency (EE) and spectrum efficiency (SE) of the overall networks. Unfortunately, maximizing the EE results in low performance of the SE and vice versa. This paper investigates how to balance the trade-off that arises when maximizing both the EE and the SE simultaneously. The joint EE and SE maximization problem is formulated as a multi-objective optimization problem, which is later converted into a single-objective optimization problem using the weighted sum method. An iterative algorithm based on the Lagrangian dual decomposition method is proposed. Simulation results show that the proposed algorithm achieves an optimal trade-off between the EE and the SE with fast convergence.