A Novel Multiobjective Cell Switch-Off Method with Low Complexity for Realistic Cellular Deployments

Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes such as the need for minimizing the real-time complexity and the number of transitions as well as handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The method distinguishes itself from the other proposals in two ways: 1) The number of cell switch on/off transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where traffic is highly unbalanced, with neither compromising the Quality-of-Service (QoS) nor requiring heavy real-time processing.