###### Abstract  
The introduction of fifth-generation (5G) mobile networks leads to an increase in energy consumption and higher operational costs for mobile network operators (MNOs). Consequently, the optimization of 5G networks' energy efficiency is crucial, both in terms of reducing MNO costs and in terms of the negative environmental impact. However, many aspects of the 5G mobile network technology itself have been standardized, including the 5G network slicing concept. This enables the creation of multiple independent logical 5G networks within the same physical infrastructure. Since the only necessary resources in 5G networks need to be used for the realization of a specific 5G network slice, the question of whether the implementation of 5G network slicing can contribute to the improvement of 5G and future sixth-generation networks' energy efficiency arises. To tackle this question, this review paper analyzes 5G network slicing and the energy demand of different network slicing use cases and mobile virtual network operator realizations based on network slicing. The paper also overviews standardized key performance indicators for the assessment of 5G network slices' energy efficiency and discusses energy efficiency in 5G network slicing lifecycle management. In particular, to show how efficient network slicing can optimize the energy consumption of 5G networks, versatile 5G network slicing use case scenarios, approaches, and resource allocation concepts in the space, time, and frequency domains have been discussed, including artificial intelligence-based implementations of network slicing. The results of the comprehensive discussion indicate that the different implementations and approaches to network slicing pave the way for possible further reductions in 5G MNO energy costs and carbon dioxide emissions in the future. 5G; network slice; energy efficiency; software define network (SDN); virtual network function (VNF); third-generation partnership project (3 GPP); MNO 2024243242423242  
many cases, lead to increased telecommunication service prices. By 2030, in the best-case scenario, it is projected that 8% of the global demand for electrical energy will come from the information and communication technology (ICT) sector [1]. The aforementioned factors indicate that striving towards better energy efficiency (EE) in mobile networks is one of the key goals in the planning, implementation, and operation of 5G mobile networks. Knowing this, EE improvement entails optimizing resources that can lower the energy consumption, mitigate the emission of greenhouse gases, and incorporate renewable energy sources in the power supply of network elements [2]. It is expected that with the full practical global implementation of 5G networks by 2030, the data transfer speed will be increased by a factor of 1000, while, simultaneously, network energy consumption will be reduced by a factor of 2. To achieve such energy efficiency improvements that are 2000 times higher per transferred bit in comparison with the energy efficiency of previous network generations, different solutions need to be implemented in order to enable the optimization of 5G network energy consumption [3]. One of the prominent solutions dedicated to the optimization of 5G network resource usage is a technique known as network slicing. Fifth-generation network slicing enables the creation and existence of multiple independent logical 5G networks within the same physical infrastructure. This offers great flexibility for specific mobile network implementations which can contribute to the reduction in service implementation costs and extension of service offerings, and can ensure better exploitation of the mobile network operator (MNO) resources. In this context, the question that arises is whether the implementation of network slicing in 5G networks can contribute to the improvement in network energy efficiency.