## 1 Introduction  
Device-to-device (D2D) communications in infrastructure networks have been studied actively since the 1990s [1], due to the potential to reduce delays, increase throughput, and to improve power or energy efficiency. D2D enables cooperative services and data dissemination methods and can be used in coming 5G networks over various radio access technologies (RATs). Actively developed application areas currently include 3 GPP proximity services, public safety communications, vehicle-to-everything (V2X) communications, autonomous ships, the Internet of Things (IoT) and wearables [1; 2; 3; 4; 5; 6; 7; 8; 9]. For instance, the number of wearable devices is predicted to grow from 325 million in 2016 to 929 million in 2021, when 7% of the devices may use in-built cellular connectivity [10]. Other devices, on the other hand, may obtain cellular access through e.g., smart phones. An essential part of the use of D2D in the mentioned application areas is energy efficiency [11; 12; 13; 14], which is heavily dependent on the used radio interfaces. In general, the role of WiFi and other small cell technologies is important, as 60% of mobile data was offloaded onto the fixed network through WiFi or femtocell in 2016 [10]. In addition, computing power is important, especially in short distance communication [15]. Compared to theoretical power control work, such as [16; 17], one is able to estimate more accurately the resource use in a practical network if measurement-based models for air interfaces are available. The power consumption of different 3 GPP long-term evolution (LTE) and WiFi interfaces has been actively measured and modelled in recent years [18; 19; 20; 21; 22]. Both user device and base station power consumption models are available. However, there is a lot of variation in measurement campaigns between different protocols and between different smart phone models. Some of the differences can be explained by the new generation of air interfaces and partially the power consumption changes are due to the different use of the user devices. For example, social networking [23] generates a constant stream of traffic, causing the mobile device to frequently move between idle and connected states. Energy state transitions alone cost energy, but these transitions also cause excessive signaling overhead in (3 GPP) networks. Mechanisms such as adaptive discontinuous reception (DRX), user equipment (UE) assistance, energy harvesting, and massive multiple-input multiple-output (MIMO) antenna systems at the base station side have been proposed to reduce the power consumption of LTE mobiles [24; 25; 26; 27; 28; 29]. We analyzed the power consumption of user devices in D2D communications in [30] and studied the power consumption from the base station perspective in [31] using many different measurement-based LTE and WiFi models. In this paper, we extend and unify analysis of [30] and [31] and update the results with the latest power consumption models [32]. In addition, we review the status in 3 GPP standardization of D2D communications, focusing especially on IoT, wearables, and V2X communications [33; 34; 35; 36; 37; 38]. The analysis shows where the industry is going and deepens the discussion on energy efficiency aspects in depicted networks. We believe that quality of service (QoS) and priority management mechanisms such as network slicing [35; 36] can also be used to improve the performance of D2D networks. We will extend the state-of-the art in [11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32], summarizing the novelty of this paper as: (1) Review of the status of the 3 GPP standardization, including a summary of D2D features of different releases of the standard. (2) Definition of a set of D2D application scenarios with multiple data delivery options. (3) Analysis of the power consumption of the network in the depicted scenarios using measurement-based models.