Energy efficiency is a major concern in the emerging mobile cellular wireless networks since massive connectivity is to be expected with high energy requirements from the network operators. Non-orthogonal multiple access (NOMA) being the frontier multiple access scheme for 5G, there exists numerous research attempts on enhancing the energy efficiency of NOMA enabled wireless networks while maintaining its outstanding performance metrics such as high throughput, data rates and capacity maximized optimally.The concept of green NOMA is introduced in a generalized manner to identify the energy efficient NOMA schemes. These schemes will result in an optimal scenario in which the energy generated for communication is managed sustainably. Hence, the effect on the environment, economy, living beings, etc is minimized. The recent research developments are classified for a better understanding of areas which are lacking attention and needs further improvement. Also, the performance comparison of energy efficient, NOMA schemes against conventional NOMA is presented. Finally, challenges and emerging research trends, for energy efficient NOMA are discussed.

Under a dense and large IoT network, a star topology where each device is directly connected to the Internet gateway may cause serious waste of energy and congestion issues. Grouping network devices into clusters provides a suitable architecture to reduce the energy consumption and allows an effective management of communication channels. Although several clustering approaches were proposed in the literature, most of them use the single-hop intra-clustering model. In a large network, the number of clusters increases and the energy draining remains almost the same as in un-clustered architecture. To solve the problem, several approaches use the k-hop intra-clustering to generate a reduced number of large clusters. However, k-hop proposed schemes are, generally, centralized and only assume the node direct neighbors information which lack of robustness. In this regard, the present work proposes a distributed approach for the k-hop intra-clustering called Distributed Clustering based 2-Hop Connectivity (DC2HC). The algorithm uses the two-hop neighbors connectivity to elect the appropriate set of cluster heads and strengthen the clusters connectivity. The objective is to optimize the set of representative cluster heads to minimize the number of long range communication channels and expand the network lifetime. The paper provides the convergence proof of the proposed solution. Simulation results show that our proposed protocol outperforms similar approaches available in the literature by reducing the number of generated cluster heads and achieving longer network lifetime.

Reliable and efficient transmission of emergency calls during a massive network failure is both an indispensable and challenging task. In this paper, we propose a novel fully 3GPP and 5G compatible emergency call protocol named 5G StandalOne Service (5G-SOS). A 5G-SOS-enabled emergency service provides potential out-of-coverage victims’ devices with a way to contact the 4G/5G core network through D2D multi-hop relaying protocol. The objective of 5G-SOS is to maintain this connection even when a large fraction of the network infrastructure is destroyed. 5G-SOS is a fully distributed protocol designed to generate zero additional control traffic and to adapt its parameters based on the local emergency call congestion. Therefore, devices behave as an ad-hoc network with the common purpose to ensure the best chances for emergency call transfer within a reasonable delay. A densely populated Traverse city of Michigan, USA, with a 15,000 population, is used to evaluate 5G-SOS under extreme emergency scenarios. The performance of 5G-SOS is shown to be significant when compared with existing protocols, namely, M-HELP and FINDER, in terms of transmission success rate, end-to-end latency, network traffic control, and energy management. 5G-SOS provides satisfactory performance (success rate of 50%) even when the number of simultaneous emergency calls is very high (5000 calls over 10 min). On average, 5G-SOS performs 24.9% better than M-HELP and 73.9% than FINDER in terms of success rate. Additionally, 5G-SOS reduces the average end-end latency of the emergency calls transfer by 20.8% compared to M-HELP and 61.7% compared to FINDER.

One of the most challenging tasks in a disaster scenario is the detection and localization of victims with high accuracy and minimum delay, especially in out-of-coverage areas. In the event of a disaster that disrupts the cellular network infrastructure, emergency calls can be relayed to the core network via multi-hop D2D communications. In this paper, a localization system is proposed that uses radio measurements obtained through such D2D multi-hop assisted emergency calls to localize in-coverage and out-of-coverage devices. To address the uncertainty and gradual reception of data in real-time in this scenario, a dynamic constraint satisfaction-based Multi Victim Localization Algorithm (MVLA) is proposed. This algorithm locates multi-hop devices in a progressive propagation manner to provide fast and accurate updates on victim locations. Additionally, three modes of ${MVLA}$ , namely ${MVLA}_{recent}$ , ${MVLA}_{seq}$ , and ${MVLA}_{all}$ are proposed. Simulation results demonstrate that ${MVLA}_{all}$ has a lower localization error compared to ${MVLA}_{recent}$ and ${MVLA}_{seq}$ . Moreover, ${MVLA}_{all}$ , is compared with an existing particle filtering-based localization algorithm called RSSI Monte-Carlo Boxed Localization ( RSSI-MCL ) under an increasing number of emergency user devices and functional gNodeBs. Results show that ${MVLA}_{all}$ significantly outperforms the RSSI-MCL method in terms of localization accuracy and computational delay.