Abstract The ultra‐dense deployment of pico cells in 5G heterogeneous networks (HetNets) has raised serious concerns regarding interference and energy consumption. Both industry and academia are focusing on enhancing network energy efficiency (EE) while maintaining satisfactory quality of service (QoS) levels. However, finding an optimal solution to NEE is very challenging, especially in ultra‐dense HetNets. Here, a user association and power management algorithm is presented that follows a heuristic approach and aims to maximize EE while satisfying other network requirements. The proposed algorithm associates users based on criteria that consider the users’ EE and minimizes energy consumption by intermittently switching into sleep mode base stations with the highest impact on overall network EE. The performance of this solution is evaluated in a realistic multi‐cell two‐tier scenario considering both co‐tier and cross‐tier interference by comparing it with two other solutions: a heuristic approach based on standardized eICIC, and an optimization approach based on Lagrangian dual decomposition. The simulation results show that our solution outperforms benchmarking solutions in terms of EE, average user rate, and network throughput while minimizing energy consumption.

In this paper, we analyze requirements of next generation 112 emergency services in the era of ubiquitous mobile devices and sensors and present the design, implementation, and piloting results of our testbed, which was developed within the H2020 project NEXES. The system leverages a multihop location-aware PEMEA routing network that finds the geographically closest responsible public service answering point (PSAP) and supports cross-border application roaming. Our reference mobile implementation utilizes multiple device and network-based positioning technologies, which, combined, both outperform traditional cell-tower based positioning and provide a means for detecting fraudulent calls. The system is extensible and can establish a variety of communication channels after the initial emergency session is set up; we demonstrate this with an interoperable WebRTC-based video call. The obtained results demonstrate the viability and flexibility of PEMEA-based over-the-top emergency services, show high user acceptance when comparing them with existing solutions, and thus pave the road for further rollout of such systems.

The assurance of quality of experience (QoE) and provisioning of high throughput of the system represent the main goals of future wireless and mobile networks. This paper presents novel and practical cross-layer QoE-aware radio resource allocation (RRA) algorithms for the downlink of a heterogeneous orthogonal frequency division multiple access (OFDMA) system. The objective of the proposed algorithms is to assure the appropriate level of QoE for each user of the system by incorporating application-layer parameters and subjective human perception of quality into the RRA process. We propose two user-oriented joint subcarrier and power allocation algorithms with low complexity for real-time and interactive services. The first algorithm dynamically allocates resources by assuring the same level of QoE to all users of the system, whereas the second algorithm introduces the efficient trade-off between the user's QoE and the spectral efficiency of the system. By considering application-layer parameters and user's perception of quality, high users' QoE and explicit control of data rates can be achieved. The numerical results show that the proposed algorithms achieve significant increase in the level of QoE compared to previous works, a fair distribution of capacity among users and near to optimal solution of QoE for the OFDMA system.