Mode Selection for 5G Heterogeneous and Opportunistic Networks

5G and beyond networks will offer multiple communication modes including device-to-device and multi-hop cellular (or UE-to-network relay) communications. Several studies have shown that these modes can signi_cantly improve the Quality of Service (QoS), the spectrum and energy ef_ciency, and the network capacity. Recent studies have demonstrated that further gains can be achieved when integrating demand-driven opportunistic networking into Multi-Hop Cellular Networks (MCN). In opportunistic MCN connections, devices can exploit the delay tolerance of many mobile data services to search for the most ef_cient connections between nodes. The availability of multiple communication modes requires mode selection schemes capable to decide the optimum mode for each transmission. Mode selection schemes have been previously proposed to account for the introduction of D2D and MCN. However, existing mode selection schemes cannot integrate opportunistic MCN connections into the selection process. This paper advances the state of the art by proposing the _rst mode selection scheme capable to integrate opportunistic MCN communications within 5G and beyond networks. The conducted analysis demonstrates the potential of opportunistic MCN communications, and the capability of the proposed mode selection scheme to select the most adequate communication mode.This work was supported in part by the Spanish Ministry of Economy, Industry, and Competitiveness, AEI, and FEDER funds under Grant TEC2017-88612-RGrant TEC2014-57146-Rand in part by the Generalitat Valenciana under Grant GV/2016/049

Next Generation Opportunistic Networking in Beyond 5G Networks

Beyond 5G networks are expected to support massive traffic through decentralized solutions and advanced networking mechanisms. This paper aims at contributing towards this vision through the integration of device-centric wireless networks, including Device-to-Device (D2D) communications, and the Next Generation of Opportunistic networking (NGO). This integration offers multiple communication modes such as opportunistic cellular and opportunistic D2D-aided communications. Previous studies have demonstrated the potential and benefits of this integration in terms of energy efficiency, spectral efficiency and traffic offloading. We propose an integration of device-centric wireless networks and NGO that is not driven by a precise knowledge of the presence of the links. The proposed technique utilizes a novel concept of graph to model the evolution of the networking conditions and network connectivity. Uncertainties and future conditions are included in the proposed graph model through anticipatory mobile networking to estimate the transmission energy cost of the different communication modes. Based on these estimates, the devices schedule their transmissions using the most efficient communication mode. These decisions are later revisited in real-time using more precise knowledge about the network state. The conducted evaluation shows that the proposed technique significantly reduces the energy consumption (from 60% to 90% depending on the scenario) compared to traditional single-hop cellular communications and performs closely to an ideal “oracle based” system with full knowledge of present and future events. The transmission and computational overheads of the proposed technique show small impact on such energy gains.This work has been partially funded by the Spanish Ministry of Science, Innovation and Universities, AEI, and FEDER funds (TEC2017-88612-R)the Ministry of Science, Innovation and Universities (IJC2018-036862-I)the UMH (‘Ayudas a la Investigación e Innovación de la Universidad Miguel Hernández de Elche 2018’)and by the European Commission under the H2020 REPLICATE (691735), SoBigData (654024) and AUTOWARE (723909) project

A dynamic graph optimization framework for multihop device-to-device communication underlaying cellular networks

With emerging demands for local area and popular content sharing services, multihop device-to-device communication is conceived as a vital component of next-generation cellular networks to improve spectral reuse, bring hop gains, and enhance system capacity. Ripening these benefits depends on fundamentally understanding its potential performance impacts and efficiently solving several main technical problems. Aiming to establish a new paradigm for the analysis and design of multihop D2D communications, in this article, we propose a dynamic graph optimization framework that enables the modeling of large-scale systems with multiple D2D pairs and node mobility patterns. By inherently modeling the main technological problems for multihop D2D communications, this framework benefits investigation of theoretical performance limits and studying the optimal system design. Furthermore, these achievable benefits are demonstrated by examples of simulations under a realistic multihop D2D communication underlaying cellular network