Ferran Adelantado

Bio: Ferran Adelantado is an academic researcher from Open University of Catalonia. The author has contributed to research in topics: Cellular network & Heterogeneous network. The author has an hindex of 16, co-authored 60 publications receiving 1632 citations. Previous affiliations of Ferran Adelantado include Polytechnic University of Catalonia.

Understanding the Limits of LoRaWAN

Abstract: Low-power wide area networking technology offers long-range communication, which enables new types of services. Several solutions exist; LoRaWAN is arguably the most adopted. It promises ubiquitous connectivity in outdoor IoT applications, while keeping network structures and management simple. This technology has received a lot of attention in recent months from network operators and solution providers. However, the technology has limitations that need to be clearly understood to avoid inflated expectations and disillusionment. This article provides an impartial and fair overview of the capabilities and limitations of LoRaWAN. We discuss those in the context of use cases, and list open research and development questions.

Exploring the Performance Boundaries of NB-IoT

Abstract: Narrow band-Internet of Things (NB-IoT) has just joined the low power wide area network (LPWAN) community. Unlike most of its competitors, NB-IoT did not emerge from a blank slate. Indeed, it is closely linked to Long Term Evolution (LTE), from which it inherits many of the features that undoubtedly determine its behavior. In this paper, we empirically explore the boundaries of this technology, analyzing from a user’s point of view critical characteristics such as energy consumption, reliability, and delays. The results show that its performance in terms of energy is comparable and even outperforms, in some cases, an LPWAN reference technology like LoRa, with the added benefit of guaranteeing delivery. However, the high variability observed in both energy expenditure and network delays call into question its suitability for some applications, especially those subject to service-level agreements.

Energy- and Spectrum-Efficient User Association in Millimeter-Wave Backhaul Small-Cell Networks

Abstract: Macrocells are expected to be densely overlaid by small cells (SCs) to meet increasing capacity demands. Due to their dense deployment, some SCs will not be connected directly to the core network, and thus, they may forward their traffic to the neighboring SCs until they reach it, thereby forming a multihop backhaul (BH) network. This is a promising solution, since the expected short length of BH links enables the use of millimeter-wave (mmWave) frequencies to provide high-capacity BH. In this context, user association becomes challenging due to the multihop BH architecture, and therefore, new optimal solutions should be developed. Thus, in this paper, we study the user association problem aiming at the joint maximization of network energy efficiency (EE) and spectrum efficiency (SE), without compromising the user quality of service (QoS). The problem is formulated as an $\varepsilon$ -constraint problem, which considers the transmit energy consumption both in the access network, i.e., the links between the users and their serving cells, and the BH links. The optimal Pareto-front solutions of the problem are analytically derived for different BH technologies, and insights are gained into the EE and SE tradeoff. The proposed optimal solutions, despite their high complexity, can be used as a benchmark for the performance evaluation of user association algorithms. We also propose a heuristic algorithm, which is compared with reference solutions under different traffic scenarios and BH technologies. Our results motivate the use of mmWave BH, whereas the proposed algorithm achieves near-optimal performance.

Energy-efficient user association in cognitive heterogeneous networks

Abstract: Due to the ever increasing data traffic demands, which are directly connected to increased energy consumption, it becomes challenging for operators to achieve capacity enhancement while limiting their electric bill. To that end, exploiting the context awareness of future cognitive networks is expected to play a key role. Next generation cellular networks are about to include a plethora of small cells, with users being able to communicate via multiple bands. Given that small cells are expected to be eventually as close as 50 m apart, not all of them will have a direct connection to the core network; thus, multihop communication through neighboring small cells may be required. In such architectures, the user association problem becomes challenging, with backhaul energy consumption being a definitive parameter. Thus, in this article, we study the user association problem in cognitive heterogeneous networks. We evaluate the existing approaches in terms of energy efficiency and show the potential of exploiting the available context-aware information (i.e., users' measurements and requirements, knowledge of the network architecture, and the available spectrum resources of each base station) to associate the users in an energy-efficient way, while maintaining high spectrum efficiency. Our study considers both the access network and backhaul energy consumption, while the performance of the association algorithms is evaluated under two different case study scenarios.

Energy-efficient context-aware user association for outdoor small cell heterogeneous networks

Abstract: To meet the ever-increasing traffic demands, future cellular networks are about to include a plethora of small cells (SCs), with user equipments (UEs) being able of communicating via multiple bands. Given that SCs are expected to be eventually as close as 50 m apart, some of them will not have a direct connection to the core network, and thus will forward their traffic to the neighboring SCs until they reach it. In such architectures, the user association problem becomes challenging with backhaul (BH) energy consumption playing a key role. Thus, in this paper, we study the user association problem aiming at maximizing the network energy efficiency. The problem is formulated as an optimization problem, which is NP-hard. Therefore, we propose a cognitive heuristic algorithm that exploits context-aware information (i.e., UE measurements and requirements, the HetNet architecture knowledge and the available spectrum resources of each base station (BS)) to associate the UEs in an energy-efficient way, while considering both the access and the BH energy consumption. We evaluate the performance of the proposed algorithm under two study-case scenarios and we prove that it achieves significantly higher energy efficiency than the reference algorithms, while maintaining high spectral efficiency.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Low Power Wide Area Networks: An Overview

Abstract: Low power wide area (LPWA) networks are attracting a lot of attention primarily because of their ability to offer affordable connectivity to the low-power devices distributed over very large geographical areas. In realizing the vision of the Internet of Things, LPWA technologies complement and sometimes supersede the conventional cellular and short range wireless technologies in performance for various emerging smart city and machine-to-machine applications. This review paper presents the design goals and the techniques, which different LPWA technologies exploit to offer wide-area coverage to low-power devices at the expense of low data rates. We survey several emerging LPWA technologies and the standardization activities carried out by different standards development organizations (e.g., IEEE, IETF, 3GPP, ETSI) as well as the industrial consortia built around individual LPWA technologies (e.g., LoRa Alliance, Weightless-SIG, and Dash7 alliance). We further note that LPWA technologies adopt similar approaches, thus sharing similar limitations and challenges. This paper expands on these research challenges and identifies potential directions to address them. While the proprietary LPWA technologies are already hitting the market with large nationwide roll-outs, this paper encourages an active engagement of the research community in solving problems that will shape the connectivity of tens of billions of devices in the next decade.

Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions

Abstract: Network slicing has been identified as the backbone of the rapidly evolving 5G technology. However, as its consolidation and standardization progress, there are no literatures that comprehensively discuss its key principles, enablers, and research challenges. This paper elaborates network slicing from an end-to-end perspective detailing its historical heritage, principal concepts, enabling technologies and solutions as well as the current standardization efforts. In particular, it overviews the diverse use cases and network requirements of network slicing, the pre-slicing era, considering RAN sharing as well as the end-to-end orchestration and management, encompassing the radio access, transport network and the core network. This paper also provides details of specific slicing solutions for each part of the 5G system. Finally, this paper identifies a number of open research challenges and provides recommendations toward potential solutions.

Digital Twin: Values, Challenges and Enablers From a Modeling Perspective

Abstract: Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

5G Backhaul Challenges and Emerging Research Directions: A Survey

Abstract: 5G is the next cellular generation and is expected to quench the growing thirst for taxing data rates and to enable the Internet of Things. Focused research and standardization work have been addressing the corresponding challenges from the radio perspective while employing advanced features, such as network densification, massive multiple-input-multiple-output antennae, coordinated multi-point processing, inter-cell interference mitigation techniques, carrier aggregation, and new spectrum exploration. Nevertheless, a new bottleneck has emerged: the backhaul. The ultra-dense and heavy traffic cells should be connected to the core network through the backhaul, often with extreme requirements in terms of capacity, latency, availability, energy, and cost efficiency. This pioneering survey explains the 5G backhaul paradigm, presents a critical analysis of legacy, cutting-edge solutions, and new trends in backhauling, and proposes a novel consolidated 5G backhaul framework. A new joint radio access and backhaul perspective is proposed for the evaluation of backhaul technologies which reinforces the belief that no single solution can solve the holistic 5G backhaul problem. This paper also reveals hidden advantages and shortcomings of backhaul solutions, which are not evident when backhaul technologies are inspected as an independent part of the 5G network. This survey is key in identifying essential catalysts that are believed to jointly pave the way to solving the beyond-2020 backhauling challenge. Lessons learned, unsolved challenges, and a new consolidated 5G backhaul vision are thus presented.