Eduardo Baena

Dr. Eduardo Baena

Institute for the Wireless Internet of Things, Northeastern University, Boston, Massachusetts, USA
orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 March 2019 in Sensors
Verified
Journal Article
Open access
PDF file
Sergio FortesSergio Fortes
Sergio Fortes
JRJosé Antonio Santoyo Ramón
José Antonio Santoyo Ramón
DPDavid Palacios
David Palacios
Eduardo BaenaEduardo Baena
Eduardo Baena
RMRocío Mora-García
Rocío Mora-García
Raquel Barco MorenoRaquel Barco Moreno
Raquel Barco Moreno
For the past few years, the concept of the Internet of Things (IoT) has been a recurrent view of the technological environment where nearly every object is expected to be connected to the network. This infrastructure will progressively allow one to monitor and efficiently manage the environment. Until recent years, the IoT applications have been constrained by the limited computational capacity and especially by efficient communications, but the emergence of new communication technologies allows us to overcome most of these issues. This situation paves the way for the fulfillment of the Smart-City concept, where the cities become a fully efficient, monitored, and managed environment able to sustain the increasing needs of its citizens and achieve environmental goals and challenges. However, many Smart-City approaches still require testing and study for their full development and adoption. To facilitate this, the university of Málaga made the commitment to investigate and innovate the concept of Smart-Campus. The goal is to transform university campuses into “small” smart cities able to support efficient management of their area as well as innovative educational and research activities, which would be key factors to the proper development of the smart-cities of the future. This paper presents the University of Málaga long-term commitment to the development of its Smart-Campus in the fields of its infrastructure, management, research support, and learning activities. In this way, the adopted IoT and telecommunication architecture is presented, detailing the schemes and initiatives defined for its use in learning activities. This approach is then assessed, establishing the principles for its general application.

17 February 2021 in Sensors
Verified
Journal Article
Open access
PDF file
OPOswaldo Peñaherrera-Pulla
Oswaldo Peñaherrera-Pulla
CBCarlos Baena
Carlos Baena
Sergio FortesSergio Fortes
Sergio Fortes
Eduardo BaenaEduardo Baena
Eduardo Baena
Raquel Barco MorenoRaquel Barco Moreno
Raquel Barco Moreno
Cloud Gaming is a cutting-edge paradigm in the video game provision where the graphics rendering and logic are computed in the cloud. This allows a user’s thin client systems with much more limited capabilities to offer a comparable experience with traditional local and online gaming but using reduced hardware requirements. In contrast, this approach stresses the communication networks between the client and the cloud. In this context, it is necessary to know how to configure the network in order to provide service with the best quality. To that end, the present work defines a novel framework for Cloud Gaming performance evaluation. This system is implemented in a real testbed and evaluates the Cloud Gaming approach for different transport networks (Ethernet, WiFi, and LTE (Long Term Evolution)) and scenarios, automating the acquisition of the gaming metrics. From this, the impact on the overall gaming experience is analyzed identifying the main parameters involved in its performance. Hence, the future lines for Cloud Gaming QoE-based (Quality of Experience) optimization are established, this way being of configuration, a trendy paradigm in the new-generation networks, such as 4G and 5G (Fourth and Fifth Generation of Mobile Networks).

18 June 2025 in IEEE Transactions on Mobile Computing
Verified
Journal Article
Closed access
DVDavide Villa
Davide Villa
IKImran Khan
Imran Khan
FKFlorian Kaltenberger
Florian Kaltenberger
NHNicholas Hedberg
Nicholas Hedberg
RSRúben Soares da Silva
Rúben Soares da Silva
DKDimitrios Koutsonikolas
Dimitrios Koutsonikolas
As Fifth generation (5G) cellular systems transition to softwarized, programmable, and intelligent networks, it becomes fundamental to enable public and private 5G deployments that are (i) primarily based on software components while (ii) maintaining or exceeding the performance of traditional monolithic systems and (iii) enabling programmability through bespoke configurations and optimized deployments. This requires hardware acceleration to scale the Physical (PHY) layer performance, programmable elements in the Radio Access Network (RAN) and intelligent controllers at the edge, careful planning of the Radio Frequency (RF) environment, as well as end-to-end integration and testing. In this paper, we describe how we developed the programmable X5G testbed, addressing these challenges through the deployment of the first 8-node network based on the integration of NVIDIA Aerial RAN CoLab Over-the-Air (ARC-OTA), OpenAirInterface (OAI), and a near-real-time RAN Intelligent Controller (RIC). The Aerial Software Development Kit (SDK) provides the PHY layer, accelerated on Graphics Processing Unit (GPU), with the higher layers from the OAI open-source project interfaced with the PHY through the Small Cell Forum (SCF) Functional Application Platform Interface (FAPI). An E2 agent provides connectivity to the O-RAN Software Community (OSC) nearreal-time RIC. We discuss software integration, network infrastructure, and a digital twin framework for RF planning. We then profile the performance with up to 4 Commercial Off-the-Shelf (COTS) smartphones for each base station with iPerf and video streaming applications, as well as up to 25 emulated User Equipments (UEs), measuring a cell rate higher than 1.65 Gbps in downlink and 143 Mbps in uplink.

29 October 2021 in Sensors
Verified
Journal Article
Open access
PDF file
Sergio FortesSergio Fortes
Sergio Fortes
Noelia Hidalgo-TrianaNoelia Hidalgo-Triana
Noelia Hidalgo-Triana
JSJuan-Manuel Sánchez-La-Chica
Juan-Manuel Sánchez-La-Chica
LGLuz Garcia-Ceballos
Luz Garcia-Ceballos
JCJuan Cantizani-Estepa
Juan Cantizani-Estepa
AGAlberto García-Marín
Alberto García-Marín
At present, climate change, pollution, and uncontrolled urbanism threaten not only natural ecosystems, but also the urban environment. Approaches to mitigate these challenges and able to provide an alternative for the use of the space are deemed to be multidisciplinary, combining architecture, vegetation integration, circular economy and information and communications technologies (ICT). University campuses are a key scenario to evaluate such solutions as their student and research community is intrinsically willing to support these experiences and provide a wide knowledge on the fields necessary for their design and implementation. However, the creation of areas combining usability and sustainability is commonly lacking a multidisciplinary approach combining all these different perspectives. Hence, the present work aims to overcome this limitation by the development of a novel integrated approach for campus spaces for co-working and leisure, namely a “Smart Tree”, where novel architecture, furniture design, flora integration, environmental sensoring and communications join together. To this end, a survey of the literature is provided, covering related approaches as well as general principles behind them. From this, the general requirements and constraints for the development of the Smart Tree area are identified, establishing the main interactions between the architecture, greening and ICT perspectives. Such requirements guide the proposed system design and implementation, whose impact on the environment is analyzed. Finally, the research challenges and lessons learned for their development are identified in order to support future works.

14 October 2019 in IEEE Vehicular Technology Magazine
Verified
Journal Article
Closed access
AHAna Herrera-Garcia
Ana Herrera-Garcia
Sergio FortesSergio Fortes
Sergio Fortes
Eduardo BaenaEduardo Baena
Eduardo Baena
Jessica MendozaJessica Mendoza
Jessica Mendoza
CBCarlos Baena
Carlos Baena
Raquel Barco MorenoRaquel Barco Moreno
Raquel Barco Moreno
Thanks to evolving cellular telecommunication networks, providers can deploy a wide range of services. Soon, 5G mobile networks will be available to handle all types of services and applications for vast numbers of users through their mobile equipment. To effectively manage new 5G systems, end-to-end (E2E) performance analysis and optimization will be key features. However, estimating the end-user experience is not an easy task for network operators. The amount of end-user performance information operators can measure from the network is limited, complicating this approach. Here we explore the calculation of service metrics [known as key quality indicators (KQIs)] from classic low-layer measurements and parameters. We propose a complete machine-learning (ML) modeling framework. This system’s low-layer metrics can be applied to measure service-layer performance. To assess the approach, we implemented and evaluated the proposed system on a real cellular network testbed.

20 July 2022 in IEEE Transactions on Network and Service Management
Verified
Journal Article
Open access
OPOswaldo Peñaherrera-Pulla
Oswaldo Peñaherrera-Pulla
CBCarlos Baena
Carlos Baena
Sergio FortesSergio Fortes
Sergio Fortes
Eduardo BaenaEduardo Baena
Eduardo Baena
Raquel Barco MorenoRaquel Barco Moreno
Raquel Barco Moreno
Extended Reality (XR) arises as one of the current cutting-edge educational and entertainment emergent technologies. This service differs from traditional video streaming approaches due to its immersive experience, which allows the user to enjoy omnidirectional multimedia. However, the service experience must be guaranteed to avoid side effects such as cybersickness or disorientation. This work presents a framework to assess 360-video service streaming performance over mobile networks through Key Quality Indicators (KQIs) using VR (Virtual Reality) HMD (Head Mounted Device). The testbed is composed of a 360-video client for DASH (Dynamic Adaptive Streaming over HTTP), which playbacks multimedia content from a video server located in the cloud while KQI measuring tasks are performed in the user as on the network sides. Various metrics are collected such as resolution, frame rate, initial playback time, throughput, stall events, and round trip time (RTT), among various others. Finally, a performance comparison between LTE and 5G technologies is provided. Results from the KQI measurement highlight the potential of the new generation of mobile networks in the provision of service with high-quality levels of experience.