Browsing Scientific Publications in Information and Communication Technology by Author "Beferull-Lozano, Baltasar"
Now showing items 1-20 of 37
-
Accurate Graph Filtering in Wireless Sensor Networks
Ben Saad, Leila; Beferull-Lozano, Baltasar (Peer reviewed; Journal article, 2020)Wireless sensor networks (WSNs) are considered as a major technology enabling the Internet-of-Things (IoT) paradigm. The recent emerging graph signal processing field can also contribute to enabling the IoT by providing ... -
Adaptive Medium Access Control for Distributed Processing in Wireless Sensor Networks
Asensio-Marco, César; Beferull-Lozano, Baltasar (Journal article; Peer reviewed, 2018) -
Channel Gain Cartography via Mixture of Experts
Lopez Ramos, Luis Miguel; Teganya, Yves; Beferull-Lozano, Baltasar; Kim, Seung-Jun (Journal article; Peer reviewed, 2020) -
Consensus-Based Distributed State Estimation of Biofilm in Reverse Osmosis Membranes by WSNs
Alonso, Daniel; Asensio-Marco, César; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2017)The appearance of biofilm has become a serious problem in many reverse osmosis based systems such as the ones found in water treatment and desalination plants. In these systems, the use of traditional techniques such as ... -
Cross-layer MAC Protocol for Unbiased Average Consensus under Random Interference
Asensio-Marco, César; Alonso-Román, Daniel; Beferull-Lozano, Baltasar (Journal article; Peer reviewed, 2018)Wireless Sensor Networks have been revealed as a powerful technology to solve many different problems through sensor nodes cooperation. One important cooperative process is the so-called average gossip algorithm, which ... -
Data-Driven Pump Scheduling for Cost Minimization in Water Networks
Bhardwaj, Jyotirmoy; Krishnan, Joshin Parakkulangarayil; Beferull-Lozano, Baltasar (Chapter, 2021)Pumps consume a significant amount of energy in a water distribution network (WDN). With the emergence of dynamic energy cost, the pump scheduling as per user demand is a computationally challenging task. Computing the ... -
Decentralized subspace projection in large networks
Ghari, Siavash Mollaebrahim; Asensio-Marco, César; Romero, Daniel; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2018) -
Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications
Jaiswal, Rahul Kumar; Elnourani, Mohamed; Deshmukh, Siddharth; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2022)This paper investigates the problem of transfer learning in radio map estimation for indoor wireless communications, which can be exploited for different applications, such as channel modelling, resource allocation, network ... -
Dynamic network identification from non-stationary vector autoregressive time series
Lopez-Ramos, Luis M.; Romero, Daniel; Zaman, Bakht; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2018) -
Energy Efficient Consensus Over Directed Graphs
Asensio-Marco, César; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2018)Consensus algorithms are iterative methods that represent a basic building block to achieve superior functionalities in increasingly complex sensor networks by facilitating the implementation of many signal-processing tasks ... -
Experimental Validation for Spectrum Cartography using Adaptive Multi-kernels
Idsøe, Henning; Hamid, Mohamed; Cenkeramaddi, Linga Reddy; Jordbru, Thomas; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2017) -
Fast Distributed Subspace Projection via Graph Filters
Weerasinghe, Thilina Nuwan; Romero, Daniel; Asensio-Marco, César; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2018)A significant number of linear inference problems in wireless sensor networks can be solved by projecting the observed signal onto a given subspace. Decentralized approaches avoid the need for performing such an operation ... -
Fast Graph Filters for Decentralized Subspace Projection
Romero, Daniel; Ghari, Siavash Mollaebrahim; Beferull-Lozano, Baltasar; Marco, Cesar Asensio (Peer reviewed; Journal article, 2020)A number of inference problems with sensor networks involve projecting a measured signal onto a given subspace. In existing decentralized approaches, sensors communicate with their local neighbors to obtain a sequence of ... -
Forecasting Aquaponic Systems Behaviour With Recurrent Neural Networks Models
Cardenas, Juan Diego; Elnourani, Mohamed Gafar Ahmed; Beferull-Lozano, Baltasar (Peer reviewed; Journal article, 2022)Aquaponic systems provide a reliable solution to grow vegetables while cultivating fish (or other aquatic organisms) in a controlled environment. The main advantage of these systems compared with traditional soil-based ... -
Joint Topology and Radio Resource Optimization for Device-to-Device Based Mobile Social Networks
Hamid, Mohamed; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2018)In this paper, we consider a joint topology and radio resource optimization for device-to-device (D2D) based mobile social networks. The considered social network is an interest based which is modeled as a d -intersection ... -
Localization-Free Power Cartography
Teganya, Yves; Lopez-Ramos, Luis M.; Romero, Daniel; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2018)Spectrum cartography constructs maps of metrics such as channel gain or received signal power across a geographic area of interest using measurements of spatially distributed sensors. Applications of these maps include ... -
Location-free Indoor Radio Map Estimation using Transfer learning
Jaiswal, Rahul Kumar; Elnourani, Mohamed; Deshmukh, Siddharth; Beferull-Lozano, Baltasar (Chapter; Peer reviewed, 2023)Accurate estimation of radio maps is important for various applications of wireless communications, such as network planning, and resource allocation. To learn accurate radio map models, one needs to have accurate knowledge ... -
Location-Free Spectrum Cartography
Teganya, Yves; Romero, Daniel; Lopez-Ramos, Luis M.; Beferull-Lozano, Baltasar (Journal article; Peer reviewed, 2019) -
Low-complexity detection for uplink massive MIMO SCMA systems
Sharma, Sanjeev; Deka, Kuntal; Beferull-Lozano, Baltasar (Journal article; Peer reviewed, 2020) -
Online Hyperparameter Search Interleaved with Proximal Parameter Updates
Lopez-Ramos, Luis M.; Beferull-Lozano, Baltasar (Chapter, 2020)There is a clear need for efficient hyperparameter optimization (HO) algorithms for statistical learning, since commonly applied search methods (such as grid search with N-fold cross-validation) are inefficient and/or ...