"5G new radio (NR) sidelink (SL) is envisioned as a key enabler of high speed, low latency applications like automated driving. To meet the high data rate requirements for such applications, SL support at mmWave and sub-THz frequencies with large bandwidths will be essential. Several enhancements and optimizations will be...
Video services traffic over the internet has drastically grown these past years, currently representing more than 80% of the internet bandwidth [1]. The massive usage of unicast delivery leads to network congestion that can result in poor quality of experience for the viewer, high delivery cost for operators and increased...
"The increased mobile connectivity, the range and number of services available in various computing environments in the network, demand mobile applications to be highly dynamic to be able to efficiently incorporate those services into applications, along with other local capabilities on mobile devices. However, the monolithic structure and mostly static...
We propose XRC, an explicit rate control algorithm that overcomes the poor performance of commonly used TCP variants in cellular networks. XRC exploits an explicit feedback from the radio access network that is aware of the physical, network and transport layer information of all UEs as well as resource distribution...
RESEARCH PAPER / Oct 2021
/
Audio processing,
Neural network,
Machine learning/ Deep learning /Artificial Intelligence
Music source separation is the task of isolating individual instruments which are mixed in a musical piece. This task is particularly challenging, and even state-of-the-art models can hardly generalize to unseen test data. Nevertheless, prior knowledge about individual sources can be used to better adapt a generic source separation model...
The backdoor attack raises a serious security concern to deep neural networks, by fooling a model to misclassify certain inputs designed by an attacker. In particular, the trigger-free backdoor attack is a great challenge to be detected and mitigated. It targets one or a few specific samples, called target samples,...
RESEARCH PAPER / Oct 2021
/
Computer Vision,
Neural network,
Machine learning/ Deep learning /Artificial Intelligence
High quality facial attribute editing in videos is a challenging problem as it requires the modifications to be realistic and consistent throughout the video frames. Previous works address the problem with auto-encoder architectures and rely on adversarial training to ensure the attribute editing and the temporal consistency of the results....
RESEARCH PAPER / Sep 2021
/
Video coding,
Compression,
Machine learning/ Deep learning /Artificial Intelligence Neural network
Despite many modern applications of Deep Neural Networks (DNNs), the large number of parameters in the hidden layers makes them unattractive for deployment on devices with storage capacity constraints. In this paper we propose a Data-Driven Low-rank (DDLR) method to reduce the number of parameters of pretrained DNNs and expedite...
RESEARCH PAPER / Aug 2021
/
Neural network,
Machine learning/ Deep learning /Artificial Intelligence,
Computer Vision
Deep neural networks (DNNs) have recently achieved great success in many machine learning tasks including computer vision and speech recognition. However, existing DNN models are computationally expensive and memory demanding, hindering their deployment in devices with low memory and computational resources or in applications with strict latency requirements. In addition,...
RESEARCH PAPER / Dec 2020
/
5G,
Machine learning/ Deep learning /Artificial Intelligence,
Network and Communications
This document describes the winning solution to the GNN Challenge 2020 organized by the Barcelona Neural Networking Center for the ITU Artificial Intelligence/Machine Learning in 5G Challenge. We first describe our methodology, then give the set of hyper-parameters that allowed us to achieve the best score with an average relative...
RESEARCH PAPER / Dec 2020
/
Network and Communications,
5G,
Wireless communication,
Computing and Optimization
For Internet operators, on-line service providers and end-users, representative operational measurements are crucial to monitor and diagnose the performance of networks and on-line services. While numerous approaches have been proposed to measure performance, only a few works fully adopt an end-user perspective by taking measurements from within web browsers. In...
RESEARCH PAPER / Nov 2020
/
5G,
Wireless communication,
Network and Communications,
Computing and Optimization
This paper investigates the task management for cooperative mobile edge computing (MEC), where a set of geographically distributed heterogeneous edge nodes not only cooperate with remote cloud data centers but also help each other to jointly process tasks and support real-time IoT applications at the edge of the network. Especially,...
RESEARCH PAPER / Sep 2020
/
Wireless communication,
Network and Communications,
Computing and Optimization
Mobile edge computing (MEC) is an emerging paradigm that integrates computing resources in wireless access networks to process computational tasks in close proximity to mobile users with low latency. In this paper, we propose an online double deep Q networks (DDQN) based learning scheme for task assignment in dynamic MEC...
Efficient Nearest Neighbor (NN) search in high-dimensional spaces is a foundation of many multimedia retrieval systems. A common approach is to rely on Product Quantization, which allows the storage of large vector databases in memory and efficient distance computations. Yet, implementations of nearest neighbor search with Product Quantization have their...
"A recently celebrated kind of deep neural networks is Generative Adversarial Networks. GANs are generators of samples from a distribution that has been learned; they are up to now centrally trained from local data on a single location. We question the performance of training GANs using a spread dataset over...
In order for network slicing to deliver on its promise as an effective tool to generate new revenues and profitability, new business models must match the dynamic technical and operational changes that it brings. Significant progress is being made in demonstrations and trials, as highlighted in this report and the...
Learning parameters from voluminous data can be prohibitive in terms of memory and computational requirements. We propose a ‘compressive learning’ framework, where we estimate model parameters from a sketch of the training data. This sketch is a collection of generalized moments of the underlying probability distribution of the data. It...
The success of Google’s PageRank algorithm popularized graphs as a tool to model the web’s navigability. At that time, the web topology was resulting from human edition of hyper-links. Nowadays, that topology is mostly resulting from algorithms. In this paper, we propose to study the topology realized by a class...
A large portion of data mining and analytic services use modern machine learning techniques, such as deep learning. The state-of-the-art results by deep learning come at the price of an intensive use of computing resources. The leading frameworks (e.g., TensorFlow) are executed on GPUs or on high-end servers in datacenters....
Some structural characteristics of online discussions have been successfully modeled in the recent years. When parameters of these models are properly estimated, the models are able to generate synthetic discussions that are structurally similar to the real discussions. A common aspect of these models is that they consider that all...
This chapter presents the Integrated Lens Antenna (ILA) technology as it evolved since its introduction aiming to respond to the needs of emerging applications such as high-data-rate communication, intelligent transport, and mm-wave imaging. The topics covered include the ILA design concepts as well as the electromagnetic phenomena intrinsic to dielectric...
Les liens DSL peuvent subir des pannes sporadiques entraînant des deconnexions ou un acces Internet dégradé. Ces pannes sont a l’origine d’une expérience utilisateur négative et générent des coûts pour les fournisseurs d’accès Internet (FAI) via des appels d’assistance technique. La prediction de pannes permet aux FAI de mettre en...
La recommandation joue un rôle central dans le e-commerce et dans l'industrie du divertissement. L'intérêt croissant pour la transparence algorithmique nous motive dans cet article à observer les résultats de recommandations sous la forme d'un graphe capturant les navigations proposées dans l'espace des items. Nous argumentons qu'une telle approche en...
Uncovering Influence Cookbooks : Reverse Engineering the Topological Impact in Peer Ranking Services
Ensuring the early detection of important social network users is a challenging task. Some peer ranking services are now well established, such as PeerIndex, Klout, or Kred. Their function is to rank users according to their influence. This notion of influence is however abstract, and the algorithms achieving this ranking...
Accounts are often shared by multiple users, each of them having different item consumption and temporal habits. Identifying of the active user can lead to improvements in a variety of services by switching from account personalized services to user personalized services. To do so, we develop a topic model extending...
Détecter au plus tôt les utilisateurs importants dans les réseaux sociaux est un problème majeur. Les services de classement d'utilisateurs (peer ranking) sont maintenant des outils bien établis, par des sociétés comme PeerIndex, Klout ou Kred. Leur fonction est de ``classer'' les utilisateurs selon leur influence. Cette notion est néanmoins...
Aggregation of streamed data is key to the expansion of the Internet of Things. This paper addresses the problem of designing a topology for reliably aggregating data flows from many devices arriving at a datacenter. Reliability here means ensuring operation without data loss. We seek a frugal solution that prevents...
InterDigital’s M2M team was recently published in the prestigious IEEE Communications Magazine with their article, “CA-P2P: Context-Aware Proximity-Based Peer-to-Peer Wireless Communications.” The work was co-authored by Chonggang Wang, Qing Li, Hongkun Li, Paul Russell, Jr. and Zhuo Chen, all engineers at InterDigital. The authors argue that CA-P2P may be a...
InterDigital’s CEO, Bill Merritt, will appear on The Fox Business Network’s “Countdown to the Closing Bell” tomorrow, Tuesday, July 22. Bill was invited to appear as part of a week-long series highlighting mid-cap companies with the best percentage gains year to date and, according to the show, InterDigital is among...
We’ve all been there, while attending a major event you snap a picture to capture a big moment and want to share that photo with friends, family and your social network. Unfortunately, so does everyone else. With the increased traffic, wireless networks become congested and connectivity becomes nearly impossible. Our...
BLOG / Nov 2014
/
Network of Networks,
Small Cells,
Network Operators,
Narayan Menon
/ Posted By: meghan.carney
With data access becoming increasingly ubiquitous, and the amount and variety of value-added services increasing daily, one question continues to grow in importance in the wireless world: what will be the future role of operators? How will they benefit from the growth in wireless they’ve done so much to drive?...
5G is theorized to be a fundamental shift and key enabler in the future of the digital world. The shift from 4G to 5G will encompass the emergence of new technologies and approaches to the Internet that will change the way people live, work and play. The new approaches may...
Last month, 5G World 2016 brought together a number of telecom industry leading companies, including InterDigital, to demonstrate their latest work in making 5G a reality and enabling services to run over it. On the floor of the show, 5G World TV caught up with InterDigital Europe’s Dirk Trossen on...
