5G Development: Automation and the Role of Artificial Intelligence

[1]  Shih Yu Chang,et al.  Determination of Wireless Networks Parameters through Parallel Hierarchical Support Vector Machines , 2012, IEEE Transactions on Parallel and Distributed Systems.

[2]  Peter Dayan,et al.  Q-learning , 1992, Machine Learning.

[3]  Richard Demo Souza,et al.  A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks , 2017, IEEE Communications Surveys & Tutorials.

[4]  Tapani Ristaniemi,et al.  Location accuracy impact on cell outage detection in LTE-A networks , 2015, 2015 International Wireless Communications and Mobile Computing Conference (IWCMC).

[5]  Martin Björklund,et al.  YANG - A Data Modeling Language for the Network Configuration Protocol (NETCONF) , 2010, RFC.

[6]  Liam Quinn The Evolving 5G Landscape , 2020 .

[7]  Albert A. Lysko,et al.  Overview of 9 Open-Source Resource Orchestrating ETSI MANO Compliant Implementations: A Brief Survey , 2019, 2019 IEEE 2nd Wireless Africa Conference (WAC).

[8]  Faqir Zarrar Yousaf,et al.  Benchmarking open source NFV MANO systems: OSM and ONAP , 2020, Comput. Commun..

[9]  Alexandros Kaloxylos,et al.  A Survey and an Analysis of Network Slicing in 5G Networks , 2018, IEEE Communications Standards Magazine.

[10]  Judith Kelner,et al.  An autonomic and policy-based authorization framework for OpenFlow networks , 2017, 2017 13th International Conference on Network and Service Management (CNSM).

[11]  Tan-Hsu Tan,et al.  Resource Allocation For D2D Communications With A Novel Distributed Q-Learning Algorithm In Heterogeneous Networks , 2018, 2018 International Conference on Machine Learning and Cybernetics (ICMLC).

[12]  Song Guo,et al.  Resource Management at the Network Edge: A Deep Reinforcement Learning Approach , 2019, IEEE Network.

[13]  Raquel Barco,et al.  Automatic Root Cause Analysis for LTE Networks Based on Unsupervised Techniques , 2016, IEEE Transactions on Vehicular Technology.

[14]  Faqir Zarrar Yousaf,et al.  On the Challenges and KPIs for Benchmarking Open-Source NFV MANO Systems: OSM vs ONAP , 2019, ArXiv.

[15]  Lee Soohwan,et al.  Trends of 5G Network Automation and Intelligence Technologies Standardization , 2019 .

[16]  John Riedl,et al.  An algorithmic framework for performing collaborative filtering , 1999, SIGIR '99.

[17]  John M. Cioffi,et al.  A Learning-Based Network Selection Method in Heterogeneous Wireless Systems , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[18]  Bhaskar Krishnamachari,et al.  Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks , 2018, IEEE Transactions on Cognitive Communications and Networking.

[19]  Guoyin Wang,et al.  Self-training semi-supervised classification based on density peaks of data , 2018, Neurocomputing.

[20]  Rouzbeh Razavi,et al.  A Fuzzy reinforcement learning approach for self-optimization of coverage in LTE networks , 2010, Bell Labs Technical Journal.

[21]  Kaibin Huang,et al.  Communication, Computing, and Learning on the Edge , 2018, 2018 IEEE International Conference on Communication Systems (ICCS).

[22]  Kin K. Leung,et al.  Demo abstract: Distributed machine learning at resource-limited edge nodes , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[23]  Abbas Javed,et al.  Critical Analysis of Learning Algorithms in Random Neural Network Based Cognitive Engine for LTE Systems , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).

[24]  P. Sandhir,et al.  A Neural Network Demand Prediction Scheme for Resource Allocation in Cellular Wireless Systems , 2008, 2008 IEEE Region 5 Conference.

[25]  Fabrice Guillemin,et al.  Network Slice Life-Cycle Management Towards Automation , 2019, 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).

[26]  Yueshen Xu,et al.  QoS Prediction for Mobile Edge Service Recommendation With Auto-Encoder , 2019, IEEE Access.

[27]  Arsalan Darbandi,et al.  Enabling proactive self-healing by data mining network failure logs , 2017, 2017 International Conference on Computing, Networking and Communications (ICNC).

[28]  James Irvine,et al.  An Advanced SOM Algorithm Applied to Handover Management Within LTE , 2013, IEEE Transactions on Vehicular Technology.

[29]  K. Hatonen,et al.  Trial report on self-organizing map based analysis tool for radio networks [GSM applications] , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[30]  Ahmed Karmouch,et al.  Towards Autonomic Network Management: an Analysis of Current and Future Research Directions , 2009, IEEE Communications Surveys & Tutorials.

[31]  Muhammad Ali Imran,et al.  A learning‐based approach for autonomous outage detection and coverage optimization , 2016, Trans. Emerg. Telecommun. Technol..

[32]  Nabanita Das,et al.  Mobile User Tracking Using A Hybrid Neural Network , 2005, Wirel. Networks.

[33]  Ulf Lindqvist,et al.  Detecting anomalies in cellular networks using an ensemble method , 2013, Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013).

[34]  Jani Puttonen,et al.  Coverage optimization for Minimization of Drive Tests in LTE with extended RLF reporting , 2010, 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[35]  César Viho,et al.  Semi-Supervised Deep Learning-Based Methods for Indoor Outdoor Detection , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[36]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[37]  Joseph Isabona,et al.  Handoffs Decision Optimization of Mobile Celular Networks , 2015, 2015 International Conference on Computational Science and Computational Intelligence (CSCI).

[38]  Floriano De Rango,et al.  A novel passive bandwidth reservation algorithm based on Neural Networks path prediction in wireless environments , 2010, Proceedings of the 2010 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS '10).

[39]  Xiaodong Ji,et al.  A dynamic affinity propagation clustering algorithm for cell outage detection in self-healing networks , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[40]  Takaya Miyazawa,et al.  Automation of 5G Network Slice Control Functions with Machine Learning , 2019, IEEE Communications Standards Magazine.

[41]  Anku Jaiswal,et al.  Predicting unlabeled traffic for intrusion detection using semi-supervised machine learning , 2016, 2016 International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT).

[42]  Dong Liang,et al.  Self-configuration and self-optimization in LTE-advanced heterogeneous networks , 2013, IEEE Communications Magazine.

[43]  Adnan Abu-Dayya,et al.  A framework for classification of Self-Organising network conflicts and coordination algorithms , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[44]  Alejandro Quintero A user pattern learning strategy for managing users' mobility in UMTS networks , 2005, IEEE Transactions on Mobile Computing.

[45]  F. M. Landstorfer,et al.  Radio network planning with neural networks , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[46]  Tara Ali-Yahiya,et al.  End-to-End Automation of 5G Networks , 2019, Mob. Inf. Syst..

[47]  Danish Rafique,et al.  Machine learning for network automation: overview, architecture, and applications [Invited Tutorial] , 2018, IEEE/OSA Journal of Optical Communications and Networking.

[48]  John Keeney,et al.  5G networks must be autonomic! , 2018, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium.

[49]  Lorenzo Favalli,et al.  Dynamic Cell Sectorization Using Clustering Algorithms , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[50]  Victor C. M. Leung,et al.  Deep-Reinforcement-Learning-Based Optimization for Cache-Enabled Opportunistic Interference Alignment Wireless Networks , 2017, IEEE Transactions on Vehicular Technology.

[51]  Hai Jin,et al.  Modeling User Activity Patterns for Next-Place Prediction , 2017, IEEE Systems Journal.

[52]  José Roberto Boisson de Marca,et al.  Load balancing in self-organized heterogeneous LTE networks: A statistical learning approach , 2015, LATINCOM.

[53]  Filip De Turck,et al.  Design and Evaluation of a Self-Learning HTTP Adaptive Video Streaming Client , 2014, IEEE Communications Letters.

[54]  Bill Karakostas Towards Autonomic Cloud Configuration and Deployment Environments , 2014, 2014 International Conference on Cloud and Autonomic Computing.

[55]  Zhi Ding,et al.  Wavelet transform processing for cellular traffic prediction in machine learning networks , 2015, 2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP).

[56]  Tapani Ristaniemi,et al.  An Approach for Network Outage Detection from Drive-Testing Databases , 2012, J. Comput. Networks Commun..

[57]  Sherif Akoush,et al.  The Use of Bayesian Learning of Neural Networks for Mobile User Position Prediction , 2007, Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

[58]  Christian M. Mueller,et al.  A Cell Outage Detection Algorithm Using Neighbor Cell List Reports , 2008, IWSOS.

[59]  H. Vincent Poor,et al.  Distributed learning in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[60]  Hamid Aghvami,et al.  Internet of skills, where robotics meets AI, 5G and the Tactile Internet , 2017, 2017 European Conference on Networks and Communications (EuCNC).

[61]  D. C. Cox,et al.  A handoff algorithm for wireless systems using pattern recognition , 1998, Ninth IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (Cat. No.98TH8361).

[62]  Alejandro Quintero,et al.  A profile-based strategy for managing user mobility in third-generation mobile systems , 2004, IEEE Communications Magazine.

[63]  Joseph Dureau,et al.  Federated Learning for Keyword Spotting , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[64]  Kai Yang,et al.  Deep Network Analyzer (DNA): A Big Data Analytics Platform for Cellular Networks , 2017, IEEE Internet of Things Journal.

[65]  César Viho,et al.  Mobile User Environment Detection using Deep Learning based Multi-Output Classification , 2019, 2019 12th IFIP Wireless and Mobile Networking Conference (WMNC).

[66]  Mehdi Bennis,et al.  Living on the edge: The role of proactive caching in 5G wireless networks , 2014, IEEE Communications Magazine.

[67]  Pinyi Ren,et al.  Semi-supervised learning based big data-driven anomaly detection in mobile wireless networks , 2018, China Communications.

[68]  Nelson Luis Saldanha da Fonseca,et al.  Redundant placement of virtualized network functions for LTE evolved Multimedia Broadcast Multicast Services , 2017, 2017 IEEE International Conference on Communications (ICC).

[69]  Zwi Altman,et al.  Automated Diagnosis for UMTS Networks Using Bayesian Network Approach , 2008, IEEE Transactions on Vehicular Technology.

[70]  Chetan Nadiger,et al.  Federated Reinforcement Learning for Fast Personalization , 2019, 2019 IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE).

[71]  Kin K. Leung,et al.  Adaptive Federated Learning in Resource Constrained Edge Computing Systems , 2018, IEEE Journal on Selected Areas in Communications.

[72]  Luis Jorge Romero 5G standardization in ETSI , 2018, Elektrotech. Informationstechnik.

[73]  Nararat Ruangchaijatupon,et al.  Enhancing indoor positioning based on partitioning cascade machine learning models , 2014, 2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).

[74]  Xin Li,et al.  Network Slicing for 5G: Challenges and Opportunities , 2017, IEEE Internet Computing.

[75]  Stuart Clayman,et al.  Towards autonomic management of software enabled networks , 2013, 2013 8TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE).

[76]  Tapani Ristaniemi,et al.  Anomaly Detection Algorithms for the Sleeping Cell Detection in LTE Networks , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).