Communications Materials

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Scientific Publications

Journals and Magazine Articles

  1. H. Hellaoui, O. Bekkouche, M. Bagaa and T. Taleb. “Aerial Control System for Spectrum Efficiency in UAV-to-Cellular Communications”. In: IEEE Communications Magazine 56.10 (Oct. 2018), pp. 108–113. issn: 0163-6804. doi: 10.1109/MCOM.2018.1800078.
  2. S. Kim et al. “Sense-and-Predict: Harnessing Spatial Interference Correlation for Cognitive Radio Networks”. In: IEEE Transactions on Wireless Communications 18.5 (May 2019), pp. 2777–2793. issn: 1536-1276. doi:10.1109/TWC.2019.2908168.
  3. E. Y. Menta et al. “On the Performance of AoA–Based Localization in 5G Ultra–Dense Networks”. In: IEEE Access 7 (2019), pp. 33870–33880. issn: 2169-3536. doi: 10.1109/ACCESS.2019.2903633.
  4. M. Shin, J. Kim, and M. Levorato. “Auction-Based Charging Scheduling With Deep Learning Framework for Multi-Drone Networks”. In: IEEE Transactions on Vehicular Technology 68.5 (May 2019), pp. 4235–4248. issn: 0018-9545. doi: 10.1109/TVT.2019.2903144.
  5. T. Xie et al. “On the Power Leakage Problem in Millimeter-Wave massive MIMO with Lens Antenna Arrays”. In: IEEE Transactions on Signal Processing (2019), pp. 1–1. issn: 1053-587X. doi: 10.1109/TSP.2019.2926019.
  6. C. Zhu et al. “Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing”. In: IEEE Internet of Things Journal 6.3 (June 2019), pp. 4150–4161. issn: 2327-4662. doi: 10.1109/JIOT.2018.2875520.
  7. M. Choi, D. Yoon, and J. Kim. "Blind Signal Classi cation for Non-Orthogonal Multiple Access in Vehicular Networks". Accepted for IEEE Transactions on Vehicular Technology (2019), pp. 1-1. issn: 0018-9545. doi:10.1109/TVT.2019.2932407.
  8. J. Choi et al. "Random Access with Opportunity Detection in Wireless Networks". In: IEEE Wireless Communications Letters (2019), pp. 1-1., issn: 2162-2337. doi: 10.1109/LWC.2019.2921367.
  9. J. Song and W. Choi. "Mobility-Aware Content Placement for Device-to-Device Caching Systems". In: IEEE Transactions on Wireless Communications 18.7 (July 2019), pp. 3658{3668. issn: 1536-1276. doi: 10.1109/TWC.2019.2916781.
  10. M. Choi, A. No and M. Ji and J. Kim. "Markov Decision Policies for Dynamic Video Delivery in Wireless Caching Networks". Accepted for IEEE Transactions on Wireless Communications (2019).

Conference Papers

  1. B. Jin, J. Woo, and Y. Yi. “On the Asymptotic Content Routing Stretch in Network of Caches: Impact of Popularity Learning”. In: International Conference on Network Games, Control, and Optimization (NETGCOOP 2018). Ed. by J. Walrand et al. New York, Nov. 2018, pp. 145–163.
  2. D. Kwon and J. Kim, "Optimal Trajectory Learning for UAV-BS Video Provisioning System: A Deep Reinforcement Learning Approach," in Proceedings of the IEEE International Conference on Information Networking (ICOIN), Kuala Lumpur, Malaysia, January 2019.
  3. M. U. Sheikh, K. Ruttik, and Riku Jäntti. “Analysis of Indoor Solutions for Provision of Indoor Coverage at 3.5 GHz and 28 GHz for 5G System”. 26th IEEE International Conference in Telecommunications (ICT’19). Hanoi, Apr. 2019.
  4. M. U. Sheikh, K. Ruttik, and Riku Jäntti. “Performance Analysis of Vertical and Higher Order Sectorization in Urban Environment at 28 GHz”. 26th IEEE International Conference in Telecommunications (ICT’19). Hanoi, Apr. 2019.
  5. M. U. Sheikh, K. Ruttik, and Riku Jäntti. “Performance Evaluation of Switched Beam Antenna with Different Configurations at 28 GHz”. IEEE Wireless Communications and Networking Conference (WCNC) 2019. Marrakech, Apr. 2019.
  6. H. Cha and S. Kim. “A Reinforcement Learning Approach to Dynamic Spectrum Access in Internet-of-Things Networks”. 2019 IEEE International Conference on Communications (ICC 2019). May 2019, pp. 1–6. doi:10.1109/ICC.2019.8762091.
  7. M. Choi et al. “Probabilistic Caching Policy for Categorized Contents and Consecutive User Demands”. In: 2019 IEEE International Conference on Communications (ICC 2019). May 2019, pp. 1–6. doi:10.1109/ICC.2019.8761047.
  8. D. Kim et al. “Learning to Schedule Communication in Multi-agent Reinforcement Learning”. Seventh International Conference on Learning Representations (ICLR 2019). New Orleans, May 2019.
  9. M. Shin and J. Kim. “Randomized Adversarial Imitation Learning for Autonomous Driving”. In: 2019 International Joint Conference on Artificial Intelligence (IJCAI). Macao, May 2019.
  10. K. Son et al. “QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning”. 36th International Conference on Machine Learning (ICML 2019). Long Beach, Jun. 2019.
  11. D. Kwon, S. Park, and J. Kim, "Poster: Multi-Agent Deep Reinforcement Learning for Connected Vehicles," in Proceedings of the ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) (Extended Abstract), Seoul, Korea, June 2019.
  12. M. Noreikis, Y. Xiao, and Y. Jiang. “Edge capacity planning for real time compute-intensive applications”. IEEE International Conference on Fog Computing (ICFC 2019). Prague, Jun. 2019.
  13. J. Costa-Requena and A. Mohammedadem. "5G Network Slicing based on SDN and Machine Learning". 2019 European Conference on Networks and Communications (EuCNC). Valencia, June 2019.
  14. Y. Hong, Y. Kyung, and S.-L. Kim. "Multi-Robot Cooperative Patrolling Algorithm with Sharing Multiple Cycles," 2019 European Conference on Networks and Communications (EuCNC), Valencia, Spain, June 2019.
  15. J. Jeon, J. Kim, K. Kim, J. Kim, A. Mohaisen, and J.-K. Kim, "Privacy-Preserving Deep Learning Computation for Geo-Distributed Medical Big-Data Platforms," in Proceedings of the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) (Fast Abstract), Portland, Oregon, USA, June 2019.
  16. M. Shin and J. Kim, "Adversarial Imitation Learning via Random Search," in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 2019.
  17. D. Kim, J. Kim, J. Kwon, and T.-H. Kim, "Depth-Controllable Very Deep Super-Resolution Network," in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 2019.
  18. S. Park, J. Kim, D. Kwon, M. Shin, and J. Kim, "Joint Offloading and Streaming in Mobile Edges: A Deep Reinforcement Learning Approach," in Proceedings of the IEEE Asia Pacific Wireless Communications Symposium (APWCS), Singapore, August 2019.
  19. M. U. Sheikh, K. Ruttik, and Riku Jäntti. “DAS and UDN Solutions for Indoor Coverage at Millimeter Wave (mmWave) Frequencies”. Accepted for IEEE 90th Vehicular Technology Conference (VTC’ Fall 2019). Honolulu, Sept. 2019.
  20. M. U. Sheikh, F. Ghavami, K. Ruttik, and Riku Jäntti. “Drone Detection and Classification Using Cellular Network: A Machine Learning Approach”. Accepted for IEEE 90th Vehicular Technology Conference (VTC’ Fall 2019). Honolulu, Sept. 2019.
  21. K. W. Sung et al. “PriMO-5G: making firefighting smarter with immersive videos through 5G”. Accepted for 2019 IEEE 2nd 5G World Forum (5GWF). Dresden, Sept. 2019.
  22. M. U. Sheikh et al. "Usability Bene fits and Challenges in mmWave V2V Communications: A Case Study". Accepted for IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMOB). Barcelona, Oct. 2019.
  23. D. Kwon and J. Kim. “Multi-Agent Deep Reinforcement Learning for Cooperative Connected Vehicles”. Accepted for 2019 IEEE Global Communications Conference (GLOBECOM 2019). Hawaii, Dec. 2019.