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Computer Science

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49
Citations
10410
World Ranking
5855
National Ranking
38

Electronics and Electrical Engineering

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World Ranking
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Research.com Recognitions

  • 2019 - IEEE Fellow For contributions to source-channel coding and wireless communications

Overview

Mikael Skoglund is affiliated with the Royal Institute of Technology in Sweden. Their research spans the fields of Computer Science and Engineering, with a particular focus on Artificial Intelligence, Electrical and Electronic Engineering, and Computer Networks and Communications. Their work also touches on Molecular Biology and Control and Systems Engineering on a smaller scale.

The scientist has contributed to several main topics, including Wireless Communication Security Techniques, Privacy-Preserving Technologies in Data, Cryptography and Data Security, Cooperative Communication and Network Coding, Advanced MIMO Systems Optimization, Distributed Sensor Networks and Detection Algorithms, and Stochastic Gradient Optimization Techniques.

Frequent co-authors include Tobias J. Oechtering, Ming Xiao, Amirreza Zamani, H. Vincent Poor, and Photios A. Stavrou.

Mikael Skoglund has published extensively in venues such as arXiv (Cornell University), IEEE Transactions on Communications, IEEE Transactions on Information Theory, IEEE Transactions on Automatic Control, and IEEE Transactions on Information Forensics and Security.

Recent papers authored or co-authored by Mikael Skoglund include:

  • Federated Learning Over Wireless IoT Networks With Optimized Communication and Resources, 2022, IEEE Internet of Things Journal
  • Decentralized Beamforming Design for Intelligent Reflecting Surface-Enhanced Cell-Free Networks, 2020, IEEE Wireless Communications Letters
  • The 'New Urban Science': towards the interdisciplinary and transdisciplinary pursuit of sustainable transformations, 2021, Urban Transformations
  • Privacy-Preserving Incremental ADMM for Decentralized Consensus Optimization, 2020, IEEE Transactions on Signal Processing
  • Secure Estimation and Zero-Error Secrecy Capacity, 2020, mediaTUM - the media and publications repository of the Technical University Munich (Technical University Munich)

Mikael Skoglund received the IEEE Fellow award in 2019 for contributions to source-channel coding and wireless communications.

Best Publications

  • Combining beamforming and orthogonal space-time block coding

    G. Jongren;M. Skoglund;B. Ottersten

  • Multiple-User Cooperative Communications Based on Linear Network Coding

    Ming Xiao;Mikael Skoglund

  • Nested Polar Codes for Wiretap and Relay Channels

    M Andersson;V Rathi;R Thobaben;Jörg Kliewer

  • Design of Network Codes for Multiple-User Multiple-Relay Wireless Networks

    Ming Xiao;J. Kliewer;M. Skoglund

  • On the Expected Rate of Slowly Fading Channels With Quantized Side Information

    T.T. Kim;M. Skoglund

  • Subspace Estimation and Decomposition for Large Millimeter-Wave MIMO Systems

    Hadi Ghauch;Taejoon Kim;Mats Bengtsson;Mikael Skoglund

  • Design of network codes for multiple-user multiple-relay wireless networks

    Ming Xiao;Mikael Skoglund

  • On the capacity of a multiple-antenna communication link with channel side information

    M. Skoglund;G. Jongren

  • Hybrid Digital–Analog Source–Channel Coding for Bandwidth Compression/Expansion

    M. Skoglund;N. Phamdo;F. Alajaji

  • Cognitive radio in a frequency-planned environment: some basic limits

    E. Larsson;M. Skoglund

  • Symmetric private information retrieval for MDS coded distributed storage

    Qiwen Wang;Mikael Skoglund

  • Diversity–Multiplexing Tradeoff in MIMO Channels With Partial CSIT

    T.T. Kim;M. Skoglund

  • Federated Learning over Wireless IoT Networks with Optimized Communication and Resources.

    Hao Chen;Shaocheng Huang;Deyou Zhang;Ming Xiao

  • Quantized feedback information in orthogonal space-time block coding

    G. Jongren;M. Skoglund

  • Decentralized Beamforming Design for Intelligent Reflecting Surface-Enhanced Cell-Free Networks

    Shaocheng Huang;Yu Ye;Ming Xiao;H. Vincent Poor

  • Robust utilization of feedback information in space-time coding

    George Jöngren;Mikael Skoglund

  • The Capacity of Private Information Retrieval With Eavesdroppers

    Qiwen Wang;Hua Sun;Mikael Skoglund

  • Utilizing quantized feedback information in orthogonal space-time block coding

    G. Jongren;M. Skoglund

  • Polar Codes for Cooperative Relaying

    R. Blasco-Serrano;R. Thobaben;M. Andersson;V. Rathi

  • Throughput Analysis of ARQ Schemes in Gaussian Block Fading Channels

    Peter Larsson;Lars K. Rasmussen;Mikael Skoglund

  • Distributed quantization over noisy channels

    N. Wernersson;J. Karlsson;M. Skoglund

  • Secure symmetric private information retrieval from colluding databases with adversaries

    Qiwen Wang;Mikael Skoglund

Frequent Co-Authors

Ming Xiao
Ming Xiao Royal Institute of Technology
Lars K. Rasmussen
Lars K. Rasmussen Royal Institute of Technology
Karl Henrik Johansson
Karl Henrik Johansson Royal Institute of Technology
Peter Händel
Peter Händel Royal Institute of Technology
James Gross
James Gross Royal Institute of Technology
Carlo Fischione
Carlo Fischione Royal Institute of Technology
Henrik Sandberg
Henrik Sandberg Royal Institute of Technology
Mats Bengtsson
Mats Bengtsson Royal Institute of Technology
Erik G. Larsson
Erik G. Larsson Linköping University
H. Vincent Poor
H. Vincent Poor Princeton University

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