Mikael Gidlund

Mid Sweden University

Papers

5

Total Citations

162

H-Index

5

About

Mikael Gidlund is a prominent researcher whose work sits at the intersection of industrial wireless communications, the Internet of Things, and next-generation network architectures. His scholarship has made substantial contributions to the evolution of industrial connectivity, from the foundational challenges of Industry 4.0 through to the emerging vision of Industry 5.0. Gidlund's most influential work includes a 2022 study on elastic O-RAN slicing for Industrial IoT environments, which garnered 56 citations and offered a novel distributed matching game and deep reinforcement learning framework to optimize network resource management for real-time industrial applications. His survey work defining the Industry 5.0 vision — accumulated 52 citations — has become a key reference for researchers exploring resilient, sustainable, and human-centric wireless network architectures. Gidlund has also addressed practical challenges such as mobility-aware routing protocols for IIoT networks and the impact of multipath channels on ultra-reliable low-latency communications (URLLC). Collectively, his research provides both conceptual frameworks and engineering solutions that bridge cutting-edge wireless technology with the demanding requirements of modern industrial automation, making his work essential reading for anyone studying smart manufacturing and next-generation connectivity.

Research Focus

Key Achievements

5
H-Index
5
Papers
162
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
Elastic O-RAN Slicing for Industrial Monitoring and Control: A Distributed Matching Game and Deep Reinforcement Learning Approach
56 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Mid Sweden University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago