Wireless Optimization and Analytics

The advancement of smart devices equipped with sensing, computing, and communication capabilities has led to a wide range of latency-sensitive applications that require efficient and automated operation through wireless connectivity but without direct and pervasive human supervision. We explore new performance engineering approaches that are tailored for these emerging cyber-physical systems and IoT applications.

To this end, the research addresses mathematical modelling, analytical analysis, and efficient algorithms for network planning and configuration, resource allocation, and performance evaluation, with objective ranging from resource efficiency, quality of service, energy consumption, to timeliness and semantics. research also aims at applying optimization as a tool for: 

 

1. Analyzing performance limits in wireless networking, and 
2. deriving data analytics and customized machine learning algorithms.
   

Examples of projects:

• Sparsity-Aware Online Signal Processing with Compressive Sensing (PROVING), funded by Infotech Oulu.
• Sparsity and Information Aging for Wireless Internet of Things (SAFARI), funded by the Academy of Finland.
• IoT / Big Data with advanced analysis tools in the construction industry: Studies of climate-improved, funded by Smart Built Environment.

• The Smart Construction Site, funded by Vinnova

• Compressed Sensing Techniques for Wireless Sensor Networks, Marie Skłodowska-Curie Individual Fellowship funded by European Union Horizon 2020 Programme

• Anticipatory Networking Techniques in 5G and Beyond (ACT5G), funded by European Union Horizon 2020 Programme

• Deploying High-Capacity Dense Small Cell Heterogeneous Networks (DECADE), funded by European Union Horizon 2020 Programme

Collaboration:

• Ericsson
• Combitech
• ELLIIT research excellence center
• Swerock
• Cementa

• Peab